Trading signals based on Fisher transform for algorithmic trading

Abstract

Trading and investment on financial markets are common activities today. A very high number of investors, companies, public or private funds are buying and selling every day with a single purpose: the profit. The common questions for any market participant are: when to buy, when to sell and when is better to stay away from the market risk. In order to answer all these questions, many trading strategies are used to establish the best moments to entry or to exit the trades. Due to the large price volatility, a significant part of the trades are made automatically today by computers using algorithmic trading procedures. For this particular field, special aspects must be met in order to automate the trading process. On this paper it will be presented one of these mathematical models used in automated trading systems, a method based on the price Fisher transform. It will be presented a general form of this method, the functional parameters and the way to optimize them in order to reduce the risk. It will be also revealed a method to build reliable trading signals with the Fischer function. Three different trading signal types will be explained together with the significance of the functional parameters in the price field. A code sample will be included in this paper to prove the simplicity of this method. Real results obtained with the Fisher trading signals will be also presented, compared and analyzed in order to show how this method can be implemented in algorithmic trading.