Abstract
Methods of path integrals are used to develop multi-factor probabilities of bid-ask variables to be used in high-frequency trading (HFT). Adaptive Simulated Annealing (ASA) is used to fit the nonlinear forms, so developed to a day of BitMEX tick data. Maxima algebraic code is used to develop the path integral codes into C codes, and a sampling code is used for the fitting process. After these fits, the resultant C code is very fast and useful for forecasting upcoming ‘ask’, bid, midprice, etc., when narrow and wide windows of incoming data are used. A bonus is the availability of canonical momenta indicators (CMI) useful to forecast direction and strengths of these variables.
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