In this article, we’re going to cover one of the most important exercises you need to do on a regular basis to hone your skills as a trader. Whether you’re trading a retail strategy or a supply and demand strategy like the Phantom Trading methodology, it’s vital that you collect data on it so that you can enter confidently without hesitation in the live market!
Learn The Basics First & Develop A Clear Trading Plan
First things first, ensure you fully understand the basics of the strategy you’re trading. If you try to dive in after only a couple weeks of watching a forex trading course, don’t expect to be able to collect data effectively, or even properly at all. In fact, skipping this crucial step is going to do you more harm that good in the long run. Make sure you understand your strategy well, even if it means you have to spend 2-4+ months learning the basics.
If you’re a Phantom Trader, that would mean being able to properly mark up market structure, supply and demand zones, and liquiditywithout making mistakes, and it would also mean you have a clear trading plan! That means if you’re trading the 1m, you have a 1m plan with 1m entry models, and if you’re only trading the 15m, you have a 15m plan with 15m entry models!
Develop Entry Models For Yourself
The next step as mentioned in the previous section is to develop entry models that make sense to you. You could either take existing entry models or develop ones for yourself based on trade setups you see in hindsight on the charts. Whatever you decide on, make sure you pick one or the other and stick to it!
One of the best ways to solidify your entry models is to create some entry model diagrams for long and short scenarios, and ideally some entry models for continuations and reversals.
Our only word of caution is to be wary of making your reversal patterns too aggressive.
That being said, the next step is going to help us determine the efficacy of our overall strategy combined with the entry models we’ve just come up with, or the ones that we took from whoever is teaching us.
Remember, if an entry model doesn’t perform to your expectations, you can always cut it out of your trading plan or swap it out for something that you find works better for you and your style of trading. Trading is different for everyone, and what may work for one person, may not work for the next.
Set Up Your Data Collection Tool & Workflow
Next on our list is to figure out a process for collecting and recording data based on the plan and entry models you’ve laid out for yourself to test. This could be as simple as using an excel sheet, a physical notebook, or our favourite tool: notion.so!
The reason we like using notion is because you have the option to create a very robust database based on the criteria and data you want to collect, plus you can even add pictures of your trades in each database entry. The flexibility ultimately makes it a killer tool for this exact use case.
Some of the things we like to collect when doing case studies include the following:
Continuation / Reversal
NET +R
Win/Loss (For tallying strike rate of the data set after building case studies)
Sesson (Asia, London, New York)
Entry Time
Day of The Week
A quick note: remember to keep your database as simple as possible as you don’t want to bog yourself down entering 20 different data points for each trade. Keep it simple!
Alternatively, if you find notion.so too difficult to use, you can always throw everything into a word or google doc with images and text, then tally up the data at the end of your tests.
Start Building Case Studies
Now that everything else is out of the way and sorted, here comes the fun part! You can now actually get to testing. Pull up a chart on Tradingview or the backtesting software of your choice, and start scanning for setups. The whole idea is to reverse engineer the higher-timeframe down to the time-frame where you’re entering, so we highly suggest doing this in hindsight rather than in bar-replay mode.
Either you can batch tasks by looking for trades first, then recording data on them, or look for a trade setup, reverse-engineer it, and record the result and any other data points you have in your database.
It’s important to take your time and not cherry-pick trades just because they work. We suggest including “valid losses” in your case studies because it will help you understand whether or not a certain entry model is going to work in the long run or not.
Review Your Data
Now that you’ve collected your first set of data it’s time to tally up your wins, losses, and net R to get an idea of things like your strike rate and profit factor.
Here is an example from my notion with 40 trades collected:
EXAMPLE ASIA/NY TRADES ONLY STATS
40 Total Trades 18 Wins 22 Losses =45% SR
AVERAGE +R = 2.87 AVERAGE WINNING TRADE = 4.22R AVERAGE LOSING TRADE = -1R
NET+R = 117.63
Profit Factor = (50 x 4.22) / (50 x 1). == 4.22 (@50% WR)
Again, the nice thing about notion is that you can filter based on certain things like setup type or session to see what you should keep and what you should cut out, but this is your opportunity now to improve your trade plan and keep what works well, and shelve what isn’t to really improve your overall trading plan and to help you stick to high probability setups by only using high probability entry models.
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Robert is a funded trader based out of Toronto, Canada, and has been trading currencies, commodities, stocks, and cryptocurrencies for over 7 years. Outside of trading he enjoys producing music, mixed martial arts, and riding his motorcycle in the summer.
