I’ve never managed to get a 50R trade, through manual trading – the best trades have been around 30R.  Having a robot do the entries and management, certainly makes things easier, and removes the human factor in banking too early.

The ‘Bot’ as we call it on the Skype group, is still not finished and doesn’t look like it will be before 2025 – I am just getting too many things to code and test, as each week passes. It’s seemingly never ending and one of the reasons that I’ve been slack with my blog posts and everything else is life.  The trades that the Bot is designed to trade can all be done manually (obviously) using eWavesHarmonics, ABC123 and ATM – I’m trying to make this as close to my own trading as possible although the Bot is more setup-driven, whereas my manual trading is more HTF-target-driven.
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At time of writing, with 1% risk per trade, the EA is generating over 10,000% profit on a GB £10k a/c in 14 months of back testing; 12,337% profit on a US $10k a/c (the difference is due to the 100-lot size maximum value limit).

Live trading results are very close to the back testing results but due to the number of variables, for all the different market conditions, we’ve yet to realise the true potential in live; I’m quietly confident that we will eventually. The general idea, with the automation, is that Fibonacci-based price patterns repeat themselves -even if they don’t always deliver the same results – so, given enough time, we should see everything repeat at least once.  Indeed, we have already seen numerous occurrences of some setups.

To give you an idea of how the Bot trades, and hopefully some ideas for your own trading, I’ve taken the top 5 trades with over 25% profit (@1% risk per trade) and uploaded them to the Trader Training Course (still free for eWH and ATM licence holders). I’ve explained the logic for entry and exit – all quite basic stuff really, but it’s the simple things that we often overlook as traders. I hope it helps with your trading.

Does more than 10,000% profit in a year sound to good to be true?   Well, you know what they say, but it’s 100% possible in theory and according to the past year of back testing.  I'd love to see another 50R+ this December - I'll let you know if we do.

Before I get into the subject matter, I should really comment on the previous post: what a load of tosh that turned out to be. Instead of seeing the bears run rampant, we saw new all-time highs on DAX and DOW, although the first week of Sept started very bearish.   NASD also made a good gain, after a heavy start, getting back to test the ATH supply, formed back in July.  It just goes to show that you can’t always rely on history repeating itself nor can you rely solely on statistics to accurately predict the future of price action.
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The subject of statistics is the point of this blog post, once again – I am rather fond of them, despite the September-effect being irrelevant this year.  I’ve always remembered the formula for Spearman’s Rank Coefficient, for some odd reason.  I memorised if for my Statistics ‘A’ level exam, back in the days when Hugh Cornwell was the front man for my all-time favourite band, and was very disappointed to see it presented at the top of the exam paper. There is little else that I remember from my mathematical learning, other than the benefits of statistical analysis I’ve yet to use Spearman’s formula for trading, although have seen reference to it.  Instead, I’ve simply focused on win/loss ratios using the EA that’s been in forward-testing since June.  If, like me, you trade the DOW, from when the NYSE bell rings, you might find these stats to be of interest, or even relate to them from your own trading experiences.

As per previous stats blog post, the EA basically trades Fibonacci retraces, with confluence.  There is seemingly an infinite number of permutations and combinations for the setups.  As each week passes, I find more and code the extra variables, seeking to improve the profits and reduce the drawdown. All the trade history is posted to a CSV file, so - with the help of some pivot tables - I can see what works well and what should be avoided; that applies to the setups and, more recently as I’ve discovered, times. I was hoping to have this EA running nicely without the ‘tweakamisations’ by now but the markets keep throwing their curve balls, so am resigned to the work continuing until year end, if not into next year. 

Anyway, enough waffle and onto the stats. The data below is for a little over one year of EA-trading DOW – mostly back-tested results, although back testing is very close to forward testing, give or take some spread variations that can occur at random times.
  
Best months – bearing in mind that I have some overlap with August and September history: 

January and July top the list with a 32%-win rate.  April was a super month for profit but that had one trade with a 50% gain, so is a tad misleading.  August and September, as we’ve seen from our live trading, have been very tricky months. We had 17 losing trades in a row in Sept: no fun at all.   I’ll need another 4 years of forward-testing to get some real meaningful monthly stats – remind me to share the results in 2028.
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Best days of the week to trade DOW: -

Thursdays are, without doubt, the best day of the week, followed by Tuesdays.  You might as well take Monday off, although even with a win rate of just 22.11% there was still a profit to be had, from 190 trades.  A return of 257R – or 257% (non-compound) gain if you risk 1% per trade – from just trading on a Thursday is impressive.

Best hour on any day of the week – this is broker time (GMT+2) with the NYSE bell going ding ding at 16:30.  Note that I’ve previously found that 20:00 has a very low win rate, so the EA only takes a trade on the hour, not during it: there have been two such trades.

Apart from 20:00, the lowest chance of success is in the hour after the NYSE opened.  The first half hour generates the best returns but with just a 1 in 4 chance of success; that’s perfectly understandable given the often-seen whipsaw followed by the long duration for which the trade might stay open. The best chance of success is during 21:00 but the returns aren’t so great, due to the limited time left for the trade to stay open: the EA closes any open trades before the markets close and, it’s worth pointing out, will only take one trade during the first 17 minutes after the bell rings.

​If we look at every hour in each day of the week, with focus on there being a reasonable number of trades taken, the stats show that the first half hour of Thursdays is the time to trade, if you can only spare that amount of time in a week. Thursday 19:00 also generates good returns with a 47% win rate, but there’s only a sample of 17 trades for that time. Friday 16:00 is crap, although … law of sods ... this Friday, with that time switched off for the live account EA but not the demo account EA, it did this trade, for over 5R; would have been 7R by sticking with the TP and not activating the trailing trade management.

I’ll not go into all the stats now, but I’ve also gathered additional data for success rates: the day before US holidays (bad) and the actual US holiday (surprisingly good); the days before FOMC (bad) and FOMC day after 18:00 (good); Triple Witching days aren’t so good but better if you wait until after 19:00 (although I only have 5 of those days in my stats); GDP news day – bad when it’s on a Wednesday but good on a Thursday ... and so on ...

These stats are from the EA trading but I believe the times discussed should be relevant for many DOW traders who buy the dips and sell the rallies (basic price action trading, in a nutshell). It might be a different experience for the squiggly line or breakout traders (shudder at the thought).  I’ve found all this to be interesting and the data certainly improves the results for the robot. As with all stats though, they’ll need to be revisited as we get new data. Please drop me an email if your own experiences are completely different.

Bears out for the indices this month?  It certainly seems to have started that way, with NASDAQ dropping 700 points yesterday, and DOW over 600 points.

The last four years have seen strong bear markets for the indices but bull markets for the US Dollar Index.  Since 1929, the S&P has, on average, seen a decline  in September - most of you know that September 1929 was the start of the great depression that lasted for ten years. Perhaps that's why we see history so often repeating itself for this month.

My chart data goes back to 2002, so I've done my own analysis to see what the chances are for this month being all doom-and-gloom.  I don't trade the S&P so have left it off, preferring to stick with the indices that I do like to trade.  Out of the 22 years of data, DAX fell on 12 Septembers, DOW on 11 of them and NASD on 12.  That puts the chances of a drop for the month at a little over 50%; but a 100% chance if we just look at the last four years.

With rare exception (2006, 2009, 2018 & 2019), the US Dollar index has risen when the NASD fell and dropped when the NASD climbed - not really a surprise.  We've enjoyed trading to the new all-time-highs (ATH) on the indices in the past couple of months and, as we've so often seen before, the ATHs eventually precede a big correction - profit-taking - before the next move for a new ATH begins.  We just need to identify the reversal zones to buy the dips, as the indices always go back up.

If history and yesterday is anything to go by, it looks like we could be in for another good bearish September on the indices - enjoy the ride.

Due to the low leverage that is available to many traders, since the ESMA regulations were introduced, 5 years ago, some traders have experienced 'Not Enough Money' errors when trying to place trades with ATM, even when only risking 1% on a trade - that's essentially saying there isn't sufficient margin available.

I've made an upgrade to ATM to mitigate this annoyance: ATM will now reduced the lot size, calculated from the percentage risk, by the smallest lot size possible, until it detects that there is sufficient margin. 

Those who have tested this upgrade have reported back to say all is now good.  The upgraded version is available for download from the installation page.

It’s nearly a whole year since I started what became known as ‘The Project’: writing some auto-traders (robots / bots / EAs) that could be left to their own devices but allowing for some human intervention if required. Whilst I have written countless robots over the past decade or so, this is the first bot project that has consumed so much of my time with near-100% focus, often at the expense of my own trading. The key criterium, for the long-term results, is a simple one: the robot must achieve 10x more percentage profit than drawdown.  So, if it achieved 100% profit, the maximal drawdown must not exceed 10%.  For the most part, that has been relatively easy to achieve.

The bulk of my time goes into tweaking and constant back testing, across at least three different brokers. All this time spent on development and testing has taught me some valuable lessons, not only about how bad the MT4 back testing can be, but also some for my own trading and how different the brokers’ price feeds can be.

I thought some of you might get something from my lessons, hence the post – lessons learned in no order, just as they come to mind.

DO NOT TRUST BACK TESTING RESULTS
For some obscure reasons, the MetaTrader back testing is heavily biased to showing positive results. I have no idea why MetaQuotes made it so but it’s a total pain in the arse.  You can not back test trailing stops within a one-minute bar, for example, as the tick data isn’t there; even if it was there, it would be vastly different between brokers, so you have to make the stops very conservative – far from price -to avoid spikes that the back testing would otherwise not show as stopping your trade.  There is also the problem of variable spreads.  I’ve seen some wild random spreads (not news driven) on ICM and Pepperstone that back testing won’t pick up: you’d be stopped in live trading or have profits much reduced with the lot size calculation, whereas back testing will say all is hunky dory and the bot grabbed a great trade. The only way to properly test the bot is on a live account, for several months.  After each week of live testing, I like to back test that week to compare results, then code some workarounds so back and forward tests eventually align, as much as is possible; it will never be 100%. 

KEEP IT SIMPLE
My previous bot traded five different setups.  It achieved >1000% profit for around 20% DD, in less than a year – according to the back testing – but became a monster to tweak and maintain. The other problem was that the base variables for the whole program might not be the best for each setup. After many months in development, I’ve ended up spending many more weeks creating deconstructed bots: one for each setup.  This has allowed me to reduce the number of variables in each program and fine tune each setup.  Now I have individual bots tuned to achieve the long-term target 10:1 ratio, that collectively achieve a greater return than the all-in-one bot. That's just like normal trading: keep it simple and have specific rules for each setup that you trade.

THE PERFECT WAY TO PROVE THE EFFECTIVENESS OF YOUR OWN TRADING SETUPS
This has been the most beneficial experience, apart from the buzz of creating profitable bots.  It takes so much longer to visually back test setups but once coded into a bot, it takes no time at all to confirm if a setup is really any good for manual trading.   I have at least another ten setups to code and test – this will keep me busy until 2025. I’ve always said that any trading idea could be turned into a robot, if it’s any good: the information that a human trader uses is, after all, mostly just a load of binary inputs (on/off; true/false; it is or it isn’t).  Has X done Y; is A greater than B, does Q=R; etc. Traders should trade like robots and thus the trading rules could be coded as such.
 
KEEP TRADING THE SETUPS EVEN AFTER A COUPLE OF WEEKS OF DRAWDOWN
I’ve seen, from the back testing, that most of my bots go into draw down, for a couple of weeks here and there.  When looking at the daily bars, for those draw down periods, I find the average daily range has shrunk to way below normal, or price is stuck in a tight range – it’s no wonder that the bots struggle; I would have struggled to manually trade those periods.  It’s pointless expending too much effort into coding workarounds for those periods – time is far better spent on optimising for ‘normal’ periods and just accepting that there will be some weeks of DD.  Liquidity will invariably return but we never know when, so it’s just best to keep trading the setups, knowing that the tightly coiled spring will eventually go BOING! From working with countless traders, I’ve seen too many give up when they have periods of draw down; they go in search of better short-term trading ideas and leave behind the most valuable ideas that work in the longer term.  Trading (manual or automated) is a long-term game that you cannot judge after just a few weeks.
 
FIBONACCI RETRACEMENTS OF IMPULSIVE MOVES WORK
… but they work a lot better when you have plenty of confluence. Of all the bots that I’ve written, trading Fib Rs has been the most successful – achieving 1,114% profit with 15% DD, in less than a year.  I suspect there are a lot of Fib R bot traders out there, which helps to make the method more successful. I also suspect they will use different approaches to look for confluence – it doesn’t really matter what you use if it works. I use the information provided by the opening ranges but am looking to add a few other factors for added confluence. To benefit from the rewards of trading Fib Rs, you need to give price plenty of room to do its thing, such as in the last blog post – those occasional big moves will more than make up for extended periods of DD; just like with manual trading.

Which are the best retracement levels to trade? Good question … the Fib R bot trades 38, 50, 62 and 78% retraces.  Individually when just the one Fib R is traded, the results (from the same period that generated the 1114% profit) are: -

• 38%:74% profit for 21% Maximal DD
• 50%: 110% for 12%
• 62%: 110% for 18% - I find that surprising, with 62% being the key ratio.
• 78%: 134% for 13% - by far the best but only according to the way the bot trades

I’ll probably test others eventually but the above 4 are working perfectly well, if not all individually meeting my 10:1 goal. The compounded result, with ever growing lot sizes, is the key to big account growth with relatively low DD.
 
WAIT FOR UPSIDE/DOWNSIDE REJECTION TO SIGNAL THE CHANGE OF DIRECTION FROM KEY LEVELS
Japanese candlestick analysts will use individual, or a combination of, different types of bars – all with names that few traders will easily remember.  If you’ve done my trading course, you’ll know that I dislike candlestick names and just prefer to see what a price bar has done, or (more importantly) a combination of price bars.  When you combine several bars, you can identify upside and downside rejections (or call them pin bar combos if you must) that, when they occur at key levels, can be effectively used to confirm a trade. Success, without these rejection combos, is greatly reduced.

NOT ALL BROKERS ARE CREATED EQUAL
This has been the most surprising discovery.  A bot that trades the exact same setups with the exact same inputs should roughly generate the same results on all brokers – at least that’s what any normal trader would assume.  Alas, that’s not the case, since the liquidity providers generate their own prices.  I’ve seen a difference of more than 10 points on DOW between brokers and individual M1 bars can vary tremendously.  Just to give you an idea, back testing the Fib R bot just for April this year (a particularly successful month, mostly because of the massive move on the 4th)

• Pepperstone: 93% for 12.7% DD
• ICM: 68% profit for 12%
• FTMO: 35% for 10.6%.

 
Why FTMO performs so badly, relative to Pepperstone, has yet to be determined but it’s quite an eye-opener and consistent with all the bots that I’ve tested. However, results can be vastly improved with some FTMO-specific optimisation, to get it much closer to Pepperstone results.
 
I could go on but that’s enough blah blah for this post.  I might do a follow up in the future, as more bots are created and tested – the simple ABC zigzag should generate some interesting stats and allow me to prove just how valuable the FE127 is.   In the meantime, … back to the project I go.

Every day, in our Skype group, we look to buy the dips and sell the rallies; i.e. we look to identify the end of corrective moves, to get in early on the next impulsive move.  It's a simple tried-and-tested approach that makes for the big Rs trades.

Last night saw the most perfect example on the DOW 1 minute chart. Sadly for me, it happened after my trading day had finished, but what a gem of a trade it would have been - an easy 50R+..  That would double your account in just a few hours, with 2% risk.

Using eWH and the ABC123 indies, DOW showed a golden zone correction for a perfect P5 setup, along with a double top and ABC FE62 correction  back to prior support: plenty of confluence to place a short trade with a tight stop - a very low point risk trade.  The rest speaks for itself..  

Trading really doesn't have to be complicated.  I just need to finish the work on the EA that trades these setups for when I'm away from the trading desk.

This popped up when I was browsing Reddit - so true!

A few of us, in our Skype Trading Group, took this trade yesterday, with various degrees of profit taking.  It's a fine example of how a top-down analysis with entries from the M1 time frame, can give terrific R:R.   

We have had strong upside targets on the monthly/weekly/daily time frames, that we've been aiming for over the past few months.  The "tea leaves" have been spot on and I am still expecting DOW to reach the 40K level, sooner or later.

M15 showed a very strong impulsive move up and the day of the trade was a very clear corrective wave.  During the NEO session, price had broken the overnight high then retraced for much of the session before the London Close.  The ABC123 indi showed FE127 just above a kick-start gap, that had preceded the break of the overnight high - a fine area of demand to be looking to buy; all discussed in the Skype chat so everyone had a chance to prepare.

With a strong price magnet of M15 TZ1 to aim for, there was no question that we'd be looking for the next impulsive move up; we just had to wait for the correction to complete and press the ATM 'buy' button. 

I have uploaded annotated chart pictures to the Training Course - in the section at the bottom with lots of other examples of successful trades done by Skype Group members.  It's worth taking a look - you only need a few of these a year to be very happy, but you'll likely see such examples every week, if you know what to look for.

Trading made simple with eWavesHarmonics and the ABC123 indi ...

Another year over, and we end the year with the indices at all time highs - who'd have thought that was possible, when the year started and so many global issues ?  Well, we did get a clue with eWH, a few months before the end of 2022 - good "tea leaves" (some of you will know what I mean by that).

Once again, many many thanks to you all for your support and success stories throughout 2023 - particularly to my many friends in our Skype Trading Group who have provided such great company.  Big CONGRATULATIONS to those of you who have passed prop-firm challenges after doing the course.  I hope to be able to work with more of you, this coming year, to help you improve your trading and see more of you achieve your dream of becoming prop-firm funded traders; or any other kind of trader for that matter.

All the very best for the festive season and may 2024 be your best trading year yet; and let there be peace on earth for everyone. 

If you’re diligent enough to keep a journal, or at least review your trade history on a regular basis, you will know what your ratio of winning to losing trades is. When you know this (rather basic) information, you’ll have a pretty good idea of what sort of R:R trades you should always be aiming for; avoiding trades that don't offer at least your minimum required returns.

I recently received an email from a wonderful lady, who is a long-time customer,  asking if I could make a change to ATM to place automatic stop losses; effectively making the stop loss wide enough to reduce the number of stop outs / losing trades. ATM can already do stop loss placements using custom indicators, as well as auto-entering a trade, so of course the request could be accommodated. However, such a request begs the question: is it a good idea to go with a wider stop loss, to reduces stop-outs whilst also reducing the potential profitability of a trade? That’s assuming you’re risking a percentage per trade, rather than fixed lots, of course.

As I’ve discussed in previous blog posts, I’m a big fan of looking for very low pip/point risk (VLPR) trades, with the goal of achieving at least 5R but seeking 10R or more; this really isn’t hard when taking trades on the lower timeframes.  This approach allows for more losing trades but, in my experience, greater profitability. It also makes trading that much more interesting – and challenging – although it might not be everyone’s cup of tea.  I’ve done some calculations, to compare profitability based on average win-rate – over 10 trades – compared with average R:R per trade.  This table assumes 1% risk per trade on a constant balance of £10,000; in reality that balance would fluctuate after every trade, but I’m trying to keep it simple. (click on the table to enlarge it).

With my average R:R per trade being 5, I need only be right once in every 5 trades to make a profit.  If I’m right 40% of the time, I can make a healthy 14% profit with 10 trades.

On the other hand, by widening your stop loss you’ll reduce your R:R.  So, let’s say I’m now looking for 2R trades … I would need to be right 50% of the time, just to make 5% profit from 10 trades; or find 80% winners to make 14% profit.  Making 8 profitable trades in every 10 is a very big ask – not impossible, but extremely challenging.  Personally, I’d much rather feel comfortable about having a losing trade: it’s no big deal when you’re always aiming for a 5% return on a trade.
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Something to think about but at the end of the day, every trader needs to find their own comfort zone with win/loss ratios and average R:Rs.