Algo-Trading Strategy for IntraweekForeign Exchange Speculation Based on RandomForest and Probit Regression

In the Forex market, the price of the currencies increases and decreases rapidly based on many economic and political factors suchas commercial balance, the growth index, the inflation rate, and the employment indicators. Having a good strategy to buy and sell can make a profit from the above changes. A successful strategy in Forex should take into consideration the relation betweenbenefits and risks. In this work, we propose an intraweek foreign exchange speculation strategy for currency markets based on acombination of technical indicators. This system has a two-level decision and is composed of the Probit regression model and rulesdiscovery using Random Forest. There are two minimum requirements for a trading strategy: a rule to enter the market and a rule to exit it. Our proposed system, to enter the currency market, should validate two conditions. First, it should validate Random For estaccess rules over the following week while in the second one the predicted value of the next day using Probit should be positive.To exit the currency market just one negative warning from Probit or Random Forest is enough. This system was used to developdynamic portfolio trading systems. The profitability of the model was examined for USD/(EUR, JYN, BRP) variation within the period from January 2014 to January 2016. The proposed system allows improving the prediction accuracy. This indicates a good prediction of the behavior market and it helps to identify the good times to enter it or to leave it.