The Long Range Indicator. A Look at Trading Market Extremes.
By: Sofien Kaabar
Tags: Trading, Finance, Machine Learning, Data Science, Artificial Intelligence

Does Simplicity Still Work?

If you regularly follow my articles, you will find that many of the indicators I develop have a high hit ratio and on average are profitable. This is mostly due to the risk management method I use. But what about market randomness and the fact that many underperformers blaming Technical Analysis for their failure?

First of all, I constantly publish my trading logs on Twitter before initiation and after initiation to show the results. This ensures transparency. I also publish a track record on Twitter every 1–3 months. However, I never guarantee a return nor superior skill whatsoever. As for the indicators that I develop, I constantly use them in my personal trading. Hence, I have no motive to publish biased research. My goal is to share back what I have learnt in the online community.

Remember to always do your back-tests. Even though I supply the indicator’s function (as opposed to just bloat about it and say it is the holy grail and its function is a secret), you should always believe that other people are wrong. My indicators and style of trading works for me but maybe not for everybody. I rely on this rule:

The market price cannot be predicted or is very hard to be predicted more than 50% of the time. But market reactions can fairly be predicted.

What the above quote means is that we can form a small zone around an area and say with some degree of confidence that the market price will show a reaction around that area. But we cannot really say that it will go down 4% from there, then test it again, and breakout on the third attempt. The error term becomes exponentially higher because we are predicting over predictions.

While we are discussing this topic, I should point out a few things about my back-tests and articles:

The spread I use is based on institutional quotes of a small pip fraction. Generally, retail traders are given a whopping spread of 1–2 pips per trade. This is huge. I use 0.2 spread. However, most of the strategies that use the hourly time frame still work with 1 pip spread. For the ones that use M15 or M5 time frames, they cannot be profitable with a spread of 1 pip.

The holding period calculation I use is close to close in case there is no risk management process.

The risk management process I use is all about the Average True Range. I specifically mention that the technique I use is suboptimal because it forces a theoretical 0.25 risk-reward ratio meaning that I risk 4 monetary units to gain 1 monetary unit. The majority of the strategies I publish outperform this way. Some are still profitable.

Although I discourage trading based on just one indicator, the numbers do not lie. What I am presenting is what could have happened when taking into account a low spread.

Some of the back-tests I provide are losers and they are published either to demystify a trading myth or to present interesting functions to be coded by readers.

Finally, I am a firm believer of not spoon-feeding the learners. I have learnt by doing and not by copying. You should get the idea, the function, the intuition, the conditions of the strategy, and then elaborate (an even better) one yourself so that you back-test it and improve it before deciding to take it live or to eliminate it.

To sum up, are the strategies I provide realistic? Yes, but with optimizing the environment (robust algorithm, low costs, honest broker, risk management). Are the strategies provided for the sole use of trading? No, it is to stimulate brainstorming and getting more trading ideas as we are all sick of hearing about an oversold RSI as a reason to go short.