Keeping a good trading journalÂ in which all the trades that are executed (along with their results) is fundamental to be able to improve over time.
But much more important than noting the essential data of the various trades executed (market, purchase and sale price, time of purchase and sale, final result …), is to be able to carry out a collection of a series of parallel data to the actual trade taken. Â This will show usÂ what immediate changes can lead to tangible positiveÂ results in our trades.
The backtesting of a system
Usually, to accelerate the implementation of a particular trading system, what is customary to do is an exercise in simulatingÂ how the system in question has behaved in the most recent past.Â For example, in the case of being traded intraday, it would suffice to apply the system during the last 15 days in the market being analyzed.
Indeed, it is not exactly the same as performing a real trade, but it can give us a rough idea of â€‹â€‹whether that system can work in the market in question or not.Â This exercise of applying a system on past price action is known as “backtesting.”
Of course,Â it is not conclusive that a past system will work now, but undoubtedly is a very healthy exercise that certainly will not detract from our trading. And it could even help us to realize details to improve that system in the market that is being analyzed.
Thus, if the trading system that one plans to carry out in real can replicate in a backtesting exercise (or, much better, if the platform allows, in a real-time market replay), I strongly recommend that is made.Â The learning that comes from this work is often very valuable.
Real-time system optimization
But beyond the backtesting, what is really interesting is what I said at the beginning of the entry:Â the analysis of trades at the same time we are taking them.
So that you understood what I mean by this, I always write in my trading journal, among other things, two very simple data that I consider fundamental to improve my trading system constantly:Â the maximum progress against me and maximum progress in favor.
Why?Â Well I think it is easy to understand: the maximum advance against me allows me toÂ adjust the stop loss to my entries.Â That is, if I, by default, execute my trades with a stop loss of $100, and with the analysis of this data I notice that all the positive trades that I have have an advance against me only of $60, I could modify my stop loss to $ 70, for example, thereby reducing my loss on each negative transaction by $30.
It is necessary to take into account, therefore, that all trades that have been positive with a maximum advance between $70 and $100 will become negative trades with this change.
In the case of maximum progress in my favor, it allows me toÂ design exit strategies much more optimizedÂ to reality.Â Why leave a trade with benefit of $100 if by default most positive trades have a maximum advance in my favor of $200?Â If all this information is perfectly accounted for, we can adjust our system to a totally empirical numerical reality.
That is why it is essential to be able to handle with minimal looseness the statistics associated with the interpretation of this data and others much more complex.Â After all,Â trading is closely linked to statistics, and a system is a winner or not depending on the % of positive trades you have and what you earn and lose on positive and negative trades respectively.Â If we are able to play with those numbers in our favor (knowing which ones we need to keep track of), we will be much closer to having consistent positive results.