Zero-Inflated Hidden Markov Models and Optimal Trading Strategies in High-Frequency Foreign Exchange Trading
Abstract: The properties of high-frequency foreign exchange markets and how well they can be modeled using Hidden Markov Models will be studied in this thesis. Specifically, a Zero-inflated Poisson HMM will be implemented and evaluated for high-frequency price data for the EURSEK exchange rate. Furthermore, a trading strategy aimed at distributing large volumes optimally is developed and evaluated. The results show that the price model performs better than a random walk for some prediction horizons, both when used as a price predictor and as a classifier. The initial tests of the strategy indicate that it has good performance compared to the market benchmark. Both the price model and the strategy needs to undergo more testing before any final conclusions can be made.
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