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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]

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]

[Not my post] The Structure of Forex Brokers

Originally posted by Darkstar at Forex Factory.
Disclaimer: I did not write this. I found this post on ForexFactory written by a user called DarkStar, which I believe a lot of redditors will benefit from reading.
________________________________________________________________________________________________________
There has been much discussion of late regarding borker spreads and liquidity. Many assumptions are being made about why spreads are widened during news time that are built on an incomplete knowledge of the architecture of the forex market in general. The purpose of this article is to dissect the market and hopefully shed some light on the situation so that a more rational and productive discussion can be undertaken by the Forex Factory members.
We will begin with an explanation of the purpose of the Forex market and how it is utilized by its primary participants, expand into the structure and operation of the market, and conclude with the implications of this information for speculators. With that having been said, let us begin.
Unlike the various bond and equity markets, the Forex market is not generally utilized as an investment medium. While speculation has a critical role in its proper function, the lion’s share of Forex transactions are done as a function of international business.
The guy who buys a shiny new Eclipse more then likely will pay for it with US Dollars. Unfortunately Mitsubishi’s factory workers in Japan need to get their paychecks denominated in Yen, so at some point a conversion needs to be made. When one considers that companies like Exxon, Boeing, Sony, Dell, Honda, and thousands of other international businesses move nearly every dollar, real, yen, rubble, pound, and euro they make in a foreign country through the Forex market, it isn’t hard to understand how insignificant the speculative presence is; even in a $2tril per day market.
By and large, businesses don’t much care about the intricacies of exchange rates, they just want to make and sell their products. As a central repository of a company’s money, it was only natural that the banks would be the facilitators of these transactions. In the old days it was easy enough for a bank to call a foreign bank (or a foreign branch of ones own bank) and swap the stockpiles of currency each had accumulated from their many customers.
Just as any business would, the banks bought the foreign currency at one rate and marked it up before selling it to the customer. With that the foreign exchange spread was born. This was (and still is) a reasonable cost of doing business. Mitsubishi can pay its customers and the banks make a nice little profit for the hassle and risks associated with moving around the currency.
As a byproduct of transacting all this business, bank traders developed the ability to speculate on the future of currency rates. Utilizing a better understanding of the market, a bank could quote a business a spread on the current rate but hold off hedging until a better one came along. This process allowed the banks to expand their net income dramatically. The unfortunate consequence was that liquidity was redistributed in a way that made certain transactions impossible to complete.
It was for this reason and this reason alone that the market was eventually opened up to non-bank participants. The banks wanted more orders in the market so that a) they could profit from the less experienced participants, and b) the less experienced participants could provide a better liquidity distribution for execution of international business hedge orders. Initially only megacap hedge funds (such as Soros’s and others) were permitted, but it has since grown to include the retail brokerages and ECNs.

Market Structure:
Now that we have established why the market exists, let’s take a look at how the transactions are facilitated:
The top tier of the Forex market is transacted on what is collectively known as the Interbank. Contrary to popular belief the Interbank is not an exchange; it is a collection of communication agreements between the world’s largest money center banks.
To understand the structure of the Interbank market, it may be easier to grasp by way of analogy. Consider that in an office (or maybe even someone’s home) there are multiple computers connected via a network cable. Each computer operates independently of the others until it needs a resource that another computer possesses. At that point it will contact the other computer and request access to the necessary resource. If the computer is working properly and its owner has given the requestor authorization to do so, the resource can be accessed and the initiating computers request can be fulfilled. By substituting computers for banks and resources for currency, you can easily grasp the relationships that exist on the Interbank.
Anyone who has ever tried to find resources on a computer network without a server can appreciate how difficult it can be to keep track of who has what resources. The same issue exists on the Interbank market with regard to prices and currency inventory. A bank in Singapore may only rarely transact business with a company that needs to exchange some Brazilian Real and it can be very difficult to establish what a proper exchange rate should be. It is for this purpose that EBS and Reuters (hereafter EBS) established their services.
Layered on top (in a manner of speaking) of the Interbank communication links, the EBS service enables banks to see how much and at what prices all the Interbank members are willing to transact. Pains should be taken to express that EBS is not a market or a market maker; it is an application used to see bids and offers from the various banks.
The second tier of the market exists essential within each bank. By calling your local Bank of America branch you can exchange any foreign currency you would like. More then likely they will just move some excess currency from one branch to another. Since this is a micro-exchange with a single counterparty, you are basically at their mercy as to what exchange rate they will quote you. Your choice is to accept their offer or shop a different bank. Everyone who trades the forex market should visit their bank at least once to get a few quotes. It would be very enlightening to see how lucrative these transactions really are.
Branching off of this second tier is the third tier retail market. When brokers like Oanda, Forex.com, FXCM, etc. desire to establish a retail operation the first thing they need is a liquidity provider. Nine in ten of these brokers will sign an agreement with just one bank. This bank will agree to provide liquidity if and only if they can hedge it on EBS inclusive of their desired spread. Because the volume will be significantly higher a single bank patron will transact, the spreads will be much more competitive. By no means should it be expected these tier 3 providers will be quoted precisely what exists on the Interbank. Remember the bank is in the business of collecting spreads and no agreement is going to suspend that priority.
Retail forex is almost akin to running a casino. The majority of its participants have zero understanding how to trade effectively and as a result are consistent losers. The spread system combined with a standard probability distribution of returns gives the broker a built in house advantage of a few percentage points. As a result, they have all built internal order matching systems that play one loser off against a winner and collect the spread. On the occasions when disequilibrium exists within the internal order book, the broker hedges any exposure with their tier 2 liquidity provider.
As bad as this may sound, there are some significant advantages for speculators that deal with them. Because it is an internal order book, many features can be provided which are otherwise unavailable through other means. Non-standard contract sizes, high leverage on tiny account balances, and the ability to transact in a commission free environment are just a few of them…
An ECN operates similar to a Tier 2 bank, but still exists on the third tier. An ECN will generally establish agreements with several tier 2 banks for liquidity. However instead of matching orders internally, it will just pass through the quotes from the banks, as is, to be traded on. It’s sort of an EBS for little guys. There are many advantages to the model, but it is still not the Interbank. The banks are going to make their spread or their not go to waste their time. Depending on the bank this will take the form of price shading or widened spreads depending on market conditions. The ECN, for its trouble, collects a commission on each transaction.
Aside from the commission factor, there are some other disadvantages a speculator should consider before making the leap to an ECN. Most offer much lower leverage and only allow full lot transactions. During certain market conditions, the banks may also pull their liquidity leaving traders without an opportunity to enter or exit positions at their desired price.

Trade Mechanics:
It is convenient to believe that in a $2tril per day market there is always enough liquidity to do what needs to be done. Unfortunately belief does not negate the reality that for every buyer there MUST be a seller or no transaction can occur. When an order is too large to transact at the current price, the price moves to the point where open interest is abundant enough to cover it. Every time you see price move a single pip, it means that an order was executed that consumed (or otherwise removed) the open interest at the current price. There is no other way that prices can move.
As we covered earlier, each bank lists on EBS how much and at what price they are willing to transact a currency. It is important to note that no Interbank participant is under any obligation to make a transaction if they do not feel it is in their best interest. There are no “market makers” on the Interbank; only speculators and hedgers.
Looking at an ECN platform or Level II data on the stock market, one can get a feel for what the orders on EBS look like. The following is a sample representation:
You’ll notice that there is open interest (Level II Vol figures) of various sizes at different price points. Each one of those units represents existing limit orders and in this example, each unit is $1mil in currency.
Using this information, if a market sell order was placed for 38.4mil, the spread would instantly widen from 2.5 pips to 4.5 pips because there would no longer be any orders between 1.56300 and 1.56345. No broker, market maker, bank, or thief in the night widened the spread; it was the natural byproduct of the order that was placed. If no additional orders entered the market, the spread would remain this large forever. Fortunately, someone somewhere will deem a price point between those 2 figures an appropriate opportunity to do something and place an order. That order will either consume more interest or add to it, depending whether it is a market or limit order respectively.
What would have happened if someone placed a market sell order for 2mil just 1 millisecond after that 38.4 mil order hit? They would have been filled at 1.5630 Why were they “slipped”? Because there was no one to take the other side of the transaction at 1.56320 any longer. Again, nobody was out screwing the trader; it was the natural byproduct of the order flow.
A more interesting question is, what would happen if all the listed orders where suddenly canceled? The spread would widen to a point at which there were existing bids and offers. That may be 5,7,9, or even 100 pips; it is going to widen to whatever the difference between a bid and an offer are. Notice that nobody came in and “set” the spread, they just refused to transact at anything between it.
Nothing can be done to force orders into existence that don’t exist. Regardless what market is being examined or what broker is facilitating transactions, it is impossible to avoid spreads and slippage. They are a fact of life in the realm of trading.

Implications for speculators:
Trading has been characterized as a zero sum game, and rightly so. If trader A sells a security to trader B and the price goes up, trader A lost money that they otherwise could have made. If it goes down, Trader A made money from trader B’s mistake. Even in a huge market like the Forex, each transaction must have a buyer and a seller to make a trade and one of them is going to lose. In the general realm of trading, this is materially irrelevant to each participant. But there are certain situations where it becomes of significant importance. One of those situations is a news event.
Much has been made of late about how it is immoral, illegal, or downright evil for a broker, bank, or other liquidity provider to withdraw their order (increasing the spread) and slip orders (as though it was a conscious decision on their part to do so) more then normal during these events. These things occur for very specific reasons which have nothing to do with screwing anyone. Let us examine why:
Leading up to an economic report for example, certain traders will enter into positions expecting the news to go a certain way. As the event becomes immanent, the banks on the Interbank will remove their speculative orders for fear of taking unnecessary losses. Technical traders will pull their orders as well since it is common practice for them to avoid the news. Hedge funds and other macro traders are either already positioned or waiting until after the news hits to make decisions dependent on the result.
Knowing what we now know, where is the liquidity necessary to maintain a tight spread coming from?
Moving down the food chain to Tier 2; a bank will only provide liquidity to an ECN or retail broker if they can instantly hedge (plus their requisite spread) the positions on Interbank. If the Interbank spreads are widening due to lower liquidity, the bank is going to have to widen the spreads on the downstream players as well.
At tier 3 the ECN’s are simply passing the banks offers on, so spreads widen up to their customers. The retailers that guarantee spreads of 2 to 5 pips have just opened a gaping hole in their risk profile since they can no longer hedge their net exposure (ever wonder why they always seem to shut down or requote until its over?). The variable spread retailers in turn open up their spreads to match what is happening at the bank or they run into the same problems fixed spreads broker are dealing with.
Now think about this situation for a second. What is going to happen when a number misses expectations? How many traders going into the event with positions chose wrong and need to get out ASAP? How many hedge funds are going to instantly drop their macro orders? How many retail traders’ straddle orders just executed? How many of them were waiting to hear a miss and executed market orders?
With the technical traders on the sidelines, who is going to be stupid enough to take the other side of all these orders?
The answer is no one. Between 1 and 5 seconds after the news hits it is a purely a 1 way market. That big long pin bar that occurs is a grand total of 2 prices; the one before the news hit and the one after. The 10, 20, or 30 pips between them is called a gap.
Is it any wonder that slippage is in evidence at this time?

Conclusions:
Each tier of the Forex market has its own inherent advantages and disadvantages. Depending on your priorities you have to make a choice between what restrictions you can live with and those you cant. Unfortunately, you can’t always get what you want.
By focusing on slippage and spreads, which are the natural byproduct of order flow, one is not only pursuing a futile ideal, they are passing up an enormous opportunity to capitalize on true inefficiencies. News events are one of the few times where a large number of players are positioned inappropriately and it is fairly easy to profit from their foolishness. If a trader truly wants to make the leap to the next level of profitability they should be spending their time figuring out how identify these positions and trading with the goal of capturing the price movement they inevitably will cause.
Nobody is going to make the argument that a broker is a trader’s best friend, but they still provide a valuable service and should be compensated for their efforts. By accepting a broker for what it is and learning how to work within the limitations of the relationship, traders have access to a world of opportunity that they otherwise could never dream of capturing. Let us all remember that simple truth.
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