Optimal Transaction Filters Under Transitory Trading Opportunities: Theory and Empirical Illustration
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abstract
If transitory profitable trading opportunities exist, filter rules are used to mitigate transaction costs. We
use a dynamic programming framework to design an optimal filter which maximizes after-cost expected
returns. The filter size depends crucially on the degree of persistence of trading opportunities, transaction
cost, and standard deviation of shocks. Applying our theory to daily dollar-yen exchange trading, we
find that the optimal filter can be economically significantly different from a naive filter equal to the
transaction cost. The candidate trading strategies generate positive returns that disappear after
accounting for transaction costs. However, when the optimal filter is used, returns after costs remain
positive and are higher than for naive filters.