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Former investment bank FX trader: Risk management part II

Former investment bank FX trader: Risk management part II
Firstly, thanks for the overwhelming comments and feedback. Genuinely really appreciated. I am pleased 500+ of you find it useful.
If you didn't read the first post you can do so here: risk management part I. You'll need to do so in order to make sense of the topic.
As ever please comment/reply below with questions or feedback and I'll do my best to get back to you.
Part II
  • Letting stops breathe
  • When to change a stop
  • Entering and exiting winning positions
  • Risk:reward ratios
  • Risk-adjusted returns

Letting stops breathe

We talked earlier about giving a position enough room to breathe so it is not stopped out in day-to-day noise.
Let’s consider the chart below and imagine you had a trailing stop. It would be super painful to miss out on the wider move just because you left a stop that was too tight.

Imagine being long and stopped out on a meaningless retracement ... ouch!
One simple technique is simply to look at your chosen chart - let’s say daily bars. And then look at previous trends and use the measuring tool. Those generally look something like this and then you just click and drag to measure.
For example if we wanted to bet on a downtrend on the chart above we might look at the biggest retracement on the previous uptrend. That max drawdown was about 100 pips or just under 1%. So you’d want your stop to be able to withstand at least that.
If market conditions have changed - for example if CVIX has risen - and daily ranges are now higher you should incorporate that. If you know a big event is coming up you might think about that, too. The human brain is a remarkable tool and the power of the eye-ball method is not to be dismissed. This is how most discretionary traders do it.
There are also more analytical approaches.
Some look at the Average True Range (ATR). This attempts to capture the volatility of a pair, typically averaged over a number of sessions. It looks at three separate measures and takes the largest reading. Think of this as a moving average of how much a pair moves.
For example, below shows the daily move in EURUSD was around 60 pips before spiking to 140 pips in March. Conditions were clearly far more volatile in March. Accordingly, you would need to leave your stop further away in March and take a correspondingly smaller position size.

ATR is available on pretty much all charting systems
Professional traders tend to use standard deviation as a measure of volatility instead of ATR. There are advantages and disadvantages to both. Averages are useful but can be misleading when regimes switch (see above chart).
Once you have chosen a measure of volatility, stop distance can then be back-tested and optimised. For example does 2x ATR work best or 5x ATR for a given style and time horizon?
Discretionary traders may still eye-ball the ATR or standard deviation to get a feeling for how it has changed over time and what ‘normal’ feels like for a chosen study period - daily, weekly, monthly etc.

Reasons to change a stop

As a general rule you should be disciplined and not change your stops. Remember - losers average losers. This is really hard at first and we’re going to look at that in more detail later.
There are some good reasons to modify stops but they are rare.
One reason is if another risk management process demands you stop trading and close positions. We’ll look at this later. In that case just close out your positions at market and take the loss/gains as they are.
Another is event risk. If you have some big upcoming data like Non Farm Payrolls that you know can move the market +/- 150 pips and you have no edge going into the release then many traders will take off or scale down their positions. They’ll go back into the positions when the data is out and the market has quietened down after fifteen minutes or so. This is a matter of some debate - many traders consider it a coin toss and argue you win some and lose some and it all averages out.
Trailing stops can also be used to ‘lock in’ profits. We looked at those before. As the trade moves in your favour (say up if you are long) the stop loss ratchets with it. This means you may well end up ‘stopping out’ at a profit - as per the below example.

The mighty trailing stop loss order
It is perfectly reasonable to have your stop loss move in the direction of PNL. This is not exposing you to more risk than you originally were comfortable with. It is taking less and less risk as the trade moves in your favour. Trend-followers in particular love trailing stops.
One final question traders ask is what they should do if they get stopped out but still like the trade. Should they try the same trade again a day later for the same reasons? Nope. Look for a different trade rather than getting emotionally wed to the original idea.
Let’s say a particular stock looked cheap based on valuation metrics yesterday, you bought, it went down and you got stopped out. Well, it is going to look even better on those same metrics today. Maybe the market just doesn’t respect value at the moment and is driven by momentum. Wait it out.
Otherwise, why even have a stop in the first place?

Entering and exiting winning positions

Take profits are the opposite of stop losses. They are also resting orders, left with the broker, to automatically close your position if it reaches a certain price.
Imagine I’m long EURUSD at 1.1250. If it hits a previous high of 1.1400 (150 pips higher) I will leave a sell order to take profit and close the position.
The rookie mistake on take profits is to take profit too early. One should start from the assumption that you will win on no more than half of your trades. Therefore you will need to ensure that you win more on the ones that work than you lose on those that don’t.

Sad to say but incredibly common: retail traders often take profits way too early
This is going to be the exact opposite of what your emotions want you to do. We are going to look at that in the Psychology of Trading chapter.
Remember: let winners run. Just like stops you need to know in advance the level where you will close out at a profit. Then let the trade happen. Don’t override yourself and let emotions force you to take a small profit. A classic mistake to avoid.
The trader puts on a trade and it almost stops out before rebounding. As soon as it is slightly in the money they spook and cut out, instead of letting it run to their original take profit. Do not do this.

Entering positions with limit orders

That covers exiting a position but how about getting into one?
Take profits can also be left speculatively to enter a position. Sometimes referred to as “bids” (buy orders) or “offers” (sell orders). Imagine the price is 1.1250 and the recent low is 1.1205.
You might wish to leave a bid around 1.2010 to enter a long position, if the market reaches that price. This way you don’t need to sit at the computer and wait.
Again, typically traders will use tech analysis to identify attractive levels. Again - other traders will cluster with your orders. Just like the stop loss we need to bake that in.
So this time if we know everyone is going to buy around the recent low of 1.1205 we might leave the take profit bit a little bit above there at 1.1210 to ensure it gets done. Sure it costs 5 more pips but how mad would you be if the low was 1.1207 and then it rallied a hundred points and you didn’t have the trade on?!
There are two more methods that traders often use for entering a position.
Scaling in is one such technique. Let’s imagine that you think we are in a long-term bulltrend for AUDUSD but experiencing a brief retracement. You want to take a total position of 500,000 AUD and don’t have a strong view on the current price action.
You might therefore leave a series of five bids of 100,000. As the price moves lower each one gets hit. The nice thing about scaling in is it reduces pressure on you to pick the perfect level. Of course the risk is that not all your orders get hit before the price moves higher and you have to trade at-market.
Pyramiding is the second technique. Pyramiding is for take profits what a trailing stop loss is to regular stops. It is especially common for momentum traders.

Pyramiding into a position means buying more as it goes in your favour
Again let’s imagine we’re bullish AUDUSD and want to take a position of 500,000 AUD.
Here we add 100,000 when our first signal is reached. Then we add subsequent clips of 100,000 when the trade moves in our favour. We are waiting for confirmation that the move is correct.
Obviously this is quite nice as we humans love trading when it goes in our direction. However, the drawback is obvious: we haven’t had the full amount of risk on from the start of the trend.
You can see the attractions and drawbacks of both approaches. It is best to experiment and choose techniques that work for your own personal psychology as these will be the easiest for you to stick with and build a disciplined process around.

Risk:reward and win ratios

Be extremely skeptical of people who claim to win on 80% of trades. Most traders will win on roughly 50% of trades and lose on 50% of trades. This is why risk management is so important!
Once you start keeping a trading journal you’ll be able to see how the win/loss ratio looks for you. Until then, assume you’re typical and that every other trade will lose money.
If that is the case then you need to be sure you make more on the wins than you lose on the losses. You can see the effect of this below.

A combination of win % and risk:reward ratio determine if you are profitable
A typical rule of thumb is that a ratio of 1:3 works well for most traders.
That is, if you are prepared to risk 100 pips on your stop you should be setting a take profit at a level that would return you 300 pips.
One needn’t be religious about these numbers - 11 pips and 28 pips would be perfectly fine - but they are a guideline.
Again - you should still use technical analysis to find meaningful chart levels for both the stop and take profit. Don’t just blindly take your stop distance and do 3x the pips on the other side as your take profit. Use the ratio to set approximate targets and then look for a relevant resistance or support level in that kind of region.

Risk-adjusted returns

Not all returns are equal. Suppose you are examining the track record of two traders. Now, both have produced a return of 14% over the year. Not bad!
The first trader, however, made hundreds of small bets throughout the year and his cumulative PNL looked like the left image below.
The second trader made just one bet — he sold CADJPY at the start of the year — and his PNL looked like the right image below with lots of large drawdowns and volatility.
Would you rather have the first trading record or the second?
If you were investing money and betting on who would do well next year which would you choose? Of course all sensible people would choose the first trader. Yet if you look only at returns one cannot distinguish between the two. Both are up 14% at that point in time. This is where the Sharpe ratio helps .
A high Sharpe ratio indicates that a portfolio has better risk-adjusted performance. One cannot sensibly compare returns without considering the risk taken to earn that return.
If I can earn 80% of the return of another investor at only 50% of the risk then a rational investor should simply leverage me at 2x and enjoy 160% of the return at the same level of risk.
This is very important in the context of Execution Advisor algorithms (EAs) that are popular in the retail community. You must evaluate historic performance by its risk-adjusted return — not just the nominal return. Incidentally look at the Sharpe ratio of ones that have been live for a year or more ...
Otherwise an EA developer could produce two EAs: the first simply buys at 1000:1 leverage on January 1st ; and the second sells in the same manner. At the end of the year, one of them will be discarded and the other will look incredible. Its risk-adjusted return, however, would be abysmal and the odds of repeated success are similarly poor.

Sharpe ratio

The Sharpe ratio works like this:
  • It takes the average returns of your strategy;
  • It deducts from these the risk-free rate of return i.e. the rate anyone could have got by investing in US government bonds with very little risk;
  • It then divides this total return by its own volatility - the more smooth the return the higher and better the Sharpe, the more volatile the lower and worse the Sharpe.
For example, say the return last year was 15% with a volatility of 10% and US bonds are trading at 2%. That gives (15-2)/10 or a Sharpe ratio of 1.3. As a rule of thumb a Sharpe ratio of above 0.5 would be considered decent for a discretionary retail trader. Above 1 is excellent.
You don’t really need to know how to calculate Sharpe ratios. Good trading software will do this for you. It will either be available in the system by default or you can add a plug-in.

VAR

VAR is another useful measure to help with drawdowns. It stands for Value at Risk. Normally people will use 99% VAR (conservative) or 95% VAR (aggressive). Let’s say you’re long EURUSD and using 95% VAR. The system will look at the historic movement of EURUSD. It might spit out a number of -1.2%.

A 5% VAR of -1.2% tells you you should expect to lose 1.2% on 5% of days, whilst 95% of days should be better than that
This means it is expected that on 5 days out of 100 (hence the 95%) the portfolio will lose 1.2% or more. This can help you manage your capital by taking appropriately sized positions. Typically you would look at VAR across your portfolio of trades rather than trade by trade.
Sharpe ratios and VAR don’t give you the whole picture, though. Legendary fund manager, Howard Marks of Oaktree, notes that, while tools like VAR and Sharpe ratios are helpful and absolutely necessary, the best investors will also overlay their own judgment.
Investors can calculate risk metrics like VaR and Sharpe ratios (we use them at Oaktree; they’re the best tools we have), but they shouldn’t put too much faith in them. The bottom line for me is that risk management should be the responsibility of every participant in the investment process, applying experience, judgment and knowledge of the underlying investments.Howard Marks of Oaktree Capital
What he’s saying is don’t misplace your common sense. Do use these tools as they are helpful. However, you cannot fully rely on them. Both assume a normal distribution of returns. Whereas in real life you get “black swans” - events that should supposedly happen only once every thousand years but which actually seem to happen fairly often.
These outlier events are often referred to as “tail risk”. Don’t make the mistake of saying “well, the model said…” - overlay what the model is telling you with your own common sense and good judgment.

Coming up in part III

Available here
Squeezes and other risks
Market positioning
Bet correlation
Crap trades, timeouts and monthly limits

***
Disclaimer:This content is not investment advice and you should not place any reliance on it. The views expressed are the author's own and should not be attributed to any other person, including their employer.
submitted by getmrmarket to Forex [link] [comments]

Former investment bank FX trader: some thoughts

Former investment bank FX trader: some thoughts
Hi guys,
I have been using reddit for years in my personal life (not trading!) and wanted to give something back in an area where i am an expert.
I worked at an investment bank for seven years and joined them as a graduate FX trader so have lots of professional experience, by which i mean I was trained and paid by a big institution to trade on their behalf. This is very different to being a full-time home trader, although that is not to discredit those guys, who can accumulate a good amount of experience/wisdom through self learning.
When I get time I'm going to write a mid-length posts on each topic for you guys along the lines of how i was trained. I guess there would be 15-20 topics in total so about 50-60 posts. Feel free to comment or ask questions.
The first topic is Risk Management and we'll cover it in three parts
Part I
  • Why it matters
  • Position sizing
  • Kelly
  • Using stops sensibly
  • Picking a clear level

Why it matters

The first rule of making money through trading is to ensure you do not lose money. Look at any serious hedge fund’s website and they’ll talk about their first priority being “preservation of investor capital.”
You have to keep it before you grow it.
Strangely, if you look at retail trading websites, for every one article on risk management there are probably fifty on trade selection. This is completely the wrong way around.
The great news is that this stuff is pretty simple and process-driven. Anyone can learn and follow best practices.
Seriously, avoiding mistakes is one of the most important things: there's not some holy grail system for finding winning trades, rather a routine and fairly boring set of processes that ensure that you are profitable, despite having plenty of losing trades alongside the winners.

Capital and position sizing

The first thing you have to know is how much capital you are working with. Let’s say you have $100,000 deposited. This is your maximum trading capital. Your trading capital is not the leveraged amount. It is the amount of money you have deposited and can withdraw or lose.
Position sizing is what ensures that a losing streak does not take you out of the market.
A rule of thumb is that one should risk no more than 2% of one’s account balance on an individual trade and no more than 8% of one’s account balance on a specific theme. We’ll look at why that’s a rule of thumb later. For now let’s just accept those numbers and look at examples.
So we have $100,000 in our account. And we wish to buy EURUSD. We should therefore not be risking more than 2% which $2,000.
We look at a technical chart and decide to leave a stop below the monthly low, which is 55 pips below market. We’ll come back to this in a bit. So what should our position size be?
We go to the calculator page, select Position Size and enter our details. There are many such calculators online - just google "Pip calculator".

https://preview.redd.it/y38zb666e5h51.jpg?width=1200&format=pjpg&auto=webp&s=26e4fe569dc5c1f43ce4c746230c49b138691d14
So the appropriate size is a buy position of 363,636 EURUSD. If it reaches our stop level we know we’ll lose precisely $2,000 or 2% of our capital.
You should be using this calculator (or something similar) on every single trade so that you know your risk.
Now imagine that we have similar bets on EURJPY and EURGBP, which have also broken above moving averages. Clearly this EUR-momentum is a theme. If it works all three bets are likely to pay off. But if it goes wrong we are likely to lose on all three at once. We are going to look at this concept of correlation in more detail later.
The total amount of risk in our portfolio - if all of the trades on this EUR-momentum theme were to hit their stops - should not exceed $8,000 or 8% of total capital. This allows us to go big on themes we like without going bust when the theme does not work.
As we’ll see later, many traders only win on 40-60% of trades. So you have to accept losing trades will be common and ensure you size trades so they cannot ruin you.
Similarly, like poker players, we should risk more on trades we feel confident about and less on trades that seem less compelling. However, this should always be subject to overall position sizing constraints.
For example before you put on each trade you might rate the strength of your conviction in the trade and allocate a position size accordingly:

https://preview.redd.it/q2ea6rgae5h51.png?width=1200&format=png&auto=webp&s=4332cb8d0bbbc3d8db972c1f28e8189105393e5b
To keep yourself disciplined you should try to ensure that no more than one in twenty trades are graded exceptional and allocated 5% of account balance risk. It really should be a rare moment when all the stars align for you.
Notice that the nice thing about dealing in percentages is that it scales. Say you start out with $100,000 but end the year up 50% at $150,000. Now a 1% bet will risk $1,500 rather than $1,000. That makes sense as your capital has grown.
It is extremely common for retail accounts to blow-up by making only 4-5 losing trades because they are leveraged at 50:1 and have taken on far too large a position, relative to their account balance.
Consider that GBPUSD tends to move 1% each day. If you have an account balance of $10k then it would be crazy to take a position of $500k (50:1 leveraged). A 1% move on $500k is $5k.
Two perfectly regular down days in a row — or a single day’s move of 2% — and you will receive a margin call from the broker, have the account closed out, and have lost all your money.
Do not let this happen to you. Use position sizing discipline to protect yourself.

Kelly Criterion

If you’re wondering - why “about 2%” per trade? - that’s a fair question. Why not 0.5% or 10% or any other number?
The Kelly Criterion is a formula that was adapted for use in casinos. If you know the odds of winning and the expected pay-off, it tells you how much you should bet in each round.
This is harder than it sounds. Let’s say you could bet on a weighted coin flip, where it lands on heads 60% of the time and tails 40% of the time. The payout is $2 per $1 bet.
Well, absolutely you should bet. The odds are in your favour. But if you have, say, $100 it is less obvious how much you should bet to avoid ruin.
Say you bet $50, the odds that it could land on tails twice in a row are 16%. You could easily be out after the first two flips.
Equally, betting $1 is not going to maximise your advantage. The odds are 60/40 in your favour so only betting $1 is likely too conservative. The Kelly Criterion is a formula that produces the long-run optimal bet size, given the odds.
Applying the formula to forex trading looks like this:
Position size % = Winning trade % - ( (1- Winning trade %) / Risk-reward ratio
If you have recorded hundreds of trades in your journal - see next chapter - you can calculate what this outputs for you specifically.
If you don't have hundreds of trades then let’s assume some realistic defaults of Winning trade % being 30% and Risk-reward ratio being 3. The 3 implies your TP is 3x the distance of your stop from entry e.g. 300 pips take profit and 100 pips stop loss.
So that’s 0.3 - (1 - 0.3) / 3 = 6.6%.
Hold on a second. 6.6% of your account probably feels like a LOT to risk per trade.This is the main observation people have on Kelly: whilst it may optimise the long-run results it doesn’t take into account the pain of drawdowns. It is better thought of as the rational maximum limit. You needn’t go right up to the limit!
With a 30% winning trade ratio, the odds of you losing on four trades in a row is nearly one in four. That would result in a drawdown of nearly a quarter of your starting account balance. Could you really stomach that and put on the fifth trade, cool as ice? Most of us could not.
Accordingly people tend to reduce the bet size. For example, let’s say you know you would feel emotionally affected by losing 25% of your account.
Well, the simplest way is to divide the Kelly output by four. You have effectively hidden 75% of your account balance from Kelly and it is now optimised to avoid a total wipeout of just the 25% it can see.
This gives 6.6% / 4 = 1.65%. Of course different trading approaches and different risk appetites will provide different optimal bet sizes but as a rule of thumb something between 1-2% is appropriate for the style and risk appetite of most retail traders.
Incidentally be very wary of systems or traders who claim high winning trade % like 80%. Invariably these don’t pass a basic sense-check:
  • How many live trades have you done? Often they’ll have done only a handful of real trades and the rest are simulated backtests, which are overfitted. The model will soon die.
  • What is your risk-reward ratio on each trade? If you have a take profit $3 away and a stop loss $100 away, of course most trades will be winners. You will not be making money, however! In general most traders should trade smaller position sizes and less frequently than they do. If you are going to bias one way or the other, far better to start off too small.

How to use stop losses sensibly

Stop losses have a bad reputation amongst the retail community but are absolutely essential to risk management. No serious discretionary trader can operate without them.
A stop loss is a resting order, left with the broker, to automatically close your position if it reaches a certain price. For a recap on the various order types visit this chapter.
The valid concern with stop losses is that disreputable brokers look for a concentration of stops and then, when the market is close, whipsaw the price through the stop levels so that the clients ‘stop out’ and sell to the broker at a low rate before the market naturally comes back higher. This is referred to as ‘stop hunting’.
This would be extremely immoral behaviour and the way to guard against it is to use a highly reputable top-tier broker in a well regulated region such as the UK.
Why are stop losses so important? Well, there is no other way to manage risk with certainty.
You should always have a pre-determined stop loss before you put on a trade. Not having one is a recipe for disaster: you will find yourself emotionally attached to the trade as it goes against you and it will be extremely hard to cut the loss. This is a well known behavioural bias that we’ll explore in a later chapter.
Learning to take a loss and move on rationally is a key lesson for new traders.
A common mistake is to think of the market as a personal nemesis. The market, of course, is totally impersonal; it doesn’t care whether you make money or not.
Bruce Kovner, founder of the hedge fund Caxton Associates
There is an old saying amongst bank traders which is “losers average losers”.
It is tempting, having bought EURUSD and seeing it go lower, to buy more. Your average price will improve if you keep buying as it goes lower. If it was cheap before it must be a bargain now, right? Wrong.
Where does that end? Always have a pre-determined cut-off point which limits your risk. A level where you know the reason for the trade was proved ‘wrong’ ... and stick to it strictly. If you trade using discretion, use stops.

Picking a clear level

Where you leave your stop loss is key.
Typically traders will leave them at big technical levels such as recent highs or lows. For example if EURUSD is trading at 1.1250 and the recent month’s low is 1.1205 then leaving it just below at 1.1200 seems sensible.

If you were going long, just below the double bottom support zone seems like a sensible area to leave a stop
You want to give it a bit of breathing room as we know support zones often get challenged before the price rallies. This is because lots of traders identify the same zones. You won’t be the only one selling around 1.1200.
The “weak hands” who leave their sell stop order at exactly the level are likely to get taken out as the market tests the support. Those who leave it ten or fifteen pips below the level have more breathing room and will survive a quick test of the level before a resumed run-up.
Your timeframe and trading style clearly play a part. Here’s a candlestick chart (one candle is one day) for GBPUSD.

https://preview.redd.it/moyngdy4f5h51.png?width=1200&format=png&auto=webp&s=91af88da00dd3a09e202880d8029b0ddf04fb802
If you are putting on a trend-following trade you expect to hold for weeks then you need to have a stop loss that can withstand the daily noise. Look at the downtrend on the chart. There were plenty of days in which the price rallied 60 pips or more during the wider downtrend.
So having a really tight stop of, say, 25 pips that gets chopped up in noisy short-term moves is not going to work for this kind of trade. You need to use a wider stop and take a smaller position size, determined by the stop level.
There are several tools you can use to help you estimate what is a safe distance and we’ll look at those in the next section.
There are of course exceptions. For example, if you are doing range-break style trading you might have a really tight stop, set just below the previous range high.

https://preview.redd.it/ygy0tko7f5h51.png?width=1200&format=png&auto=webp&s=34af49da61c911befdc0db26af66f6c313556c81
Clearly then where you set stops will depend on your trading style as well as your holding horizons and the volatility of each instrument.
Here are some guidelines that can help:
  1. Use technical analysis to pick important levels (support, resistance, previous high/lows, moving averages etc.) as these provide clear exit and entry points on a trade.
  2. Ensure that the stop gives your trade enough room to breathe and reflects your timeframe and typical volatility of each pair. See next section.
  3. Always pick your stop level first. Then use a calculator to determine the appropriate lot size for the position, based on the % of your account balance you wish to risk on the trade.
So far we have talked about price-based stops. There is another sort which is more of a fundamental stop, used alongside - not instead of - price stops. If either breaks you’re out.
For example if you stop understanding why a product is going up or down and your fundamental thesis has been confirmed wrong, get out. For example, if you are long because you think the central bank is turning hawkish and AUDUSD is going to play catch up with rates … then you hear dovish noises from the central bank and the bond yields retrace lower and back in line with the currency - close your AUDUSD position. You already know your thesis was wrong. No need to give away more money to the market.

Coming up in part II

EDIT: part II here
Letting stops breathe
When to change a stop
Entering and exiting winning positions
Risk:reward ratios
Risk-adjusted returns

Coming up in part III

Squeezes and other risks
Market positioning
Bet correlation
Crap trades, timeouts and monthly limits

***
Disclaimer:This content is not investment advice and you should not place any reliance on it. The views expressed are the author's own and should not be attributed to any other person, including their employer.
submitted by getmrmarket to Forex [link] [comments]

The Truth

The Truth submitted by Mobilenewsflash to Forex [link] [comments]

I Automated & Backtested ParallaxFX Strategy

I am a Software Engineer / Data Scientist and I decided to give a go at automating a strategy based on the ParallaxFX strategy floating around and backtests the results, also due to some inspiration by Vanguer
 
I backtested on the majors 4H timeframe between January 2015 to January 2020.
 
I am only considering trades from the top and bottom bands for now.
 
My trading criteria is:
 
Upper Band
Indecision candle
Setup candle
 
Lower Band
Indecision candle
Setup candle
 
Entry: 38.2 Fib
Stop Loss: 100 Fib
Take Profit: -161.8 Fib
RRR: 3.23
 
If a candle meets my trade criteria I open the trade and forget about it.
 
I started with a balance of 500 EUR and a risk of 1%. The results use compound gain / loss and I only considered one currency pair at a time.
 
The results were not that impressive...
EUUSD
AUD/USD
GBP/USD
NZD/USD
USD/CAD
USD/CHF
 
Due to this being automated I can test a variety of parameters pretty quickly and come back with trading screenshots, results, etc.
 
I am considering a higher timeframe but the number of trades is already fairly low.
 
Here is a link to a Google Drive (https://drive.google.com/drive/folders/16cO0ZSCGakkbK90lh-FBIC3ZJIxOj9fI?usp=sharing) with screenshots from each trade and a log of the system as it makes the trades. The candles highlighted in yellow / purple are where the trade is entered. I do not have the picture marked as a win / lose but it should be obvious by the candle formation.
submitted by TribeFX to Forex [link] [comments]

Looking for a Trading Accountability Buddy

Hello Fellow Redditor Traders,
I realized that trading a particular system is not about the system itself but on the approach of the user, an infinite amount of strategies exist out there and if a user is littered with a negative, inpatient, impulsive, loss averse, etc mindset than not even the "top" performing strategies would be of use. Thus, to me it seems that I get into this negative mindset from time to time, going into frequent draw-downs and consistent losses (low success rate) but fortunately with adequate risk management (to an extent) which kept my capital alive for this past year of actively trading the Forex market (-15% thus far). I am detail oriented and have a very detailed journal of every trade I take/ took (>500 trades mainly Forex) with statistical calculations on the different strategies that I have formulated, implemented, and back-tested manually (and have mostly failed due to user error in live markets). I can help with providing reflection on the trade setups technically and fundamentally, formulating a trading plan from scratch, formulating strategies, establishing adequate risk management and provide self-reflection as I fully know how it could be when stuck in a negative cycle.
I need someone to reciprocate accountability with (Currently at GMT +4 but wont mind the time difference in effort to make this work), I have a trend continuation based strategy that can work if I have the right mindset towards it, thus I would like to find someone to hold me accountable for the trades I enter during the week (end of week review) and also share ideas with back and forth on the different setups that are provided during the week.
Anyone serious about trading is welcome!
Regards, Z
submitted by ZzRedditor to Trading [link] [comments]

I'm a strategy lover and it's a real problem now

Hi everyone,
I have been learning about Forex for almost 2 years now.
But I have a real problem. I am a strategy lover. I hop from one strategy to another due to various reasons.
How it works: 1. I find a strategy 2. I fall in love with it 3. I learn about it, backtest it, demo trade it, etc. 4. I find something to nitpick 5. Leave the strategy and go back to point 1
In the past 2 years, I must have burned through over 20-30 strategies. I have gone through scalping, swing trading, full discretionary trading, full system based trading, half discretionary and half system based strategies, etc
I just can't seem to stick with a strategy after the honeymoon phase. Either I get tired of the strategy, or backtesting reveals it isnt profitable, or it too discretionary, or it is too system based, etc.
Once again, I left another strategy and am going back to point 1, finding a new strategy. I found a new strategy, which is the one posted by ParallaxFX. Already 2 people have backtested it and it was profitable. But even with this information, I know that I will go through the strategy, I will love it at first, I will test, then ultimately I wont stick with it and then leave it and then go back to point 1.
I like the fact it is mostly a system based strategy and lately I have tested a lot of strategies that are 50% system based and 50% discretionary. The only thing I have learned so far is that I would probably be more comfortable trading a system based strategy rather than a full discretionary one.
This is a big issue for me always and I dont know how to overcome it. It was fine in the beginning because I was a new trader and to go through strategies is just part of trading in the beginning. But now it's been almost 2 years and I have to admit now that I have a real problem that needs to be addressed. Otherwise at this rate, I will still be doing this in 5-10 years.
It seems like most people find a strategy and stick with it, but then struggle with risk management. But I'm stuck at the strategy part and I cant progress.
How do I overcome this? What steps can I take so this doesn't happen? Do I need a mentor at this point?
Any help is welcome!
submitted by forexguyz643 to Forex [link] [comments]

Trading Accountability Buddy

Hello Fellow Redditor Traders,
I realized that trading a particular system is not about the system itself but on the approach of the user, an infinite amount of strategies exist out there and if a user is littered with a negative, inpatient, impulsive, loss averse, etc mindset than not even the "top" performing strategies would be of use. Thus, to me it seems that I get into this negative mindset from time to time, going into frequent draw-downs and consistent losses (low success rate) but fortunately with adequate risk management (to an extent) which kept my capital alive for this past year of actively trading the Forex market (-15% thus far). I am detail oriented and have a very detailed journal of every trade I take/ took (>500 trades mainly Forex) with statistical calculations on the different strategies that I have formulated, implemented, and back-tested manually (and have mostly failed due to user error in live markets). I can help with providing reflection on the trade setups technically and fundamentally, formulating a trading plan from scratch, formulating strategies, establishing adequate risk management and provide self-reflection as I fully know how it could be when stuck in a negative cycle.
I need someone to reciprocate accountability with (Currently at GMT +4 but wont mind the time difference in effort to make this work), I have a trend continuation based strategy that can work if I have the right mindset towards it, thus I would like to find someone to hold me accountable for the trades I enter during the week (end of week review) and also share ideas with back and forth on the different setups that are provided during the week.
Anyone serious about trading is welcome!
Regards, Z
submitted by ZzRedditor to Daytrading [link] [comments]

When will we bottom out?

PART 2 : https://www.reddit.com/wallstreetbets/comments/g0sd44/what_is_the_bottom/
PART 3: https://www.reddit.com/wallstreetbets/comments/g2enz2/why_the_printer_must_continue/
Edit: By popular demand, the too long didn't read is now at the top
TL;DR
SPY 220p 11/20
This will likely be a multi-part series. It should be noted that I am no expert by any means, I'm actually quite new to this, it is just an elementary analysis of patterns in price and time. I am not a financial advisor, and this is not advice for a person to enter trades upon.
The fundamental divide in trading revolves around the question of market structure. Many feel that the market operates totally randomly and its’ behavior cannot be predicted. For the purposes of this DD, we will assume that the market has a structure, but that that structure is not perfect. That market structure naturally generates chart patterns as the market records prices in time. We will analyze an instrument, an exchange traded fund, which represents an index, as opposed to a particular stock. The price patterns of the various stocks in an index are effectively smoothed out. In doing so, a more technical picture arises. Perhaps the most popular of these is the SPDR S&P Standard and Poor 500 Exchange Traded Fund ($SPY).
In trading, little to no concern is given about value of underlying asset. We concerned primarily about liquidity and trading ranges, which are the amount of value fluctuating on a short-term basis, as measured by volatility-implied trading ranges. Fundamental analysis plays a role, however markets often do not react to real-world factors in a logical fashion. Therefore, fundamental analysis is more appropriate for long-term investing.
The fundamental derivatives of a chart are time (x-axis) and price (y-axis). The primary technical indicator is price, as everything else is lagging in the past. Price represents current asking price and incorrectly implementing positions based on price is one of the biggest trading errors.
Markets ordinarily have noise, their tendency to back-and-fill, which must be filtered out for true pattern recognition. That noise does have a utility, however, in allowing traders second chances to enter favorable positions at slightly less favorable entry points. When you have any market with enough liquidity for historical data to record a pattern, then a structure can be divined. The market probes prices as part of an ongoing price-discovery process. Market technicians must sometimes look outside of the technical realm and use visual inspection to ascertain the relevance of certain patterns, using a qualitative eye that recognizes the underlying quantitative nature
Markets rise slower than they correct, however they rise much more than they fall. In the same vein, instruments can only fall to having no worth, whereas they could theoretically grow infinitely and have continued to grow over time. Money in a fiat system is illusory. It is a fundamentally synthetic instrument which has no intrinsic value. Hence, the recent seemingly illogical fluctuations in the market.
According to trade theory, the unending purpose of a market is to create and break price ranges according to the laws of supply and demand. We must determine when to trade based on each market inflection point as defined in price and in time as opposed to abandoning the trend (as the contrarian trading in this sub often does). Time and Price symmetry must be used to be in accordance with the trend. When coupled with a favorable risk to reward ratio, the ability to stay in the market for most of the defined time period, and adherence to risk management rules; the trader has a solid methodology for achieving considerable gains.
We will engage in a longer term market-oriented analysis to avoid any time-focused pressure. The market is technically open 24-hours a day, so trading may be done when the individual is ready, without any pressing need to be constantly alert. Let alone, we can safely project months in advance with relatively high accuracy.
Some important terms to keep in mind:
§ Discrete – terminal points at the extremes of ranges
§ Secondary Discrete – quantified retracement or correction between two discrete
§ Longs (asset appreciation) and shorts (asset depreciation)
- Technical indicators are often considered self-fulfilling prophecies due to mass-market psychology gravitating towards certain common numbers yielded from them. That means a trader must be especially aware of these numbers as they can prognosticate market movements. Often, they are meaningless in the larger picture of things.
§ Volume – derived from the market itself, it is mostly irrelevant. The major problem with volume is that the US market open causes tremendous volume surges eradicating any intrinsic volume analysis. At major highs and lows, the market is typically anemic. Most traders are not active at terminal discretes because of levels of fear. Allows us confidence in time and price symmetry market inflection points, if we observe low volume at a foretold range of values. We can rationalize that an absolute discrete is usually only discovered and anticipated by very few traders. As the general market realizes it, a herd mentality will push the market in the direction favorable to defending it. Volume is also useful for swing trading, as chances for swing’s validity increases if an increase in volume is seen on and after the swing’s activation.
Therefore, due to the relatively high volume on the 23rd of March, we can safely determine that a low WAS NOT reached.
§ VIX – Volatility Index, this technical indicator indicates level of fear by the amount of options-based “insurance” in portfolios. A low VIX environment, less than 20 for the S&P index, indicates a stable market with a possible uptrend. A high VIX, over 20, indicates a possible downtrend. However, it is equally important to see how VIX is changing over time, if it is decreasing or increasing, as that indicates increasing or decreasing fear. Low volatility allows high leverage without risk or rest. Occasionally, markets do rise with high VIX.
As VIX is unusually high, in the forties, we can be confident that a downtrend is imminent.
– Trend definition is highly powerful, cannot be understated. Knowledge of trend logic is enough to be a profitable trader, yet defining a trend is an arduous process. Multiple trends coexist across multiple time frames and across multiple market sectors. Like time structure, it makes the underlying price of the instrument irrelevant. Trend definitions cannot determine the validity of newly formed discretes. Trend becomes apparent when trades based in counter-trend inflection points continue to fail.
Downtrends are defined as an instrument making lower lows and lower highs that are recurrent, additive, qualified swing setups. Downtrends for all instruments are similar, except forex. They are fast and complete much quicker than uptrends. An average downtrend is 18 months, something which we will return to. An uptrend inception occurs when an instrument reaches a point where it fails to make a new low, then that low will be tested. After that, the instrument will either have a deep range retracement or it may take out the low slightly, resulting in a double-bottom. A swing must eventually form.
A simple way to roughly determine trend is to attempt to draw a line from three tops going upwards (uptrend) or a line from three bottoms going downwards (downtrend). It is not possible to correctly draw an uptrend line on the SPY chart, but it is possible to correctly draw a downtrend – indicating that the overall trend is downwards.
Now that we have determined that the overall trend is downwards, the next issue is the question of when SPY will bottom out.
Time is the movement from the past through the present into the future. It is a measurement in quantified intervals. In many ways, our perception of it is a human construct. It is more powerful than price as time may be utilized for a trade regardless of the market inflection point’s price. Were it possible to perfectly understand time, price would be totally irrelevant due to the predictive certainty time affords. Time structure is easier to learn than price, but much more difficult to apply with any accuracy. It is the hardest aspect of trading to learn, but also the most rewarding.
Humans do not have the ability to recognize every time window, however the ability to define market inflection points in terms of time is the single most powerful trading edge. Regardless, price should not be abandoned for time alone. Time structure analysis It is inherently flawed, as such the markets have a fail-safe, which is Price Structure. Even though Time is much more powerful, Price Structure should never be completely ignored. Time is the qualifier for Price and vice versa. Time can fail by tricking traders into counter-trend trading.
Time is a predestined trade quantifier, a filter to slow trades down, as it allows a trader to specifically focus on specific time windows and rest at others. It allows for quantitative measurements to reach deterministic values and is the primary qualifier for trends. Time structure should be utilized before price structure, and it is the primary trade criterion which requires support from price. We can see price structure on a chart, as areas of mathematical support or resistance, but we cannot see time structure.
Time may be used to tell us an exact point in the future where the market will inflect, after Price Theory has been fulfilled. In the present, price objectives based on price theory added to possible future times for market inflection points give us the exact time of market inflection points and price.
Time Structure is repetitions of time or inherent cycles of time, occurring in a methodical way to provide time windows which may be utilized for inflection points. They are not easily recognized and not easily defined by a price chart as measuring and observing time is very exact. Time structure is not a science, yet it does require precise measurements. Nothing is certain or definite. The critical question must be if a particular approach to time structure is currently lucrative or not.
We will complete our analysis of time by measuring it in intervals of 180 bars. Our goal is to determine time windows, when the market will react and when we should pay the most attention. By using time repetitions, the fact that market inflection points occurred at some point in the past and should, therefore, reoccur at some point in the future, we should obtain confidence as to when SPY will reach a market inflection point. Time repetitions are essentially the market’s memory. However, simply measuring the time between two points then trying to extrapolate into the future does not work. Measuring time is not the same as defining time repetitions. We will evaluate past sessions for market inflection points, whether discretes, qualified swings, or intra-range. Then records the times that the market has made highs or lows in a comparable time period to the future one seeks to trade in.
What follows is a time Histogram – A grouping of times which appear close together, then segregated based on that closeness. Time is aligned into combined histogram of repetitions and cycles, however cycles are irrelevant on a daily basis. If trading on an hourly basis, do not use hours.
Yearly Lows: 12/31/2000, 9/21/2001, 10/9/2002, 3/11/2003, 8/2/2004, 4/15/2005, 6/12/2006, 3/5/2007, 11/17/2008, 3/9/2009, 7/2/10, 10/3/11, 1/1/12, 1/1/13, 2/3/14, 9/28/15, 2/8/16, 1/3/17, 12/24/18, 6/3/19
Months: 1, 1, 1, 2, 2, 3, 3, 3, 4, 6, 6, 7, 8, 9, 9, 10, 10, 11, 12, 12
Days: 1, 1, 2, 2, 3, 3, 3, 3, 5, 8, 9, 9, 11, 12, 15, 17, 21, 24, 28, 31
Monthly Lows: 3/23, 2/28, 1/27, 12/3, 11/1, 10/2, 9/3, 8/5, 7/1, 6/3, 5/31, 4/1
Days: 1, 1, 1, 2, 3, 3, 3, 5, 23, 27, 27, 31
Weighted Times are repetitions which appears multiple times within the same list, observed and accentuated once divided into relevant sections of the histogram. They are important in the presently defined trading time period and are similar to a mathematical mode with respect to a series. Phased times are essentially periodical patterns in histograms, though they do not guarantee inflection points*.*
We see that SPY tends to have its lows between three major month clusters: 1-4, primarily March (which has actually occurred already this year), 6-9, averaged out to July, and 10-12, averaged out to November. Following the same methodology, we get the third and tenth days of the month as the likeliest days. However, evaluating the monthly lows for the past year, the end of the month has replaced the average of the tenth. Therefore, we have four primary dates for our histogram.
7/3/20, 7/27/20, and 11/3/20, 11/27/20 .
How do we narrow this group down with any accuracy? Let us average the days together to work with two dates - 7/15/20 and 11/15/20.
The 8.6-Year Armstrong-Princeton Global Economic Confidence model – states that 2.15 year intervals occur between corrections, relevant highs and lows. 2.15 years from the all-time peak discrete is April 14th of 2022. However, we can time-shift to other peaks and troughs to determine a date for this year. If we consider 1/28/2018 as a localized high and apply this model, we get 3/23/20 as a low - strikingly accurate. I have chosen the next localized high, 9/21/2018 to apply the model to. We achieve a date of 11/14/2020.
The average bear market is eighteen months long, giving us a date of August 19th, 2021 for the end of the bear market - roughly speaking.
Therefore, our timeline looks like:
As we move forward in time, our predictions may be less accurate. It is important to keep in mind that this analysis will likely change and become more accurate as we factor in Terry Laundry’s T-Theory, the Bradley Cycle, a more sophisticated analysis of Bull and Bear Market Cycles, the Fundamental Investor Cyclic Approach, and Seasons and Half-Seasons.
I have also assumed that the audience believes in these models, which is not necessary. Anyone with free time may construct histograms and view these time models, determining for themselves what is accurate and what is not. Take a look at 1/28/2008, that localized high, and 2.15 years (1/4th of the sinusoidal wave of the model) later.
The question now is, what prices will SPY reach on 11/14? Where will we be at 7/28? What will happen on 4/14/22?
submitted by aibnsamin1 to wallstreetbets [link] [comments]

Trading Accountability Buddy :)

Hello Fellow Redditor Traders,
I realized that trading a particular system is not about the system itself but on the approach of the user, an infinite amount of strategies exist out there and if a user is littered with a negative, inpatient, impulsive, loss averse, etc mindset than not even the "top" performing strategies would be of use. Thus, to me it seems that I get into this negative mindset from time to time, going into frequent draw-downs and consistent losses (low success rate) but fortunately with adequate risk management (to an extent) which kept my capital alive for this past year of actively trading the Forex market (-15% thus far). I am detail oriented and have a very detailed journal of every trade I take/ took (>500 trades mainly Forex) with statistical calculations on the different strategies that I have formulated, implemented, and back-tested manually (and have mostly failed due to user error in live markets). I can help with providing reflection on the trade setups technically and fundamentally, formulating a trading plan from scratch, formulating strategies, establishing adequate risk management and provide self-reflection as I fully know how it could be when stuck in a negative cycle.
I need someone to reciprocate accountability with (Currently at GMT +4 but wont mind the time difference in effort to make this work), I have a trend continuation based strategy that can work if I have the right mindset towards it, thus I would like to find someone to hold me accountable for the trades I enter during the week (end of week review) and also share ideas with back and forth on the different setups that are provided during the week.
Anyone serious about trading is welcome!
Regards, Z
submitted by ZzRedditor to PriceActionTrading [link] [comments]

H1 Backtest of ParallaxFX's BBStoch system

Disclaimer: None of this is financial advice. I have no idea what I'm doing. Please do your own research or you will certainly lose money. I'm not a statistician, data scientist, well-seasoned trader, or anything else that would qualify me to make statements such as the below with any weight behind them. Take them for the incoherent ramblings that they are.
TL;DR at the bottom for those not interested in the details.
This is a bit of a novel, sorry about that. It was mostly for getting my own thoughts organized, but if even one person reads the whole thing I will feel incredibly accomplished.

Background

For those of you not familiar, please see the various threads on this trading system here. I can't take credit for this system, all glory goes to ParallaxFX!
I wanted to see how effective this system was at H1 for a couple of reasons: 1) My current broker is TD Ameritrade - their Forex minimum is a mini lot, and I don't feel comfortable enough yet with the risk to trade mini lots on the higher timeframes(i.e. wider pip swings) that ParallaxFX's system uses, so I wanted to see if I could scale it down. 2) I'm fairly impatient, so I don't like to wait days and days with my capital tied up just to see if a trade is going to win or lose.
This does mean it requires more active attention since you are checking for setups once an hour instead of once a day or every 4-6 hours, but the upside is that you trade more often this way so you end up winning or losing faster and moving onto the next trade. Spread does eat more of the trade this way, but I'll cover this in my data below - it ends up not being a problem.
I looked at data from 6/11 to 7/3 on all pairs with a reasonable spread(pairs listed at bottom above the TL;DR). So this represents about 3-4 weeks' worth of trading. I used mark(mid) price charts. Spreadsheet link is below for anyone that's interested.

System Details

I'm pretty much using ParallaxFX's system textbook, but since there are a few options in his writeups, I'll include all the discretionary points here:

And now for the fun. Results!

As you can see, a higher target ended up with higher profit despite a much lower winrate. This is partially just how things work out with profit targets in general, but there's an additional point to consider in our case: the spread. Since we are trading on a lower timeframe, there is less overall price movement and thus the spread takes up a much larger percentage of the trade than it would if you were trading H4, Daily or Weekly charts. You can see exactly how much it accounts for each trade in my spreadsheet if you're interested. TDA does not have the best spreads, so you could probably improve these results with another broker.
EDIT: I grabbed typical spreads from other brokers, and turns out while TDA is pretty competitive on majors, their minors/crosses are awful! IG beats them by 20-40% and Oanda beats them 30-60%! Using IG spreads for calculations increased profits considerably (another 5% on top) and Oanda spreads increased profits massively (another 15%!). Definitely going to be considering another broker than TDA for this strategy. Plus that'll allow me to trade micro-lots, so I can be more granular(and thus accurate) with my position sizing and compounding.

A Note on Spread

As you can see in the data, there were scenarios where the spread was 80% of the overall size of the trade(the size of the confirmation candle that you draw your fibonacci retracements over), which would obviously cut heavily into your profits.
Removing any trades where the spread is more than 50% of the trade width improved profits slightly without removing many trades, but this is almost certainly just coincidence on a small sample size. Going below 40% and even down to 30% starts to cut out a lot of trades for the less-common pairs, but doesn't actually change overall profits at all(~1% either way).
However, digging all the way down to 25% starts to really make some movement. Profit at the -161.8% TP level jumps up to 37.94% if you filter out anything with a spread that is more than 25% of the trade width! And this even keeps the sample size fairly large at 187 total trades.
You can get your profits all the way up to 48.43% at the -161.8% TP level if you filter all the way down to only trades where spread is less than 15% of the trade width, however your sample size gets much smaller at that point(108 trades) so I'm not sure I would trust that as being accurate in the long term.
Overall based on this data, I'm going to only take trades where the spread is less than 25% of the trade width. This may bias my trades more towards the majors, which would mean a lot more correlated trades as well(more on correlation below), but I think it is a reasonable precaution regardless.

Time of Day

Time of day had an interesting effect on trades. In a totally predictable fashion, a vast majority of setups occurred during the London and New York sessions: 5am-12pm Eastern. However, there was one outlier where there were many setups on the 11PM bar - and the winrate was about the same as the big hours in the London session. No idea why this hour in particular - anyone have any insight? That's smack in the middle of the Tokyo/Sydney overlap, not at the open or close of either.
On many of the hour slices I have a feeling I'm just dealing with small number statistics here since I didn't have a lot of data when breaking it down by individual hours. But here it is anyway - for all TP levels, these three things showed up(all in Eastern time):
I don't have any reason to think these timeframes would maintain this behavior over the long term. They're almost certainly meaningless. EDIT: When you de-dup highly correlated trades, the number of trades in these timeframes really drops, so from this data there is no reason to think these timeframes would be any different than any others in terms of winrate.
That being said, these time frames work out for me pretty well because I typically sleep 12am-7am Eastern time. So I automatically avoid the 5am-6am timeframe, and I'm awake for the majority of this system's setups.

Moving stops up to breakeven

This section goes against everything I know and have ever heard about trade management. Please someone find something wrong with my data. I'd love for someone to check my formulas, but I realize that's a pretty insane time commitment to ask of a bunch of strangers.
Anyways. What I found was that for these trades moving stops up...basically at all...actually reduced the overall profitability.
One of the data points I collected while charting was where the price retraced back to after hitting a certain milestone. i.e. once the price hit the -61.8% profit level, how far back did it retrace before hitting the -100% profit level(if at all)? And same goes for the -100% profit level - how far back did it retrace before hitting the -161.8% profit level(if at all)?
Well, some complex excel formulas later and here's what the results appear to be. Emphasis on appears because I honestly don't believe it. I must have done something wrong here, but I've gone over it a hundred times and I can't find anything out of place.
Now, you might think exactly what I did when looking at these numbers: oof, the spread killed us there right? Because even when you move your SL to 0%, you still end up paying the spread, so it's not truly "breakeven". And because we are trading on a lower timeframe, the spread can be pretty hefty right?
Well even when I manually modified the data so that the spread wasn't subtracted(i.e. "Breakeven" was truly +/- 0), things don't look a whole lot better, and still way worse than the passive trade management method of leaving your stops in place and letting it run. And that isn't even a realistic scenario because to adjust out the spread you'd have to move your stoploss inside the candle edge by at least the spread amount, meaning it would almost certainly be triggered more often than in the data I collected(which was purely based on the fib levels and mark price). Regardless, here are the numbers for that scenario:
From a literal standpoint, what I see behind this behavior is that 44 of the 69 breakeven trades(65%!) ended up being profitable to -100% after retracing deeply(but not to the original SL level), which greatly helped offset the purely losing trades better than the partial profit taken at -61.8%. And 36 went all the way back to -161.8% after a deep retracement without hitting the original SL. Anyone have any insight into this? Is this a problem with just not enough data? It seems like enough trades that a pattern should emerge, but again I'm no expert.
I also briefly looked at moving stops to other lower levels (78.6%, 61.8%, 50%, 38.2%, 23.6%), but that didn't improve things any. No hard data to share as I only took a quick look - and I still might have done something wrong overall.
The data is there to infer other strategies if anyone would like to dig in deep(more explanation on the spreadsheet below). I didn't do other combinations because the formulas got pretty complicated and I had already answered all the questions I was looking to answer.

2-Candle vs Confirmation Candle Stops

Another interesting point is that the original system has the SL level(for stop entries) just at the outer edge of the 2-candle pattern that makes up the system. Out of pure laziness, I set up my stops just based on the confirmation candle. And as it turns out, that is much a much better way to go about it.
Of the 60 purely losing trades, only 9 of them(15%) would go on to be winners with stops on the 2-candle formation. Certainly not enough to justify the extra loss and/or reduced profits you are exposing yourself to in every single other trade by setting a wider SL.
Oddly, in every single scenario where the wider stop did save the trade, it ended up going all the way to the -161.8% profit level. Still, not nearly worth it.

Correlated Trades

As I've said many times now, I'm really not qualified to be doing an analysis like this. This section in particular.
Looking at shared currency among the pairs traded, 74 of the trades are correlated. Quite a large group, but it makes sense considering the sort of moves we're looking for with this system.
This means you are opening yourself up to more risk if you were to trade on every signal since you are technically trading with the same underlying sentiment on each different pair. For example, GBP/USD and AUD/USD moving together almost certainly means it's due to USD moving both pairs, rather than GBP and AUD both moving the same size and direction coincidentally at the same time. So if you were to trade both signals, you would very likely win or lose both trades - meaning you are actually risking double what you'd normally risk(unless you halve both positions which can be a good option, and is discussed in ParallaxFX's posts and in various other places that go over pair correlation. I won't go into detail about those strategies here).
Interestingly though, 17 of those apparently correlated trades ended up with different wins/losses.
Also, looking only at trades that were correlated, winrate is 83%/70%/55% (for the three TP levels).
Does this give some indication that the same signal on multiple pairs means the signal is stronger? That there's some strong underlying sentiment driving it? Or is it just a matter of too small a sample size? The winrate isn't really much higher than the overall winrates, so that makes me doubt it is statistically significant.
One more funny tidbit: EUCAD netted the lowest overall winrate: 30% to even the -61.8% TP level on 10 trades. Seems like that is just a coincidence and not enough data, but dang that's a sucky losing streak.
EDIT: WOW I spent some time removing correlated trades manually and it changed the results quite a bit. Some thoughts on this below the results. These numbers also include the other "What I will trade" filters. I added a new worksheet to my data to show what I ended up picking.
To do this, I removed correlated trades - typically by choosing those whose spread had a lower % of the trade width since that's objective and something I can see ahead of time. Obviously I'd like to only keep the winning trades, but I won't know that during the trade. This did reduce the overall sample size down to a level that I wouldn't otherwise consider to be big enough, but since the results are generally consistent with the overall dataset, I'm not going to worry about it too much.
I may also use more discretionary methods(support/resistance, quality of indecision/confirmation candles, news/sentiment for the pairs involved, etc) to filter out correlated trades in the future. But as I've said before I'm going for a pretty mechanical system.
This brought the 3 TP levels and even the breakeven strategies much closer together in overall profit. It muted the profit from the high R:R strategies and boosted the profit from the low R:R strategies. This tells me pair correlation was skewing my data quite a bit, so I'm glad I dug in a little deeper. Fortunately my original conclusion to use the -161.8 TP level with static stops is still the winner by a good bit, so it doesn't end up changing my actions.
There were a few times where MANY (6-8) correlated pairs all came up at the same time, so it'd be a crapshoot to an extent. And the data showed this - often then won/lost together, but sometimes they did not. As an arbitrary rule, the more correlations, the more trades I did end up taking(and thus risking). For example if there were 3-5 correlations, I might take the 2 "best" trades given my criteria above. 5+ setups and I might take the best 3 trades, even if the pairs are somewhat correlated.
I have no true data to back this up, but to illustrate using one example: if AUD/JPY, AUD/USD, CAD/JPY, USD/CAD all set up at the same time (as they did, along with a few other pairs on 6/19/20 9:00 AM), can you really say that those are all the same underlying movement? There are correlations between the different correlations, and trying to filter for that seems rough. Although maybe this is a known thing, I'm still pretty green to Forex - someone please enlighten me if so! I might have to look into this more statistically, but it would be pretty complex to analyze quantitatively, so for now I'm going with my gut and just taking a few of the "best" trades out of the handful.
Overall, I'm really glad I went further on this. The boosting of the B/E strategies makes me trust my calculations on those more since they aren't so far from the passive management like they were with the raw data, and that really had me wondering what I did wrong.

What I will trade

Putting all this together, I am going to attempt to trade the following(demo for a bit to make sure I have the hang of it, then for keeps):
Looking at the data for these rules, test results are:
I'll be sure to let everyone know how it goes!

Other Technical Details

Raw Data

Here's the spreadsheet for anyone that'd like it. (EDIT: Updated some of the setups from the last few days that have fully played out now. I also noticed a few typos, but nothing major that would change the overall outcomes. Regardless, I am currently reviewing every trade to ensure they are accurate.UPDATE: Finally all done. Very few corrections, no change to results.)
I have some explanatory notes below to help everyone else understand the spiraled labyrinth of a mind that put the spreadsheet together.

Insanely detailed spreadsheet notes

For you real nerds out there. Here's an explanation of what each column means:

Pairs

  1. AUD/CAD
  2. AUD/CHF
  3. AUD/JPY
  4. AUD/NZD
  5. AUD/USD
  6. CAD/CHF
  7. CAD/JPY
  8. CHF/JPY
  9. EUAUD
  10. EUCAD
  11. EUCHF
  12. EUGBP
  13. EUJPY
  14. EUNZD
  15. EUUSD
  16. GBP/AUD
  17. GBP/CAD
  18. GBP/CHF
  19. GBP/JPY
  20. GBP/NZD
  21. GBP/USD
  22. NZD/CAD
  23. NZD/CHF
  24. NZD/JPY
  25. NZD/USD
  26. USD/CAD
  27. USD/CHF
  28. USD/JPY

TL;DR

Based on the reasonable rules I discovered in this backtest:

Demo Trading Results

Since this post, I started demo trading this system assuming a 5k capital base and risking ~1% per trade. I've added the details to my spreadsheet for anyone interested. The results are pretty similar to the backtest when you consider real-life conditions/timing are a bit different. I missed some trades due to life(work, out of the house, etc), so that brought my total # of trades and thus overall profit down, but the winrate is nearly identical. I also closed a few trades early due to various reasons(not liking the price action, seeing support/resistance emerge, etc).
A quick note is that TD's paper trade system fills at the mid price for both stop and limit orders, so I had to subtract the spread from the raw trade values to get the true profit/loss amount for each trade.
I'm heading out of town next week, then after that it'll be time to take this sucker live!

Live Trading Results

I started live-trading this system on 8/10, and almost immediately had a string of losses much longer than either my backtest or demo period. Murphy's law huh? Anyways, that has me spooked so I'm doing a longer backtest before I start risking more real money. It's going to take me a little while due to the volume of trades, but I'll likely make a new post once I feel comfortable with that and start live trading again.
submitted by ForexBorex to Forex [link] [comments]

Naked Forex Noob

TL;DR Just got into Naked Forex trading but I am stuck on backtesting. Can't correctly identify critical zones (supp and res zones) and I haven't found the criteria for my trading system (wammies and moolahs) on the charts that I have back tested. Any advice?

Hi there, I started learning about forex awhile back from a friend and he began to show me the basics while also directing me to babypips for the free course they put you through. Although I got into all of this awhile back, I have been stuck in the stages of finding my own strategy and backtesting it.
At first, I was very much into using the basic indicators (RSI, MACD, SMA/EMA) but then I came across a recommendation in this sub to read 'Naked Forex' and I was hooked. Not in a sense that now I knew exactly what my strategy was and how to implement it, but hooked in the idea of being able to read a chart and make trades based on price action and reversals.
Of course while reading the book, understanding the concepts, and looking at all the examples of the different trading strategies i'm getting hyped in my mind to get to the backtesting stage to see if I can put this knowledge to somewhat of a test. Now here I am, staring at tradingview's daily and 4h charts from 2006 onward.
Here's where I get stuck.
I understand identifying critical support and resistance zones and it all made sense to me in the book, but as I am backtesting I find that the zones are either always changing or I can't figure out which ones are critical. On top of that, my trading system looks something like this (advice is welcome on how this could be improved or if you see any glaring "wtfs" in it)
I trade wammies & moolahs (market touches supp. or res. zone twice, second touch is lowehigher with a bearish/bullish candlestick printed on the 2nd touch) and use either a kangaroo tail or big shadow for confirmation to initiate the trade.
The buy/sell stop is set 8 pips above/below the bearish/bullish candlestick and the stop loss is placed below/above the first touch.
The profit target is the following zone.
There's a bit more criteria for the trade but that's the blueprint of it. I apologize if it either doesn't make sense or confuses you but even after sifting through months/years of backtesting data my eyes never caught any of this action happening in the zones I've identified.
Any help would be appreciated as I am a sponge and will soak in as much criticism and advice as I can.
submitted by VileKyleTM to Forex [link] [comments]

How To Make Money Trading Reddit

How To Make Money Trading Reddit

MAKE MONEY WITH TRADING (Forex, Stocks, Binary Options)

https://preview.redd.it/onvu1owbn2v51.jpg?width=640&format=pjpg&auto=webp&s=63508b4c3653556bc53e4ef2df86a29df5e5dd0b
Trading consists of buying and selling assets, such as stocks, futures, currencies or derivatives, in a financial market. To trade, so that we obtain benefits, we will have to speculate with the movements in the price of the assets. This is the first step to making money from trading.
The word trading is usually associated with short-term investments, that is, short operations that seek benefits limited to a small time frame.
In other words, trading and investing are the same, only the time frame changes.
So if you hear terms like "stock trading" or "stock trading" it is the same thing, only they usually refer to different time frames.
The person who invests or trades is called a trader. A trader then is someone who invests in the financial markets.
Generally, the term trader is usually added to the asset that operates. For example, stock trader, futures trader, forex trader, in short, the asset that operates.
As you can see I am adding several concepts so that we all start from the same base.
So, trading is basically buying and selling assets, trying to buy at the lowest possible price and sell as high as possible. As simple as that.
I want you to understand something, the bases are 70% of your trading. It is amazing to see how advanced traders forget the basics before trading.
By advanced trader I mean someone who already knows how to trade but that doesn't necessarily make him a winning trader. In most cases they apply complicated strategies and forget something as simple as the bases.
How much can a trader earn? You put the roof on it, there is no limit. I recommend you measure your progress in percentages and not in nominals. It is best to verify your progress.
Is it necessary to be in a Trading Academy? Like everything, there are some who like to be social and others who prefer to work in a self-taught way. In trading, it is the same. If you need the constant support of people to not be demotivated, then a Trading Academy is a good option. Now, if you are an already motivated person who only needs to clear up doubts, then the best thing is a mentor, consulting professional, or a trading teacher who clears your doubts.
The foundations for making money trading have to be solid if we want to make profits consistently. So today I want to emphasize that, the foundations of being a successful trader. Let us begin!

How to Make Money Trading Reddit - Key Steps

https://preview.redd.it/la3o4919o2v51.jpg?width=640&format=pjpg&auto=webp&s=02e5635985796aa609c9ed4848285b4ce69f1196
1) Buy Supports (and resistances)
Buying in supports is buying in a key area where the price exerts a certain friction preventing the price from continuing to advance, for whatever reason.
A support is nothing more than an area where the asset finds the confidence of investors, it is the level where they estimate that it is a good purchase price for them, and that is why they buy the asset in question, in such a way that the asset finds help in that level.
Most trading systems, at least the ones I know of which are a few, are based on this principle but what happens, they camouflage it with flourishes.
Instead of saying, to the purchase in supports, they add colored mirrors so that it does not look so simple.
I'm not saying that details are not good, but exaggeration of details can lead to confusion and later paralysis.
Systems must necessarily be simple.
Buying in stands not only improves your overall entry, but it drastically lowers your risks. The further we move away from a support, the more the risk increases.
Many times we end up buying halfway because the price "escaped" us and we think that we will not have another equal opportunity. The reality is that the market always provides opportunities for those who know how to wait.
There is a saying that the beginning trader has fun in the market, the professional trader gets bored.
This does not mean that the professional trader does things reluctantly, or that he does not like to invest. It means that the professional trader waits crouched, calm, for that opportunity that he is looking for appears, that entry into support that reduces his risk. While the novice trader enters and exits the market euphoric.
A professional trader can be in front of the screen all day and not make a single trade. The novice trader, on the other hand, if he spends more than 5 minutes without trading, he already feels bad, anxious and thinks that he is losing opportunities.
Without further ado, enter supports.
2) Execute stop loss
Holding losses is the biggest mistake of traders. Who in the beginning has not moved the stop loss because the operation moved against him?
It's a very common mistake. We enter the market, we put the stop, the operation turns against us and instead of executing the stop, we RUN IT!
We are camicaces.
The typical phrase "I'm waiting to recover" has burned entire wallets.
The market fell 40% and instead of leaving, they began to pray.
The great advantage of small portfolios, that is, investors with little capital, is flexibility and speed of reaction.
By running the stop loss you are losing the only advantage you have with respect to professionals and large investors. Because they sure have more capital and have wider margins.
Please don't take losses, don't run the stop loss.
If you miss the stop, distance yourself from the market and analyze why that happened to you for the next better place your stop.
3) Sell in resistonce
I want you to remember something. Until you sell, the profits are not yours.
Until you sell, you have no money.
Until you sell, you cannot say that the operation was successful.
Many traders are very good at finding entries. They perfectly see the supports and manage to enter at the best prices. But what happens to them, they don't sell.
It hits a key resistance, where price clearly can't break through and what they do, they hold out in case it breaks.
The worst, the price does not break or make an upthrust (which would be a kind of professional feint), it returns to support, it bounces, it goes back to resistance and what we do ... we wait again to see if it breaks, because now it is the correct.
And there is a worse case. It reaches resistance and we want to apply the phrase "let the profits run", so what do we do, we adjust the stop loss near the resistance in case the price breaks and continues.
The price tests the resistance, falls, touches our stop and we run it in case the price returns to the path. Instead of applying the phrase “let the profits run” we apply the phrase “let the losses run”.
An old master used to say, when the price reaches resistance, I collect my winnings and go on vacation.
It seems silly but it is a way of telling our brain, if you do things well you have a prize.
Sell ​​in resistance, the market always gives new opportunities.
4) The Trend is your friend
No better elaborated phrase. The trend is your friend. And as we all know, almost no one pays attention to their friends. We ask them for advice and if they don't say what we want to hear, we won't.
If the price goes up, where do you have to invest?
"It is not that the price was stretched too much and surely now a correction is coming, so I invest against it."
You are seeing that the trend is upward in an annual, monthly, weekly, daily, hourly and minute time frame, but just in case you invest against it.
Please, the trend is your friend, if it tells you that the price is going up, it is because it is going up.
I invested in favor of the trend. You do not want to beat the market because I assure you that it breaks your arm in a blink of an eye.
5) Statistical advantage
In the financial markets there are no certainties, only probabilities and whoever tells you otherwise is surely not winning in silver.
What we are looking for are windows of statistical opportunities. In other words, we try to turn the odds in our favor.
That is why it is always important to ask yourself the question, what is more likely, that the price will go up or down?
This is because many times we operate and do not realize that the odds are against us.
We can never be 100% certain, but just putting the odds in our favor by making concrete decisions based on logic and not on emotions can earn us a lot of money.
6) Consistency
You often see many traders showing one or two of their most successful trades and the occasional loss. This is good for teaching purposes, and it is useful for transmitting teachings.
But if you want to become a professional trader you need consistency. And consistency does not speak of an isolated operation, it speaks of sustained profits over time.
And when I say time I speak of years. Not a month, not a week, not a semester. 3 years, 5 years, 10 years, 20 years.
To give you an idea, ultra-professional traders fight to see who is more consistent.
In other words, the first question they ask themselves is how many years have you been winning?
A trader who every year earns a tight, modest percentage, reasonable to say the least, but consistently, is a much better professional than one who doubles the capital one year and the other is -90.
Consistency is highly treasured as it allows for simulations, strategizing, and even projections.
7) Trading plan
The number of traders who invest without having a trading plan is impressive. Something so important, so simple to make, so useful and very few use it.
A trading plan allows you to analyze your operations, see what you are doing, and then improve.
When we don't have a trading plan, what we did last week goes completely unnoticed because we can't internalize the teaching.
And when I speak of teachings, they can be gains or losses.
A loss allows us to adjust the plan but a success also.
In fact, when we have several successful operations, there is nothing better than taking their teachings and replicating them.
The trading plan is the only tool that allows us to do this, learn, improve and be the most objective possible, leaving aside emotions.

Forex trading Reddit

https://preview.redd.it/ljyjklqgo2v51.jpg?width=640&format=pjpg&auto=webp&s=c50d6af6b81521fbbfe25938c98971e1592de261
When it comes to the currency market, one of the most popular trading markets is Forex. It represents the world's largest decentralized currency market. So we will answer how to make money from forex trading.
With only having a computer, tablet or mobile phone, and an excellent internet connection service, you will be able to operate from anywhere in the world in the Forex market. It has the great strength of being flexible and adaptable to all types of investors.
Select a prominent broker or intermediary agent, one that is recognized and very professional. Conduct negotiation trials with him, so that you get to know each other and do not put your capital at risk.
Develop together the work style that most identifies you and decide to earn money by trading, enriching yourself with all the possible knowledge and strategies.
Acquire strengths in detecting the ideal moment to carry out operations. You will achieve this by studying and understanding the graphs and trends of transactions, detecting that unique pattern that tells you when is the right time to proceed.
Do not hesitate, it is possible to earn a lot of money with trading! But, make sure, above all things, train yourself with a duly accredited professional, in guarantee of acquiring quality theoretical knowledge, imperative to understand the movement of the market.

How to Make Money Trading Reddit - Final Words

Trading is an “investment vehicle” that can serve your objectives of having financial peace of mind as long as it is part of a broad economic and financial planning in the short, medium and long term. If not, trading can become a fast track to lose your money, if you lack the necessary knowledge, experience and training. Follow the following formula to Make Money in Trading Consistently:

Profitability = (Knowledge + experience) x emotional and mental management

submitted by kayakero to makemoneyforexreddit [link] [comments]

5%ers Prop Shop Forex : $24,000 Funded Account Qualification Stage.

5%ers Prop Shop Forex : $24,000 Funded Account Qualification Stage.

Entry Level Testing

Follow results here.


Starting Fee - $270
Starting Funding - $6,000
Live Account - Yes
Required Profit to Pass - $375
Duration - Minimum of 20 days. Maximum time of 6 months to hit profit target.

Risk Restrictions


Maximum Net Loss - $250
Maximum Risk in Stop Loss - 1.5%
Maximum Size of Position - 0.30 lots
Hold Overnight - Yes
Hold Over Weekend - Yes
News Trading Restrictions - News trading is not strictly prohibited.


Notes

5%ers give you a live account from sign up. You can trade and begin to build up real earnings on day one. To qualify to be paid you need to pass the evaluation phase by hitting 6% ($375) profit. It takes at least 20 days to pass (Even if you hit target early) and you have up to 6 months to do it (So it can be passed with an average of 1% a month).
5%ers have a liberal approach to trader flexibility. The only hard and fast rule that needs to be followed is the maximum net loss. This is 4% of the starting balance (Making this far easier than high water mark systems). Traders can use some discretion on their money management to achieve this, but more aggressive trading will mean your profit targets to progress will increase.
Using conservative risk (Complying with the risk restrictions listed above) can lead to lower profit targets to progress (And account size doubles each time you hit a profit target, so this is a good thing).

5%ers main form of communication with their traders is via email. You're expected to give an active email address that you will check regularly and to respond to any messages in a timely manner.

Thoughts on Passing 5%ers Forex Funding Evaluation Stage


For experienced traders passing the evaluation stage should be easy enough and something that can be done within 3 months (Or quicker, depending on strategy and market conditions). The fact the 4% drawdown limit is off the starting balance and not a trailing high water mark give a lot of leeway for a good trader if they can get a bit ahead.

For somewhat experienced traders passing the evaluation stage is achievable if you can apply solid risk management and a strategy that has a winning edge. Having 6 months in which to complete it and the only stipulation if you can not lose $250 off the starting $6,000 mean as long as you keep lot sizing small you can stay alive long enough to hit the target.

For new traders since trading in general is hard, you're going to find stipulated risk conditions very hard. There is a fair chance for newer traders to pass this (Given it's a lot target over 6 months) but there is a higher likelihood of not passing, meaning you lose your $270 evaluation fee. I do not know the stats, but I'd assume a lot of new traders do not pass. It's probably worth getting experience first.


On boarding Process


Getting started with 5%ers Forex funding was and smooth on boarding. I made my payment via PayPal of $270. I was sent a welcome email and details to log into a back office. My account was processing for a while, and then after 30 minutes to an hour I was sent MT4 login details to a funded account of $6,000 with a $250 loss limit. I could trade within 2 hours of signing up.

Reward on Pass


Get paid 50% of the profits made. Account is increased 400% to $24,000. Each 10% made the account will be doubled again up to a maximum of $1.25 million.

Content from Welcome Email


https://preview.redd.it/41m5zg1q7tu51.png?width=572&format=png&auto=webp&s=8cdb9709335e5f722590246d63effafc56961ce6
https://preview.redd.it/slh5rcfr7tu51.png?width=621&format=png&auto=webp&s=e1c94838cdfb7156156b8c6a83375014ed383cf3

My Results


Follow results here.

See risk management plan here for 5%ers funded Forex trading.
submitted by db_aum to ForexFunding [link] [comments]

No, the British did not steal $45 trillion from India

This is an updated copy of the version on BadHistory. I plan to update it in accordance with the feedback I got.
I'd like to thank two people who will remain anonymous for helping me greatly with this post (you know who you are)
Three years ago a festschrift for Binay Bhushan Chaudhuri was published by Shubhra Chakrabarti, a history teacher at the University of Delhi and Utsa Patnaik, a Marxist economist who taught at JNU until 2010.
One of the essays in the festschirt by Utsa Patnaik was an attempt to quantify the "drain" undergone by India during British Rule. Her conclusion? Britain robbed India of $45 trillion (or £9.2 trillion) during their 200 or so years of rule. This figure was immensely popular, and got republished in several major news outlets (here, here, here, here (they get the number wrong) and more recently here), got a mention from the Minister of External Affairs & returns 29,100 results on Google. There's also plenty of references to it here on Reddit.
Patnaik is not the first to calculate such a figure. Angus Maddison thought it was £100 million, Simon Digby said £1 billion, Javier Estaban said £40 million see Roy (2019). The huge range of figures should set off some alarm bells.
So how did Patnaik calculate this (shockingly large) figure? Well, even though I don't have access to the festschrift, she conveniently has written an article detailing her methodology here. Let's have a look.
How exactly did the British manage to diddle us and drain our wealth’ ? was the question that Basudev Chatterjee (later editor of a volume in the Towards Freedom project) had posed to me 50 years ago when we were fellow-students abroad.
This is begging the question.
After decades of research I find that using India’s commodity export surplus as the measure and applying an interest rate of 5%, the total drain from 1765 to 1938, compounded up to 2016, comes to £9.2 trillion; since $4.86 exchanged for £1 those days, this sum equals about $45 trillion.
This is completely meaningless. To understand why it's meaningless consider India's annual coconut exports. These are almost certainly a surplus but the surplus in trade is countered by the other country buying the product (indeed, by definition, trade surpluses contribute to the GDP of a nation which hardly plays into intuitive conceptualisations of drain).
Furthermore, Dewey (2019) critiques the 5% interest rate.
She [Patnaik] consistently adopts statistical assumptions (such as compound interest at a rate of 5% per annum over centuries) that exaggerate the magnitude of the drain
Moving on:
The exact mechanism of drain, or transfers from India to Britain was quite simple.
Convenient.
Drain theory possessed the political merit of being easily grasped by a nation of peasants. [...] No other idea could arouse people than the thought that they were being taxed so that others in far off lands might live in comfort. [...] It was, therefore, inevitable that the drain theory became the main staple of nationalist political agitation during the Gandhian era.
- Chandra et al. (1989)
The key factor was Britain’s control over our taxation revenues combined with control over India’s financial gold and forex earnings from its booming commodity export surplus with the world. Simply put, Britain used locally raised rupee tax revenues to pay for its net import of goods, a highly abnormal use of budgetary funds not seen in any sovereign country.
The issue with figures like these is they all make certain methodological assumptions that are impossible to prove. From Roy in Frankema et al. (2019):
the "drain theory" of Indian poverty cannot be tested with evidence, for several reasons. First, it rests on the counterfactual that any money saved on account of factor payments abroad would translate into domestic investment, which can never be proved. Second, it rests on "the primitive notion that all payments to foreigners are "drain"", that is, on the assumption that these payments did not contribute to domestic national income to the equivalent extent (Kumar 1985, 384; see also Chaudhuri 1968). Again, this cannot be tested. [...] Fourth, while British officers serving India did receive salaries that were many times that of the average income in India, a paper using cross-country data shows that colonies with better paid officers were governed better (Jones 2013).
Indeed, drain theory rests on some very weak foundations. This, in of itself, should be enough to dismiss any of the other figures that get thrown out. Nonetheless, I felt it would be a useful exercise to continue exploring Patnaik's take on drain theory.
The East India Company from 1765 onwards allocated every year up to one-third of Indian budgetary revenues net of collection costs, to buy a large volume of goods for direct import into Britain, far in excess of that country’s own needs.
So what's going on here? Well Roy (2019) explains it better:
Colonial India ran an export surplus, which, together with foreign investment, was used to pay for services purchased from Britain. These payments included interest on public debt, salaries, and pensions paid to government offcers who had come from Britain, salaries of managers and engineers, guaranteed profts paid to railway companies, and repatriated business profts. How do we know that any of these payments involved paying too much? The answer is we do not.
So what was really happening is the government was paying its workers for services (as well as guaranteeing profits - to promote investment - something the GoI does today Dalal (2019), and promoting business in India), and those workers were remitting some of that money to Britain. This is hardly a drain (unless, of course, Indian diaspora around the world today are "draining" it). In some cases, the remittances would take the form of goods (as described) see Chaudhuri (1983):
It is obvious that these debit items were financed through the export surplus on merchandise account, and later, when railway construction started on a large scale in India, through capital import. Until 1833 the East India Company followed a cumbersome method in remitting the annual home charges. This was to purchase export commodities in India out of revenue, which were then shipped to London and the proceeds from their sale handed over to the home treasury.
While Roy's earlier point argues better paid officers governed better, it is honestly impossible to say what part of the repatriated export surplus was a drain, and what was not. However calling all of it a drain is definitely misguided.
It's worth noting that Patnaik seems to make no attempt to quantify the benefits of the Raj either, Dewey (2019)'s 2nd criticism:
she [Patnaik] consistently ignores research that would tend to cut the economic impact of the drain down to size, such as the work on the sources of investment during the industrial revolution (which shows that industrialisation was financed by the ploughed-back profits of industrialists) or the costs of empire school (which stresses the high price of imperial defence)

Since tropical goods were highly prized in other cold temperate countries which could never produce them, in effect these free goods represented international purchasing power for Britain which kept a part for its own use and re-exported the balance to other countries in Europe and North America against import of food grains, iron and other goods in which it was deficient.
Re-exports necessarily adds value to goods when the goods are processed and when the goods are transported. The country with the largest navy at the time would presumably be in very good stead to do the latter.
The British historians Phyllis Deane and WA Cole presented an incorrect estimate of Britain’s 18th-19th century trade volume, by leaving out re-exports completely. I found that by 1800 Britain’s total trade was 62% higher than their estimate, on applying the correct definition of trade including re-exports, that is used by the United Nations and by all other international organisations.
While interesting, and certainly expected for such an old book, re-exporting necessarily adds value to goods.
When the Crown took over from the Company, from 1861 a clever system was developed under which all of India’s financial gold and forex earnings from its fast-rising commodity export surplus with the world, was intercepted and appropriated by Britain. As before up to a third of India’s rising budgetary revenues was not spent domestically but was set aside as ‘expenditure abroad’.
So, what does this mean? Britain appropriated all of India's earnings, and then spent a third of it aboard? Not exactly. She is describing home charges see Roy (2019) again:
Some of the expenditures on defense and administration were made in sterling and went out of the country. This payment by the government was known as the Home Charges. For example, interest payment on loans raised to finance construction of railways and irrigation works, pensions paid to retired officers, and purchase of stores, were payments in sterling. [...] almost all money that the government paid abroad corresponded to the purchase of a service from abroad. [...] The balance of payments system that emerged after 1800 was based on standard business principles. India bought something and paid for it. State revenues were used to pay for wages of people hired abroad, pay for interest on loans raised abroad, and repatriation of profits on foreign investments coming into India. These were legitimate market transactions.
Indeed, if paying for what you buy is drain, then several billions of us are drained every day.
The Secretary of State for India in Council, based in London, invited foreign importers to deposit with him the payment (in gold, sterling and their own currencies) for their net imports from India, and these gold and forex payments disappeared into the yawning maw of the SoS’s account in the Bank of England.
It should be noted that India having two heads was beneficial, and encouraged investment per Roy (2019):
The fact that the India Office in London managed a part of the monetary system made India creditworthy, stabilized its currency, and encouraged foreign savers to put money into railways and private enterprise in India. Current research on the history of public debt shows that stable and large colonies found it easier to borrow abroad than independent economies because the investors trusted the guarantee of the colonist powers.

Against India’s net foreign earnings he issued bills, termed Council bills (CBs), to an equivalent rupee value. The rate (between gold-linked sterling and silver rupee) at which the bills were issued, was carefully adjusted to the last farthing, so that foreigners would never find it more profitable to ship financial gold as payment directly to Indians, compared to using the CB route. Foreign importers then sent the CBs by post or by telegraph to the export houses in India, that via the exchange banks were paid out of the budgeted provision of sums under ‘expenditure abroad’, and the exporters in turn paid the producers (peasants and artisans) from whom they sourced the goods.
Sunderland (2013) argues CBs had two main roles (and neither were part of a grand plot to keep gold out of India):
Council bills had two roles. They firstly promoted trade by handing the IO some control of the rate of exchange and allowing the exchange banks to remit funds to India and to hedge currency transaction risks. They also enabled the Indian government to transfer cash to England for the payment of its UK commitments.

The United Nations (1962) historical data for 1900 to 1960, show that for three decades up to 1928 (and very likely earlier too) India posted the second highest merchandise export surplus in the world, with USA in the first position. Not only were Indians deprived of every bit of the enormous international purchasing power they had earned over 175 years, even its rupee equivalent was not issued to them since not even the colonial government was credited with any part of India’s net gold and forex earnings against which it could issue rupees. The sleight-of-hand employed, namely ‘paying’ producers out of their own taxes, made India’s export surplus unrequited and constituted a tax-financed drain to the metropolis, as had been correctly pointed out by those highly insightful classical writers, Dadabhai Naoroji and RCDutt.
It doesn't appear that others appreciate their insight Roy (2019):
K. N. Chaudhuri rightly calls such practice ‘confused’ economics ‘coloured by political feelings’.

Surplus budgets to effect such heavy tax-financed transfers had a severe employment–reducing and income-deflating effect: mass consumption was squeezed in order to release export goods. Per capita annual foodgrains absorption in British India declined from 210 kg. during the period 1904-09, to 157 kg. during 1937-41, and to only 137 kg by 1946.
Dewey (1978) points out reliability issues with Indian agriculutural statistics, however this calorie decline persists to this day. Some of it is attributed to less food being consumed at home Smith (2015), a lower infectious disease burden Duh & Spears (2016) and diversified diets Vankatesh et al. (2016).
If even a part of its enormous foreign earnings had been credited to it and not entirely siphoned off, India could have imported modern technology to build up an industrial structure as Japan was doing.
This is, unfortunately, impossible to prove. Had the British not arrived in India, there is no clear indication that India would've united (this is arguably more plausible than the given counterfactual1). Had the British not arrived in India, there is no clear indication India would not have been nuked in WW2, much like Japan. Had the British not arrived in India, there is no clear indication India would not have been invaded by lizard people, much like Japan. The list continues eternally.
Nevertheless, I will charitably examine the given counterfactual anyway. Did pre-colonial India have industrial potential? The answer is a resounding no.
From Gupta (1980):
This article starts from the premise that while economic categories - the extent of commodity production, wage labour, monetarisation of the economy, etc - should be the basis for any analysis of the production relations of pre-British India, it is the nature of class struggles arising out of particular class alignments that finally gives the decisive twist to social change. Arguing on this premise, and analysing the available evidence, this article concludes that there was little potential for industrial revolution before the British arrived in India because, whatever might have been the character of economic categories of that period, the class relations had not sufficiently matured to develop productive forces and the required class struggle for a 'revolution' to take place.
A view echoed in Raychaudhuri (1983):
Yet all of this did not amount to an economic situation comparable to that of western Europe on the eve of the industrial revolution. Her technology - in agriculture as well as manufacturers - had by and large been stagnant for centuries. [...] The weakness of the Indian economy in the mid-eighteenth century, as compared to pre-industrial Europe was not simply a matter of technology and commercial and industrial organization. No scientific or geographical revolution formed part of the eighteenth-century Indian's historical experience. [...] Spontaneous movement towards industrialisation is unlikely in such a situation.
So now we've established India did not have industrial potential, was India similar to Japan just before the Meiji era? The answer, yet again, unsurprisingly, is no. Japan's economic situation was not comparable to India's, which allowed for Japan to finance its revolution. From Yasuba (1986):
All in all, the Japanese standard of living may not have been much below the English standard of living before industrialization, and both of them may have been considerably higher than the Indian standard of living. We can no longer say that Japan started from a pathetically low economic level and achieved a rapid or even "miraculous" economic growth. Japan's per capita income was almost as high as in Western Europe before industrialization, and it was possible for Japan to produce surplus in the Meiji Period to finance private and public capital formation.
The circumstances that led to Meiji Japan were extremely unique. See Tomlinson (1985):
Most modern comparisons between India and Japan, written by either Indianists or Japanese specialists, stress instead that industrial growth in Meiji Japan was the product of unique features that were not reproducible elsewhere. [...] it is undoubtably true that Japan's progress to industrialization has been unique and unrepeatable
So there you have it. Unsubstantiated statistical assumptions, calling any number you can a drain & assuming a counterfactual for no good reason gets you this $45 trillion number. Hopefully that's enough to bury it in the ground.
1. Several authors have affirmed that Indian identity is a colonial artefact. For example see Rajan 1969:
Perhaps the single greatest and most enduring impact of British rule over India is that it created an Indian nation, in the modern political sense. After centuries of rule by different dynasties overparts of the Indian sub-continent, and after about 100 years of British rule, Indians ceased to be merely Bengalis, Maharashtrians,or Tamils, linguistically and culturally.
or see Bryant 2000:
But then, it would be anachronistic to condemn eighteenth-century Indians, who served the British, as collaborators, when the notion of 'democratic' nationalism or of an Indian 'nation' did not then exist. [...] Indians who fought for them, differed from the Europeans in having a primary attachment to a non-belligerent religion, family and local chief, which was stronger than any identity they might have with a more remote prince or 'nation'.

Bibliography

Chakrabarti, Shubra & Patnaik, Utsa (2018). Agrarian and other histories: Essays for Binay Bhushan Chaudhuri. Colombia University Press
Hickel, Jason (2018). How the British stole $45 trillion from India. The Guardian
Bhuyan, Aroonim & Sharma, Krishan (2019). The Great Loot: How the British stole $45 trillion from India. Indiapost
Monbiot, George (2020). English Landowners have stolen our rights. It is time to reclaim them. The Guardian
Tsjeng, Zing (2020). How Britain Stole $45 trillion from India with trains | Empires of Dirt. Vice
Chaudhury, Dipanjan (2019). British looted $45 trillion from India in today’s value: Jaishankar. The Economic Times
Roy, Tirthankar (2019). How British rule changed India's economy: The Paradox of the Raj. Palgrave Macmillan
Patnaik, Utsa (2018). How the British impoverished India. Hindustan Times
Tuovila, Alicia (2019). Expenditure method. Investopedia
Dewey, Clive (2019). Changing the guard: The dissolution of the nationalist–Marxist orthodoxy in the agrarian and agricultural history of India. The Indian Economic & Social History Review
Chandra, Bipan et al. (1989). India's Struggle for Independence, 1857-1947. Penguin Books
Frankema, Ewout & Booth, Anne (2019). Fiscal Capacity and the Colonial State in Asia and Africa, c. 1850-1960. Cambridge University Press
Dalal, Sucheta (2019). IL&FS Controversy: Centre is Paying Up on Sovereign Guarantees to ADB, KfW for Group's Loan. TheWire
Chaudhuri, K.N. (1983). X - Foreign Trade and Balance of Payments (1757–1947). Cambridge University Press
Sunderland, David (2013). Financing the Raj: The City of London and Colonial India, 1858-1940. Boydell Press
Dewey, Clive (1978). Patwari and Chaukidar: Subordinate officials and the reliability of India’s agricultural statistics. Athlone Press
Smith, Lisa (2015). The great Indian calorie debate: Explaining rising undernourishment during India’s rapid economic growth. Food Policy
Duh, Josephine & Spears, Dean (2016). Health and Hunger: Disease, Energy Needs, and the Indian Calorie Consumption Puzzle. The Economic Journal
Vankatesh, P. et al. (2016). Relationship between Food Production and Consumption Diversity in India – Empirical Evidences from Cross Section Analysis. Agricultural Economics Research Review
Gupta, Shaibal (1980). Potential of Industrial Revolution in Pre-British India. Economic and Political Weekly
Raychaudhuri, Tapan (1983). I - The mid-eighteenth-century background. Cambridge University Press
Yasuba, Yasukichi (1986). Standard of Living in Japan Before Industrialization: From what Level did Japan Begin? A Comment. The Journal of Economic History
Tomblinson, B.R. (1985). Writing History Sideways: Lessons for Indian Economic Historians from Meiji Japan. Cambridge University Press
Rajan, M.S. (1969). The Impact of British Rule in India. Journal of Contemporary History
Bryant, G.J. (2000). Indigenous Mercenaries in the Service of European Imperialists: The Case of the Sepoys in the Early British Indian Army, 1750-1800. War in History
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Where is Bitcoin Going and When?

Where is Bitcoin Going and When?

The Federal Reserve and the United States government are pumping extreme amounts of money into the economy, already totaling over $484 billion. They are doing so because it already had a goal to inflate the United States Dollar (USD) so that the market can continue to all-time highs. It has always had this goal. They do not care how much inflation goes up by now as we are going into a depression with the potential to totally crash the US economy forever. They believe the only way to save the market from going to zero or negative values is to inflate it so much that it cannot possibly crash that low. Even if the market does not dip that low, inflation serves the interest of powerful people.
The impending crash of the stock market has ramifications for Bitcoin, as, though there is no direct ongoing-correlation between the two, major movements in traditional markets will necessarily affect Bitcoin. According to the Blockchain Center’s Cryptocurrency Correlation Tool, Bitcoin is not correlated with the stock market. However, when major market movements occur, they send ripples throughout the financial ecosystem which necessary affect even ordinarily uncorrelated assets.
Therefore, Bitcoin will reach X price on X date after crashing to a price of X by X date.

Stock Market Crash

The Federal Reserve has caused some serious consternation with their release of ridiculous amounts of money in an attempt to buoy the economy. At face value, it does not seem to have any rationale or logic behind it other than keeping the economy afloat long enough for individuals to profit financially and politically. However, there is an underlying basis to what is going on which is important to understand in order to profit financially.
All markets are functionally price probing systems. They constantly undergo a price-discovery process. In a fiat system, money is an illusory and a fundamentally synthetic instrument with no intrinsic value – similar to Bitcoin. The primary difference between Bitcoin is the underlying technology which provides a slew of benefits that fiat does not. Fiat, however, has an advantage in being able to have the support of powerful nation-states which can use their might to insure the currency’s prosperity.
Traditional stock markets are composed of indices (pl. of index). Indices are non-trading market instruments which are essentially summaries of business values which comprise them. They are continuously recalculated throughout a trading day, and sometimes reflected through tradable instruments such as Exchange Traded Funds or Futures. Indices are weighted by market capitalizations of various businesses.
Price theory essentially states that when a market fails to take out a new low in a given range, it will have an objective to take out the high. When a market fails to take out a new high, it has an objective to make a new low. This is why price-time charts go up and down, as it does this on a second-by-second, minute-by-minute, day-by-day, and even century-by-century basis. Therefore, market indices will always return to some type of bull market as, once a true low is formed, the market will have a price objective to take out a new high outside of its’ given range – which is an all-time high. Instruments can only functionally fall to zero, whereas they can grow infinitely.
So, why inflate the economy so much?
Deflation is disastrous for central banks and markets as it raises the possibility of producing an overall price objective of zero or negative values. Therefore, under a fractional reserve system with a fiat currency managed by a central bank – the goal of the central bank is to depreciate the currency. The dollar is manipulated constantly with the intention of depreciating its’ value.
Central banks have a goal of continued inflated fiat values. They tend to ordinarily contain it at less than ten percent (10%) per annum in order for the psyche of the general populace to slowly adjust price increases. As such, the markets are divorced from any other logic. Economic policy is the maintenance of human egos, not catering to fundamental analysis. Gross Domestic Product (GDP) growth is well-known not to be a measure of actual growth or output. It is a measure of increase in dollars processed. Banks seek to produce raising numbers which make society feel like it is growing economically, making people optimistic. To do so, the currency is inflated, though inflation itself does not actually increase growth. When society is optimistic, it spends and engages in business – resulting in actual growth. It also encourages people to take on credit and debts, creating more fictional fiat.
Inflation is necessary for markets to continue to reach new heights, generating positive emotional responses from the populace, encouraging spending, encouraging debt intake, further inflating the currency, and increasing the sale of government bonds. The fiat system only survives by generating more imaginary money on a regular basis.
Bitcoin investors may profit from this by realizing that stock investors as a whole always stand to profit from the market so long as it is managed by a central bank and does not collapse entirely. If those elements are filled, it has an unending price objective to raise to new heights. It also allows us to realize that this response indicates that the higher-ups believe that the economy could crash in entirety, and it may be wise for investors to have multiple well-thought-out exit strategies.

Economic Analysis of Bitcoin

The reason why the Fed is so aggressively inflating the economy is due to fears that it will collapse forever or never rebound. As such, coupled with a global depression, a huge demand will appear for a reserve currency which is fundamentally different than the previous system. Bitcoin, though a currency or asset, is also a market. It also undergoes a constant price-probing process. Unlike traditional markets, Bitcoin has the exact opposite goal. Bitcoin seeks to appreciate in value and not depreciate. This has a quite different affect in that Bitcoin could potentially become worthless and have a price objective of zero.
Bitcoin was created in 2008 by a now famous mysterious figure known as Satoshi Nakamoto and its’ open source code was released in 2009. It was the first decentralized cryptocurrency to utilize a novel protocol known as the blockchain. Up to one megabyte of data may be sent with each transaction. It is decentralized, anonymous, transparent, easy to set-up, and provides myriad other benefits. Bitcoin is not backed up by anything other than its’ own technology.
Bitcoin is can never be expected to collapse as a framework, even were it to become worthless. The stock market has the potential to collapse in entirety, whereas, as long as the internet exists, Bitcoin will be a functional system with a self-authenticating framework. That capacity to persist regardless of the actual price of Bitcoin and the deflationary nature of Bitcoin means that it has something which fiat does not – inherent value.
Bitcoin is based on a distributed database known as the “blockchain.” Blockchains are essentially decentralized virtual ledger books, replete with pages known as “blocks.” Each page in a ledger is composed of paragraph entries, which are the actual transactions in the block.
Blockchains store information in the form of numerical transactions, which are just numbers. We can consider these numbers digital assets, such as Bitcoin. The data in a blockchain is immutable and recorded only by consensus-based algorithms. Bitcoin is cryptographic and all transactions are direct, without intermediary, peer-to-peer.
Bitcoin does not require trust in a central bank. It requires trust on the technology behind it, which is open-source and may be evaluated by anyone at any time. Furthermore, it is impossible to manipulate as doing so would require all of the nodes in the network to be hacked at once – unlike the stock market which is manipulated by the government and “Market Makers”. Bitcoin is also private in that, though the ledge is openly distributed, it is encrypted. Bitcoin’s blockchain has one of the greatest redundancy and information disaster recovery systems ever developed.
Bitcoin has a distributed governance model in that it is controlled by its’ users. There is no need to trust a payment processor or bank, or even to pay fees to such entities. There are also no third-party fees for transaction processing. As the ledge is immutable and transparent it is never possible to change it – the data on the blockchain is permanent. The system is not easily susceptible to attacks as it is widely distributed. Furthermore, as users of Bitcoin have their private keys assigned to their transactions, they are virtually impossible to fake. No lengthy verification, reconciliation, nor clearing process exists with Bitcoin.
Bitcoin is based on a proof-of-work algorithm. Every transaction on the network has an associated mathetical “puzzle”. Computers known as miners compete to solve the complex cryptographic hash algorithm that comprises that puzzle. The solution is proof that the miner engaged in sufficient work. The puzzle is known as a nonce, a number used only once. There is only one major nonce at a time and it issues 12.5 Bitcoin. Once it is solved, the fact that the nonce has been solved is made public.
A block is mined on average of once every ten minutes. However, the blockchain checks every 2,016,000 minutes (approximately four years) if 201,600 blocks were mined. If it was faster, it increases difficulty by half, thereby deflating Bitcoin. If it was slower, it decreases, thereby inflating Bitcoin. It will continue to do this until zero Bitcoin are issued, projected at the year 2140. On the twelfth of May, 2020, the blockchain will halve the amount of Bitcoin issued when each nonce is guessed. When Bitcoin was first created, fifty were issued per block as a reward to miners. 6.25 BTC will be issued from that point on once each nonce is solved.
Unlike fiat, Bitcoin is a deflationary currency. As BTC becomes scarcer, demand for it will increase, also raising the price. In this, BTC is similar to gold. It is predictable in its’ output, unlike the USD, as it is based on a programmed supply. We can predict BTC’s deflation and inflation almost exactly, if not exactly. Only 21 million BTC will ever be produced, unless the entire network concedes to change the protocol – which is highly unlikely.
Some of the drawbacks to BTC include congestion. At peak congestion, it may take an entire day to process a Bitcoin transaction as only three to five transactions may be processed per second. Receiving priority on a payment may cost up to the equivalent of twenty dollars ($20). Bitcoin mining consumes enough energy in one day to power a single-family home for an entire week.

Trading or Investing?

The fundamental divide in trading revolves around the question of market structure. Many feel that the market operates totally randomly and its’ behavior cannot be predicted. For the purposes of this article, we will assume that the market has a structure, but that that structure is not perfect. That market structure naturally generates chart patterns as the market records prices in time. In order to determine when the stock market will crash, causing a major decline in BTC price, we will analyze an instrument, an exchange traded fund, which represents an index, as opposed to a particular stock. The price patterns of the various stocks in an index are effectively smoothed out. In doing so, a more technical picture arises. Perhaps the most popular of these is the SPDR S&P Standard and Poor 500 Exchange Traded Fund ($SPY).
In trading, little to no concern is given about value of underlying asset. We are concerned primarily about liquidity and trading ranges, which are the amount of value fluctuating on a short-term basis, as measured by volatility-implied trading ranges. Fundamental analysis plays a role, however markets often do not react to real-world factors in a logical fashion. Therefore, fundamental analysis is more appropriate for long-term investing.
The fundamental derivatives of a chart are time (x-axis) and price (y-axis). The primary technical indicator is price, as everything else is lagging in the past. Price represents current asking price and incorrectly implementing positions based on price is one of the biggest trading errors.
Markets and currencies ordinarily have noise, their tendency to back-and-fill, which must be filtered out for true pattern recognition. That noise does have a utility, however, in allowing traders second chances to enter favorable positions at slightly less favorable entry points. When you have any market with enough liquidity for historical data to record a pattern, then a structure can be divined. The market probes prices as part of an ongoing price-discovery process. Market technicians must sometimes look outside of the technical realm and use visual inspection to ascertain the relevance of certain patterns, using a qualitative eye that recognizes the underlying quantitative nature
Markets and instruments rise slower than they correct, however they rise much more than they fall. In the same vein, instruments can only fall to having no worth, whereas they could theoretically grow infinitely and have continued to grow over time. Money in a fiat system is illusory. It is a fundamentally synthetic instrument which has no intrinsic value. Hence, the recent seemingly illogical fluctuations in the market.
According to trade theory, the unending purpose of a market or instrument is to create and break price ranges according to the laws of supply and demand. We must determine when to trade based on each market inflection point as defined in price and in time as opposed to abandoning the trend (as the contrarian trading in this sub often does). Time and Price symmetry must be used to be in accordance with the trend. When coupled with a favorable risk to reward ratio, the ability to stay in the market for most of the defined time period, and adherence to risk management rules; the trader has a solid methodology for achieving considerable gains.
We will engage in a longer term market-oriented analysis to avoid any time-focused pressure. The Bitcoin market is open twenty-four-hours a day, so trading may be done when the individual is ready, without any pressing need to be constantly alert. Let alone, we can safely project months in advance with relatively high accuracy. Bitcoin is an asset which an individual can both trade and invest, however this article will be focused on trading due to the wide volatility in BTC prices over the short-term.

Technical Indicator Analysis of Bitcoin

Technical indicators are often considered self-fulfilling prophecies due to mass-market psychology gravitating towards certain common numbers yielded from them. They are also often discounted when it comes to BTC. That means a trader must be especially aware of these numbers as they can prognosticate market movements. Often, they are meaningless in the larger picture of things.
  • Volume – derived from the market itself, it is mostly irrelevant. The major problem with volume for stocks is that the US market open causes tremendous volume surges eradicating any intrinsic volume analysis. This does not occur with BTC, as it is open twenty-four-seven. At major highs and lows, the market is typically anemic. Most traders are not active at terminal discretes (peaks and troughs) because of levels of fear. Volume allows us confidence in time and price symmetry market inflection points, if we observe low volume at a foretold range of values. We can rationalize that an absolute discrete is usually only discovered and anticipated by very few traders. As the general market realizes it, a herd mentality will push the market in the direction favorable to defending it. Volume is also useful for swing trading, as chances for swing’s validity increases if an increase in volume is seen on and after the swing’s activation. Volume is steadily decreasing. Lows and highs are reached when volume is lower.
Therefore, due to the relatively high volume on the 12th of March, we can safely determine that a low for BTC was not reached.
  • VIX – Volatility Index, this technical indicator indicates level of fear by the amount of options-based “insurance” in portfolios. A low VIX environment, less than 20 for the S&P index, indicates a stable market with a possible uptrend. A high VIX, over 20, indicates a possible downtrend. VIX is essentially useless for BTC as BTC-based options do not exist. It allows us to predict the market low for $SPY, which will have an indirect impact on BTC in the short term, likely leading to the yearly low. However, it is equally important to see how VIX is changing over time, if it is decreasing or increasing, as that indicates increasing or decreasing fear. Low volatility allows high leverage without risk or rest. Occasionally, markets do rise with high VIX.
As VIX is unusually high, in the forties, we can be confident that a downtrend for the S&P 500 is imminent.
  • RSI (Relative Strength Index): The most important technical indicator, useful for determining highs and lows when time symmetry is not availing itself. Sometimes analysis of RSI can conflict in different time frames, easiest way to use it is when it is at extremes – either under 30 or over 70. Extremes can be used for filtering highs or lows based on time-and-price window calculations. Highly instructive as to major corrective clues and indicative of continued directional movement. Must determine if longer-term RSI values find support at same values as before. It is currently at 73.56.
  • Secondly, RSI may be used as a high or low filter, to observe the level that short-term RSI reaches in counter-trend corrections. Repetitions based on market movements based on RSI determine how long a trade should be held onto. Once a short term RSI reaches an extreme and stay there, the other RSI’s should gradually reach the same extremes. Once all RSI’s are at extreme highs, a trend confirmation should occur and RSI’s should drop to their midpoint.

Trend Definition Analysis of Bitcoin

Trend definition is highly powerful, cannot be understated. Knowledge of trend logic is enough to be a profitable trader, yet defining a trend is an arduous process. Multiple trends coexist across multiple time frames and across multiple market sectors. Like time structure, it makes the underlying price of the instrument irrelevant. Trend definitions cannot determine the validity of newly formed discretes. Trend becomes apparent when trades based in counter-trend inflection points continue to fail.
Downtrends are defined as an instrument making lower lows and lower highs that are recurrent, additive, qualified swing setups. Downtrends for all instruments are similar, except forex. They are fast and complete much quicker than uptrends. An average downtrend is 18 months, something which we will return to. An uptrend inception occurs when an instrument reaches a point where it fails to make a new low, then that low will be tested. After that, the instrument will either have a deep range retracement or it may take out the low slightly, resulting in a double-bottom. A swing must eventually form.
A simple way to roughly determine trend is to attempt to draw a line from three tops going upwards (uptrend) or a line from three bottoms going downwards (downtrend). It is not possible to correctly draw a downtrend line on the BTC chart, but it is possible to correctly draw an uptrend – indicating that the overall trend is downwards. The only mitigating factor is the impending stock market crash.

Time Symmetry Analysis of Bitcoin

Time is the movement from the past through the present into the future. It is a measurement in quantified intervals. In many ways, our perception of it is a human construct. It is more powerful than price as time may be utilized for a trade regardless of the market inflection point’s price. Were it possible to perfectly understand time, price would be totally irrelevant due to the predictive certainty time affords. Time structure is easier to learn than price, but much more difficult to apply with any accuracy. It is the hardest aspect of trading to learn, but also the most rewarding.
Humans do not have the ability to recognize every time window, however the ability to define market inflection points in terms of time is the single most powerful trading edge. Regardless, price should not be abandoned for time alone. Time structure analysis It is inherently flawed, as such the markets have a fail-safe, which is Price Structure. Even though Time is much more powerful, Price Structure should never be completely ignored. Time is the qualifier for Price and vice versa. Time can fail by tricking traders into counter-trend trading.
Time is a predestined trade quantifier, a filter to slow trades down, as it allows a trader to specifically focus on specific time windows and rest at others. It allows for quantitative measurements to reach deterministic values and is the primary qualifier for trends. Time structure should be utilized before price structure, and it is the primary trade criterion which requires support from price. We can see price structure on a chart, as areas of mathematical support or resistance, but we cannot see time structure.
Time may be used to tell us an exact point in the future where the market will inflect, after Price Theory has been fulfilled. In the present, price objectives based on price theory added to possible future times for market inflection points give us the exact time of market inflection points and price.
Time Structure is repetitions of time or inherent cycles of time, occurring in a methodical way to provide time windows which may be utilized for inflection points. They are not easily recognized and not easily defined by a price chart as measuring and observing time is very exact. Time structure is not a science, yet it does require precise measurements. Nothing is certain or definite. The critical question must be if a particular approach to time structure is currently lucrative or not.
We will measure it in intervals of 180 bars. Our goal is to determine time windows, when the market will react and when we should pay the most attention. By using time repetitions, the fact that market inflection points occurred at some point in the past and should, therefore, reoccur at some point in the future, we should obtain confidence as to when SPY will reach a market inflection point. Time repetitions are essentially the market’s memory. However, simply measuring the time between two points then trying to extrapolate into the future does not work. Measuring time is not the same as defining time repetitions. We will evaluate past sessions for market inflection points, whether discretes, qualified swings, or intra-range. Then records the times that the market has made highs or lows in a comparable time period to the future one seeks to trade in.
What follows is a time Histogram – A grouping of times which appear close together, then segregated based on that closeness. Time is aligned into combined histogram of repetitions and cycles, however cycles are irrelevant on a daily basis. If trading on an hourly basis, do not use hours.
  • Yearly Lows (last seven years): 1/1/13, 4/10/14, 1/15/15, 1/17/16, 1/1/17, 12/15/18, 2/6/19
  • Monthly Mode: 1, 1, 1, 1, 2, 4, 12
  • Daily Mode: 1, 1, 6, 10, 15, 15, 17
  • Monthly Lows (for the last year): 3/12/20 (10:00pm), 2/28/20 (7:09am), 1/2/20 (8:09pm), 12/18/19 (8:00am), 11/25/19 (1:00am), 10/24/19 (2:59am), 9/30/19 (2:59am), 8/29,19 (4:00am), 7/17/19 (7:59am), 6/4/19 (5:59pm), 5/1/19 (12:00am), 4/1/19 (12:00am)
  • Daily Lows Mode for those Months: 1, 1, 2, 4, 12, 17, 18, 24, 25, 28, 29, 30
  • Hourly Lows Mode for those Months (Military time): 0100, 0200, 0200, 0400, 0700, 0700, 0800, 1200, 1200, 1700, 2000, 2200
  • Minute Lows Mode for those Months: 00, 00, 00, 00, 00, 00, 09, 09, 59, 59, 59, 59
  • Day of the Week Lows (last twenty-six weeks):
Weighted Times are repetitions which appears multiple times within the same list, observed and accentuated once divided into relevant sections of the histogram. They are important in the presently defined trading time period and are similar to a mathematical mode with respect to a series. Phased times are essentially periodical patterns in histograms, though they do not guarantee inflection points
Evaluating the yearly lows, we see that BTC tends to have its lows primarily at the beginning of every year, with a possibility of it being at the end of the year. Following the same methodology, we get the middle of the month as the likeliest day. However, evaluating the monthly lows for the past year, the beginning and end of the month are more likely for lows.
Therefore, we have two primary dates from our histogram.
1/1/21, 1/15/21, and 1/29/21
2:00am, 8:00am, 12:00pm, or 10:00pm
In fact, the high for this year was February the 14th, only thirty days off from our histogram calculations.
The 8.6-Year Armstrong-Princeton Global Economic Confidence model states that 2.15 year intervals occur between corrections, relevant highs and lows. 2.15 years from the all-time peak discrete is February 9, 2020 – a reasonably accurate depiction of the low for this year (which was on 3/12/20). (Taking only the Armstrong model into account, the next high should be Saturday, April 23, 2022). Therefore, the Armstrong model indicates that we have actually bottomed out for the year!
Bear markets cannot exist in perpetuity whereas bull markets can. Bear markets will eventually have price objectives of zero, whereas bull markets can increase to infinity. It can occur for individual market instruments, but not markets as a whole. Since bull markets are defined by low volatility, they also last longer. Once a bull market is indicated, the trader can remain in a long position until a new high is reached, then switch to shorts. The average bear market is eighteen months long, giving us a date of August 19th, 2021 for the end of this bear market – roughly speaking. They cannot be shorter than fifteen months for a central-bank controlled market, which does not apply to Bitcoin. (Otherwise, it would continue until Sunday, September 12, 2021.) However, we should expect Bitcoin to experience its’ exponential growth after the stock market re-enters a bull market.
Terry Laundy’s T-Theory implemented by measuring the time of an indicator from peak to trough, then using that to define a future time window. It is similar to an head-and-shoulders pattern in that it is the process of forming the right side from a synthetic technical indicator. If the indicator is making continued lows, then time is recalculated for defining the right side of the T. The date of the market inflection point may be a price or indicator inflection date, so it is not always exactly useful. It is better to make us aware of possible market inflection points, clustered with other data. It gives us an RSI low of May, 9th 2020.
The Bradley Cycle is coupled with volatility allows start dates for campaigns or put options as insurance in portfolios for stocks. However, it is also useful for predicting market moves instead of terminal dates for discretes. Using dates which correspond to discretes, we can see how those dates correspond with changes in VIX.
Therefore, our timeline looks like:
  • 2/14/20 – yearly high ($10372 USD)
  • 3/12/20 – yearly low thus far ($3858 USD)
  • 5/9/20 – T-Theory true yearly low (BTC between 4863 and 3569)
  • 5/26/20 – hashrate difficulty halvening
  • 11/14/20 – stock market low
  • 1/15/21 – yearly low for BTC, around $8528
  • 8/19/21 – end of stock bear market
  • 11/26/21 – eighteen months from halvening, average peak from halvenings (BTC begins rising from $3000 area to above $23,312)
  • 4/23/22 – all-time high
Taken from my blog: http://aliamin.info/2020/
submitted by aibnsamin1 to Bitcoin [link] [comments]

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