Interviewed By Chat with Traders

Interviewed By Chat with Traders

A couple of weeks ago, I had the pleasure of being interviewed By Aaron from Chat with Traders.  I discussed my journey, what I think new traders should focus on, as opposed to what the typical new trader does focus on and more. And we talk pirates. Arrr!

episode-95-adeyf-chat with traders

Chat with Traders is a great site with a lot of really interesting interviews.  Below is a list of some of my favourites.

EP 039: Tom Dante speaks to the competitiveness of trading and essential skill sets for profitability

EP 037: Understanding areas of acceptance, thinking in probabilities & creating a legacy w/ @FuturesTrader71

EP 061: A scientific trading perspective, process over outcome, and the law of large numbers w/ Ari Pine

EP 063: Strong determination, preserving mental capital, and professionally trading futures w/ Nicola Duke

EP 070: Specializing, automating, and using stats for high probability trade setups w/ Jeff Davis

EP 082: How to become the trader you wish you were w/ @FuturesTrader71

EP 093: What an order flow fanatic adapted from one of the “big boys” — Ben, @BLB_Capital

It’s not me, it’s you – the relationship between your edge and variance.

It’s not me, it’s you – the relationship between your edge and variance.

One of the important things in trading is understanding from a probability perspective what is likely to happen, when you actually use your trading system over time.

Why is this important.

If we do not understand what results the trading system is likely to produce, then we cannot answer the following questions when we review our trading.

Does my system still have an edge?

Is any under performance of the trading system down to variance or is it the trader underperforming?

What do I mean by that?

The best way to explain this is to use an example.

We have a trading system that has win rate of 50%. The average winners are 1.5 bigger than the average losers, and we risk 1% of our account.

First let’s look at the probability of having a losing streak. There is a 76.8% chance of having 5 losers in a row.

If you were using this trading system and did not know that there is a high probability of having 5 losers in a row, then when this happens the first reaction could be the system has no edge and start looking for a new system.

Or the reaction could be that I am trading like shit and need to sort my trading out.

The above statements could be true, but having 5 losers in a row with this system is not an indicator of either of these statements.

Is the next trade going to be a winner?

It took me a while to understand this, but we do not know probability of the outcome of the next trade.

If we have a trading system that has a win rate of 70%, the next trade does not have a 70% chance of winning. The win rate does not refer to individual trades but to a sample size. Having a win rate of 70%, says that over a large enough sample of trades, 70% of the trades will be winners.

So what is the probability of the next one to be a winner. The answer is 50%. Why 50%, we cannot tell what order the winners and losers are going to come. So we do not know the outcome of the next trade, we just know that if we follow our trading system, that over time we will have 70% winners.

And the fact that we do not know what order the winners and losers will be in the sample size, we only know the overall percentages.

This means that over a large sample size, the actual return on the account balance can be different.

Using Monte Carlo to understand the variance in our trading system.

What is Monte Carlo? Here is the an article that explains it better than I could.

I am using Monte Carlo to simulate a trading system over a 500 trade period and what effect that will have on the account balance. But as we do not the outcome of each individual trade, the order if winners / losers are randomised.

I then rerun the simulation for another 50 times, and this gives me a range of returns.

The best way to look at this, is that we are comparing the returns of a trading system over 500 trade period against the same trading system x 50.

This is a trading system with a win rate of 50%, winners 1.5 r , losers 1 r and risk per trade 1% of account balance. Starting account balance is 10000 USD.

1. Across the 50 simulations, the worse draw down was 66%.

2. The highest finish account balance was 51,219 USD

3. The lowest finish account balance was 19,854 USD

Whilst the trading system is profitable, that actual returns are different, and different by 31,365 USD.

How do I use this information?

Every quarter I enter the previous quarters system stats into the spreadsheet, including the average number of trades per day. This will then give me likely figures for the variance in expected returns, I then break this down into months and weeks.

Once I have these figures, I use these in my end of week reviews to see how I am performing against the theoretical system. Thus giving me a benchmark range to compare my actual performance against.

I have included the excel spreadsheet at the bottom of the article so that you can run your own stats.

Here is a quick video on how to use the spreadsheet.

Here is a copy of the spreadsheet.


Resources for Building a Trade Journal

Resources for Building a Trade Journal

Last week, I posted an article walking through my trade journal, looking at what stats I track and how I lay it out.

This week I am going to go though some resources that I used to learn excel and build my own journal.

Before we start, one of the questions to ask ourselves is do we really need to build own when there are pretty good commercial alternatives. For example, Edgewonk and Tradervue


Learn Excel.

This will enable us to build custom mini journals to track specific data to answer specific questions that the main commercial journals may not cover.

The process of building the journal and learning the formula gave me a deeper understanding of what the stats are actually showing.

It is free. Yay.


Takes time to learn Excel and build the journal.

This can be done in bite size pieces but it still takes time. Around the beginning of the year, I re wrote my journal to tidy it up, turn the data into tables and re produced the stats pages using slicers.

That took me 2 solid days to reproduce. So it is an endeavour at times, but that may be just me.

As a home trader working alone, I have to be responsible for so many areas, preparation, trading, review, research and analysing.

Then there is the goal setting, the review of the best practices / processes on top of that.

I constantly find that there is so many things to do, that I have to prioritise all the time, just to get some semblance of work / life balance.

The question is, does learning how to build your own trade journal take you closer to your ultimate goal?

Only you can answer that.

If you are not familiar with Edgewonk, one of the commercial trade journals, this is an excellent alternative to building a journal. Version 2 has just come out of beta and I will be running that in parallel and will do a review of this trade journal down the line.

Read my Edgewonk Trade Journal Review

MFE/MAE Tracker

The one thing that Edgewonk doesn’t track that well, at this current time and that could change with Version 2, is the MFE and MAE as a way of optimising targets and stops and an example of my using this data is in my article How I am using my trade journal to improve my targets.

Trade Journal

I have put a quick video tutorial on how to build a basic version of my own MFE / MAE tracker.


Download the Excel file used in the video

Learning Excel to Build a Trade Journal

The first resource I used to build my own trade journal was though a video produced by Adam Grimes in his free trading course.

I recommend the whole course as it has some excellent exercises in it.

Module 3 has the video in it on how to build a trade journal.

Then the following YouTube channels where essential in learning how to write formula’s and how to use pivot tables / slicers.


Excel is Fun

Trade informed

Google Search

The last resource I used is Google Search. If I could not get a formula or logical statement to work, then I would type my question in to Google and preface with excel. That worked well a lot of the time.

Any questions or requests, please drop me a comment below and I will do my best to help.

How I am improving my Play to Win Mindset

How I am improving my Play to Win Mindset

During my break from trading in August, I have been thinking about the whole play to win mindset verses the playing not to lose, especially when it comes to taking trades and setting correct targets.


I have two types of trade, scalps which generally have a target of 5-8 ticks, and intraday swings (IDS) which typically have target of 10-16 ticks.

The problem I have, is that it is a lot easier for me to set the targets for a scalp trade and ignore that on certain trades I should be placing IDS targets.

This is due to habit and fear of losing. I am having problems accepting the risk on the IDS trades which tend to take up to an hour to play out compared to my scalp trades which play out in less than 15mins.

I have clean defined rules which decide which trades are designate an IDS, if it does not fit these rules then it is a scalp trade.

For a while now I have implemented a decision making process, to help me approach problems the same way each time.

It is based on a watered down version of John Boyd’s OODA loop called DADA loop, which stands for Data, Analysis, Decision, and then Act. Then gather more data and continue with loop.

I am going to walk through the problem using my DADA process to decide whether I should stick to just scalp targets or on certain trades aim for the larger targets.

The information generated will in turn be placed in my exit rules, so that before entry I re read these and in turn help me focus on playing the trade in my best interests.

Everything is going to be done without taking in account, commissions and costs.

DADA Process


Whether I should set scalp targets or IDS targets.

NB not randomly but when the setup rules specify IDS or scalp targets.


What is the likely outcome?

Scalps Targets

It is a Win. My current win rate on these trades is 68%. With an average win of 6 ticks.

It is a Loss. My current loss rate on these is 24%. With an average loss of 5 ticks.

It is Breakeven trade. My current breakeven rate on these trade is 8%.

My average reward to risk ratio is 1.2 to 1.

Now for some maths.

For me to be profitable taking trades with a 1.2 reward to 1 risk. I need to win 46% of the trades.

This is worked out using the following formula 1/(1+(R multiple)) therefore 1/(1+(1.2)) = 0.4545

Therefore I need to win a minimum 47% of the trades and my current win rate is 68%. So far so good.

My expectancy is typically worked out as follows

(Average win x Average Win rate) – (Average Loss x Average Loss rate)

(6 x 0.68)-(5 x 0.24)=2.88

One of the problems I have found with the expectancy formula, whilst telling whether my edge is profitable or not, it has little bearing to my real life trading decisions.

So I have decide to change this to try and give me a number that I can relate to.

Instead of using ticks, I will use the value of 1 contract and I will multiple the result by 100 trades. This will tell me the value for the next 100 trades for every contract traded.


1 contract of the Bund is worth 10 euros per tick.

My expectancy is (((6 x 10) x 0.68)-((5 x 10) x 0.24))x100 = 2,880.0 euro

By scalp setups are worth 2880 euros for every contract traded over the next 100 trades.

IDS Targets

It is a Win. My current win rate on these trades is 57%. With an average win of 12 ticks.

It is a Loss. My current loss rate on these is 33%. With an average loss of 7 ticks.

It is Breakeven trade. My current breakeven rate on these trade is 10%.

My average reward to risk ratio is 1.7 to 1.

Now for some maths.

For me to be profitable taking trades with a 1.7 reward to 1 risk.

Again using the following formula 1/(1+(R multiple)) therefore 1/(1+(1.7)) = 0.3704

Therefore I need to win 38% of the trades and my current win rate is 57%. So far so good.

Therefore my expectancy for the IDS

1 contract of the Bund is worth 10 euros per tick.

(((12 x 10) x 0.657)-((7 x 10) x 0.33))x100 = 5,574.0 euros

Data Analysis

Over 100 trades my scalp expectancy is 2880 and IDS expectancy is 5574.

The difference is 5574-2880 = 2694 euros


If I do not take a trade when I should, then I am losing a potential minimum of 2880 euros.

If I place scalp targets when I should be placing IDS targets then I am losing 2694 euros.


So I will take every setup that fits my process / rules and I will always place the correct target structure.

I then can collect more data and then repeat the process using my MFE and MAE to see if a change in targets and stops produces better results.

Of course these calculations are not taking in account my cost per contract, so are not a completely true reflection of the profitability. But the purpose of this exercise is to work though the problem in a logical manner using DADA and then turn the result into something that I can relate to.

It is a matter of re framing the risk acceptance.

My journal tells me that my expectancy is 2.87 and my win rate is 68% but during the trading session I cannot relate to that.

I can relate to

That if I take this scalp setup, I have to win 47% of the next 100 trades to be profitable and if I follow my process over these 100 trades then this is worth 2880 euros.

That if I take an IDS setup, I have to win 38% of the next 100 trades to be profitable and if I follow my process over these 100 trades then this is worth 5574 euros.

The next step is to transfer these figures to my exit cheat sheet. The plan is that when I stalking trades using my process, that the reminder of what a missed trade or incorrect targets means will help me accept the risk of losing 5 or 7 ticks on this individual trade when there is a lot more reward for sticking to the plan for the next 100 trades.

Return of the Stats – Follow up

Last week I posted an article called Playing the Odds – Return of the Stats, which was about the various techniques I was using to improve my use of stats within my trading.

One of the areas, I have worked on, is looking at the various statistics and when they worked / completed and then looking at the how far the maximum adverse exclusion (MAE) was for each instance.  I then compiled these into a sample, where I could then work out the most common (mode) and the Standard Deviation of the MAE. I then used this to help me identify potential areas of entry and defined my risk and reward.

I use RT Investor to calculate these stats and the various MAE results. David asked me to post a one of my charts with the text definition, as he was having struggling to write the code.

I mentioned in the previous article, that I got the idea for this from a webinar that Tom Dante and Hugh did called Playing the Odds.

Whilst I initially said I would post the chart definition, I have realised that each of my charts definitions use the code from one of Hugh’s charts from the webinar. Therefore I do not feel comfortable posting my definitions, as this is a paid webinar and the original code is not mine to give away.

The chart in question is Breakout Failure Part 2

There are a couple of solutions to this

1) Ask Hugh to post the definition for this chart.

2) Buy the Play the Odds webinar. It is 14.99 GBP, for that you will get the webinar and 15 templates that are compatible with MD or RT Investor. Of course if you only want the above chart, then it might sound expensive, but you could look at this way. I had put at least 5 hours in, trying to implement this, before I reverse engineered Hughs code. The question I would ask myself would this amount of money be worth the time saved.

To be totally clear. If you buy this webinar, I receive no monies from Tom or Hugh. If you want to go directly to the site then use Google search and the keywords Tom Dante Playing the odds, it is the 4th entry on the 1st page.

Hugh is much better than me at writing the code, and I would pay 14.99 for a webinar from him, on how to do these sort of charts covering various stats, as I sure that I would learn from that experience, as I have from watching his previous webinars.

But the choice is yours. If anyone has questions on the additions I made to Hugh’s original chart then I will do my best to answer them.

Practical Trading Statistics

Practical Trading Statistics

It is coming to the end of the month; it is time for me to update my Trading Statistics.

I am also using this opportunity to simplify my use of trading statistics. Currently I have the majority of my stats on a cheat sheet for each market I trade.

Below is a part of my current cheat sheet for the Bund Market.

Practical Trading Statistics

The simplify process is going to be in three steps

1) Check each stat on how practical it is to use and whether I use this on a regular basis. On each stat that I do not use regular or is not practical, I will then look at whether I should to do more research to make this practical or should I drop it.

For example

The Open In Range and Breaks the previous day’s High, has a 79% chance of closing above previous day’s vpoc, 71% chance of that days open and a 68% chance of yesterday value high. Whilst this is helpful in determining a direction, it is not that practical to use in determining targets or places to get in and place stops.

I will do more research on this stat to use if I can make it more useful. I will do a study on where the low of the day is after breaking the high. This might make this particular stat more useful.

Any stat that is not practical I will drop.

2) I will drop any stat that is under 70% (or the inverse greater than 30%), I will focus only on the higher probability stats.

3) Chunking

In the Mental Game of Poker 2, there is an interesting section on Chunking

While the size of working memory is limited, “chunking” is a way to get more out of it.

Chunking is when the brain compresses a lot of information into one small piece, kind of like a zip file or a cue card. Chunking can be illustrated in the way football teams name their plays.

Each football team has a unique language for plays that helps them communicate large amounts of data very quickly, for example, “Right Double Gun Montana Screen Left.”

Just these few words allow the quarterback to instantly give detailed instructions to the other 10 offensive players. Pages could be written about each player’s assignment during the play, however, intensive practice and study allows them to recall all of it with just a few words.”

from “The Mental Game of Poker 2: Proven Strategies For Improving Poker Skill, Increasing Mental Endurance, and Playing In The Zone Consistently” by Jared Tendler

I am going to work on improving my cheat sheet so that I can remember the stats easier during the day.

I am going to remove the percentages, I do not need to know the exact percentages, as they can be summarised with words, HP = High Probability and MP = Medium Probability.

And I will look at summarizing the whole stat play in a few words.

One of the things I have done is to have a tool on my charts, where I can draw the bands for standard deviation and 2 standard deviation of the MAE on a breakout and retest of previous day high. This helps me to keep the stat in front of my mind and gives a visual reference to take into account when looking at context and potential trades.

Practical Trading Statistics

I will look at each stat to see if I can visually replicate that stat on the chart rather than just reply on the hypo or mini plan.

This is all part of my process of simplifying my trading without making it too simple.

Improving the use of statistics in my day trading plan

Improving the use of statistics in my day trading plan

A while ago I wrote an article on how I use statistics in my trading. Over time the list of stats I use has grown into a list of 32 items, whilst some can be grouped together, this still was a list of 24 stats to keep an eye and incorporate into my trading.

As I had noticed in a previously in Repeating the Best Practice, the way I calculated my stats has changed over time. I also had noticed that the list of stats had got more complex and I was having trouble including these into my trading plan.

Or to be more precise, I was focusing only on a few stats and not using the others as it was too time consuming and complex.

As part of my Best Practises Manual, I decided to simplify the whole process.

Step 1 – Schedule and Settings

I have written a schedule of when I update these stats and what settings I am using each time. This will introduce some consistency in when and way I calculate the stats.

Step 2 – Make it easy to do

Some of my stats where calculated in Excel and some using the RT Investor Charting Software.

My next step was to convert all my stats in excel to RT Investor. I did this on Thanksgiving whilst the market was quiet, and it took me a good 5 hours but in the future it will save me time and will make it easy to update my list.

Some of the stats charts I downloaded from RT Investor Homework section, I then re purposed these to give me the stats I wanted and some of them I wrote from scratch. I am no expert with the RT Investor RTL, but by examining the downloaded charts I managed to learn enough to write by own stats charts.

My point is that if you are familiar with doing stats on excel, then a bit of time spent looking at Chad charts should give enough information to make your own charts in RT Investor / Market Delta.

I then rename all my charts and remaining excel documents that are stat based with the prefix STATS, thus making these charts and documents easy to find.

Step 3 – Incorporating my stats into my day trading plan

Previously, I would look at the chart, see where price opened or where price is trading and then check my stats document and then write out the relevant stat into my day journal and then incorporate into my intraday plan.

As my list of stats increased, this document expanded and ended up at 3 pages long. The result was I would occasionally miss a relevant stat or on some days, where I would have a few stats in play and I would have trouble incorporating all this information into an intraday plan that dove tailed into my overall daily hypo.

My observation is that if a practice is too complex then the tendency is that either it does not get implemented or not implemented correctly every time. Something has to change if I am to bring consistency to all of my best practises.

Instead of a 3 page document listing all my stats, I reduced this to an one page cheat sheet with only the relevant information in shorthand and divided into sections split between open, high, lows, etc.

I went further and numbered the most important intraday stats, so that I can refer to them by number in my day journal and I will now note whether the stat is positive or negative for the bias.

An example of how I enter this into my day journal.

From this I have found it easier to work these stats into my areas of interest and overall plan.

This has been all updated into my Best Practises Manual, and will be the routine going forward.

Repeating the Best Practise

Repeating the Best Practise

Recently I have been doing some part time consultancy work in my old career. I do this as it fits in around my trading, apart from the odd half day couple of times a month. I enjoy the work and makes me think about my trading from a different perspective.

Recently, we had a performance review of the last race of the current campaign, and it highlighted an area which I think has a cross over with trading.

Whilst the review dealt with the areas they performed well in and areas they needed to improve in, and from that a list of actions was produced to be implemented in the future.

Pretty normal review so far, but what came to my attention was that in a few of the areas they needed to improve upon, they had done better in these areas in past campaigns.

We are what we repeatedly do. Excellence, then, is not an act, but a habit.


So why were they not repeating the good procedures now?

It seemed on further discussion that slowly over time with various team changes and with just the passing of time, that routines that had been habit, had slowly changed or been forgotten without anyone really noticing.

In previous campaigns I had been involved with, I had run an operations manual which listed all the best practises for all the areas under my management. This ensured that everyone followed the correct routine and we did not stray from the path of repeating the methods that resulting in good performance.

How does this relate to my trading?

Well my trading system covering my style, entry, management, risk etc., is well documented and kept regularly up to date.

After this trading weekly review, which highlighted problems due to a lack of focus, I remembered that a couple of years ago, when I moved from trading hourly and daily charts to an intraday style of trading, I had a problem with maintaining and keeping focus, so I had a procedure to get me back into the zone.

Over time as my ability to focus improved, these routines got forgotten as I did not have to rely on these to get into the zone.

Now when they are needed again, I did not need help as I already had a forgotten tool I could use. It was only when writing the review of the week’s trading that I it occurred to me that I had a problem like this in the past and looked up the solution.

In turn this has led me to me thinking about the other areas of my trading, whilst all these areas are done pretty consistently the same way each time they are not documented.

So the question is, whilst I think that these areas are repeated consistently, are they and what other good practises I have lost to time and habit creep?

Have these changes been an improvement or have they been detrimental to my trading?

Without these areas being documented, then I do not know the answer.

For example, I update some of my stats weekly and some monthly, using the same criteria each time.

But now looking back at the stats from a year ago, I collected and updated them on a slightly different time scale and criteria. Why am I doing this differently and was it an improvement? I do not know the answer to these questions.

How many times I have made an error, which I have placed a routine in place, then over time drifted from this routine and then ended up in a similar spot and ended up re-inventing the wheel.

These changes to my routines are in theory, covered by my weekly review in my hand written, and now on line journals, but these improvements are not collected in one place unless it directly relates to my trading system.

Currently it is time consuming to go through these individual reviews to check if I am still implementing the good practises into my trading.

So moving forward I will keep a Best Practises Manual, which I will document my best practises and then using my weekly review to feed into and improve this Manual.

How I am using my trade journal to improve my targets. Part 2

How I am using my trade journal to improve my targets. Part 2

One of the statistics I track is MFE and MAE.

Maximum Favorable Excursion (MFE) –  what was the maximum number of ticks in profit that the trade had before the trade closed.

Maximum Adverse Excursion (MAE) – what was the maximum number of ticks in loss that the trade had before the trade closed.

I use these stats slightly differently. Instead of tracking the MFE and MAE during the duration of the trade, I continue tracking these stats on my trades until they make the next pivot on my trading time frame of 5min.

I do this to track how well I am setting my targets and whether they can be adjusted further away to maximise my profits.

Why do I do it this way?

As my targets tend to be at the next levels on my trading time frame and at my current size I do not leave a runner position on. I found that tracking MFE/MAE during the trade duration was telling me that I was taking the max profit during my trade but not what I was potentially leaving on the table, if I had set my targets further away.

This is last 150 trades on Bund.

Note that on the losers, this is not the draw down of the actual trade but the the numbers of ticks from entry to the next pivot. My stop is 5-8 ticks and I track any violations of that on a different sheet. Which is very rare.

The maximum MFE and MAE is of limited use in my opinion.

More of interest is the the standard deviation and the mode / poc of the MFE and MAE of the winners.

First how far does the trade goes against me?

The mode / poc of the adverse tick movement is 0 and the std deviation of the  adverse movement is 2 ticks.

This tells me that I am choosing setups / entry where price quickly goes in my favour.

It also tells me that if price goes more than 2 ticks against me, then I am either early or the trade is likely to stop out.

How far does price goes in my favor until it makes a pivot on the 5min.

The mode / poc of the positive tick movement is 10 ticks and the std  dev is 12 ticks.

I have used this to choose for my first target a 5min within 10 ticks of my entry and the second target is within 12 ticks.

This information fits in with the stats for a 5 min rotation in the Bund which are 12 ticks mode and 18 ticks standard deviation.

For every 100 trades I re do this calculation to see if my first 2 targets needed to be adjusted.

But when it comes to adding size, the question is for me, do i add a runner or do i just increase size get out at current targets levels.

For this I need more data.

Going forward I am going to be collecting data based off the MFE and MAE on the 15min time frame. Entries are still on the 5min.

I will use the mode and standard deviation of the MFE and MAE of these 15min rotations and compare that to my current targets.

I will use the expectancy formula of (average win x win percentage) – (average loss x loss percentage) to compare increased size at my current targets and stops against targets based on the 15min rotations.

This is the first 26 winners

Okay, a decrease in the mode to 4 ticks and an increase in the standard deviation to 16 ticks. But this is a too small sample size to make any decisions on.

I have also started to track the reactions to levels dependent on how large the rot is on the 5min / 15min and 60min time frames.

Again not enough sample data to make any decisions but initial thoughts are that fading a common 15min rot pullback has more potential room for profit than fading a 15min standard deviation rot.

I also tracking the 15min trend and 60 min trend to see if there is a correlation

Once I have a minimum of 100 trades based on this data, I will analysis this to see how it will effect my expectancy and whether I should alter my targets or have a third target.