Typically, I do not included trade costs in my initial exploratory work because I want to understand the general properties of a market which is best understood without imposing trade costs. Many times a strategy that shows promise but one that does not overcome trade costs can be improved to overcome those costs– but including the trade costs in the initial work would tend to obscure the strategy completely.
However, more recently I have started to explore an alternative technique where I will include trade costs, primarily when using optimization as way to see different types of market tendencies. This technique can be useful when certain dominant market characteristics, such as mean reversion, may drown out the specific type of characteristics that are being sought, such as a trend or momentum–by purposefully manipulating the trade costs, the optimizer can be coerced into discovering different types of market patterns and tendencies with different qualities.
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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