Experiments on stock trading via feedback control

This paper analyzes the predictivity and return of the Barmish-Iwarere trading algorithm described in. In the first part of the paper, we study the trade triggering algorithm using either an Ito process model, or real data from indexes and ETFs. It is shown through hypothesis testing that the trigger provides mixed results in predicting the sign of the single trade, for both the Ito process and real indexes. However, we show empirically the trigger is sufficiently good in identifying a trend, while it fails in detecting side movements. In the second part of the paper, the effect of parameters of the feedback controller will be analyzed under various market circumstances, the efficiency of a pre-optimization on the last data will appear controversal. Some changes will be tried with the objective of improving the returns. In particular, the trigger is modified to detect anomalous falls during a rising trend using the estimated volatility.