I wanted to introduce the idea for a metric that may be useful for discretionary traders, and yes, even system traders. The idea stems from this idea that markets make transitional moves that can be captured in real-time and jumps which can only be captured if positioned in advance. The percentage of moves that occur from jumps versus slower progressions can be viewed as a measure of market efficiency.
Let’s step back for a moment, a common question for futures day traders is what instruments should one focus on? One way to look at it is by looking at the average dollar range for the instrument which is point value times the average daily range. However, if most of those moves are the result of “jumps” that cannot be captured then it may suggest a lower theoretical profit potential.
The next question is what do we consider a jump vs a progression? There are a lot of possibilities. The idea of a jump is obviously a fast movement but also a large movement. Jumps are, also, relevant for market timing on a longer time scales. The measure of jumps to transitions can also be used to evaluate whether or not a quantitative edge or system is more or less likely to be improved with discretion. Systems that profit more from jumps have lower potential to be improved via discretion. Again, how we measure jumps is I think subjective because it depends on our ability to react. However, one measure might be some standardized unit of volatility or market movement exceeding a threshold in time or price. Alternatively we might only want to look at movements that extend ranges. Of course, one can take this idea and play with it, one might want to look at the possibility of adverse jumps.
Now, to be honest, a discretionary trade can also trade for jumps and probably there is some need to capture jumps inherent for most traders. But, I still think there may be value in this idea especially in terms of thinking about movements that are too fast to take advantage of. In addition, if a trader or system is trading for jumps versus transitions then one will probably need to take a greater risk.
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.
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