A Quantitative Trading Strategy Based on A Position Management Model

Abstract

With the rapid development of economic globalization, various financial products have appeared in the domestic and foreign financial markets. How to adopt ideal trading strategies to meet the demands of market traders for high returns and low risks has become the focus of investors and the research goal of scholars. In order to solve this problem, this paper establishes a quantitative trading strategy based on the position management model.First, we performed price forecasting for gold and bitcoin based on the Time-series ARIMA method. A differential autoregressive moving average model was developed for the price data of gold and bitcoin at different cycle times, respectively, and used to predict the price of the next trading day. Error analysis was performed with the actual prices, and it was found that the prediction error was the smallest when the data was 60 days, and the relative error of the average prediction value (APV) could be controlled at 0.003016.Then, we establish a quantitative trading strategy based on the position management model. We use the Apriori algorithm of Association rules to study the rising and falling rules of gold and bitcoin assets. According to the rule of " High throw bargain - hunting" in the investment market, we established a position management model and achieved dynamic and stable returns. After the model is established, we continue to introduce the evaluation indexes of the investment value of financial assets, among which the first-class indexes are profitability and safety. We use the Analytic Hierarchy Process (AHP) to determine the weight of each evaluation index, and allocate the daily trading investment through the ratio of two asset evaluation indexes. This quantitative trading strategy, based on the position management model of AHP, can not only stabilize the income but also avoid risks, reaching a quantitative trading strategy with an annualized rate of return of 25%. On September 10th, 2021, the accumulated income could reach 223,640.58 USD.Further, we evaluate the profitability and risk resistance of the strategy using Principal component analysis. Model validation was performed by varying the parameter values and selecting the parameters that yielded a locally optimal solution, which was found to be consistent with our initial parameters and was proof of the optimal solution of the model.Finally, we conducted a sensitivity analysis of the model. The two variable parameters of initial commission fluctuation and investment principal of gold and bitcoin are varied up and down respectively, and the results show that as the initial commission increases or the principal decreases, the number of trades under this strategy gradually decreases and the trading return gradually decreases, and the sensitivity curve shows that the model is sensitive and meets expectations.