Some system traders still think that they are merely reacting to markets and that they don’t predict markets. In reality, what they really believe is that they cannot predict markets better then their systems. But, there is a strong hint to determine whether or not a system developer truly believes that they don’t predict markets.
Let’s imagine, I flip a fair coin and have a certain betting strategy that I will use. Because I know I’m not predicting anything then I will never change my betting strategy no matter how many losses I incur. And, this is where the hint comes in: if a system developer truly believes they do not predict markets then they would not apply any sort of equity curve control process.
As most system developers will apply some sort of equity curve control then in essence they are predicting markets. Remember, I stated that predicting markets provided a loophole around the theory of efficient markets because it allows for profiting non systematically. In other words, it is more likely that I can profit from trends some of the time then trying to trade every single trend. System developers who can identify more quickly the types of systems that are working in today’s markets, deploy them, and shut them off before they give back all their profits are, also, in a similar way able to exploit a loophole in efficient markets. Because whatever they are doing is not long term consistently profitable then they are taking some unknown measure of risk to achieve the super normal return. The difference is the execution is purely defined and statistical. There need be no “feeling” of prediction. There is only one type of prediction allowed: a prediction based on the past.
In any regards, regardless of how one feels about it: your profits are going to be the function of your accuracy in predicting markets. Are there any exceptions? There are, of course, always a couple exceptions: automated traders who profit primarily from the spread or those trading arbitrage opportunities can profit and do not need to predict the market. However, systematic traders, directional traders, and even many sorts of options strategies need to predict some aspect of the market better then chance to make a profit, and that could be direction, expectation, winning percentage, or some aspect of volatility.
Curtis is passionate about markets. He has developed top ranked futures strategies. His core focus is (1) applying machine learning and developing systematic strategies, and (2) solving the toughest problems of discretionary trading by applying quantitative tools, machine learning, and performance discipline. You can contact him at email@example.com.
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