Research On Optimization Of Foreign Exchange Quantitative Trading Strategy Based On Combination Of Technical Analysis Indicators

Quantitative transactions originated in the United States in the 1970s.After long-term development,the theory and technology of quantitative trading have matured and have been widely used in financial transactions.At present,there are many researches on quantitative trading strategies based on technical indicators using quantitative trading platform,but there are few researches on quantitative trading strategy optimization,and there is no perfect quantitative trading construction and optimization system.Under normal circumstances,the technical indicators under the default parameters quantify the performance of the trading strategy,and it is difficult to adapt to the market trend of different markets and different time.The quantitative trading strategy can be adapted to the market trend of specific trading varieties and improve profitability through parameter optimization-With the deepening of investors'research on quantitative trading,the optimization of quantitative trading strategies will become an important research direction in the field of quantitative trading.This paper designs and constructs two single-index quantitative trading strategies and two-index combined trading strategies for MACD indicators and RSI indicators in the MetaTrader5 quantitative trading platform,selects the historical trading data of the euro against the US dollar,and conducts backtesting tests on the three quantitative trading strategies.verify the trading performance of the three quantitative trading strategies under the default parameters.On the basis of the backtesting test,the genetic algorithm is used to optimize the parameters of the three quantitative trading strategies,and the calculated optimization parameters are tested in the sample data and the data outside the sample.According to the performance of the two tests,three are selected.The optimal optimization parameters for the strategy.Finally,the three quantitative trading strategies using the best optimization parameters are simulated and tested to verify the profitability and stability of the data outside the sample.This paper draws the following conclusions through research:First,it can achieve profitability in the foreign exchange market by constructing a quantitative trading strategy based on technical indicators.The technical index combination quantitative trading strategy has better profit and risk than single-index quantitative trading strategy,which performed.Secondly,the genetic algorithm can be used to optimize the parameters of the quantitative trading strategy,and the profitability and risk level of the technical index can be improved.The technical indicator combination strategy has better performance than the single-index strategy,and has more optimization space..Third,through the intra-sample data backtest and the out-of-sample data test,the optimal parameters of the quantitative trading strategy screened by the two tests can effectively avoid the over-fitting with historical data,and make the quantitative trading strategy stable in the sample data.Can be applied to real trading.