Trading Strategy Formulation Based on the Dynamic Linear Programming Model

Jiachen Yang ； Lei Huang ； Weihan Li

《World Scientific Research Journal》 8卷7期 (2022/07) Pp. 10-18

https://doi.org/10.6911/WSRJ.202207_8(7).0002

摘要

The word ＂buying and selling＂ can be traced back to primitive human society. At all times, people want to maximize returns. This paper mainly predicts the price of gold and bitcoin by establishing a mathematical model and formulating a trading strategy to maximize profits. The research on this issue can guide for investors to maximize benefits and minimize risks. Based only on price data of gold and bitcoin up to that day, the paper is asked to determine the trading strategy for maximizing returns. Essentially, this is a single‐objective multi‐variable programming problem with the dynamic linear restrict condition. First, we use a Time Sequence Model to predict the missing price. Then, the risk score was obtained by the Entropy Weight Method and the TOPSIS model. Finally, we use the Dynamic Linear Programming Model to simulate the trading strategy. Among them, we performed a Double Sample Z‐Test on the data, which was obtained under different constraints, and the original data to judge the validity of the model. Upon examination, we learned that the model is effective and optimized by nearly 30% compared with the planning results under other conditions. What's more, we conduct Sensitivity Analysis on the model of TaskⅠ In this paper, the transaction cost ratio R of gold and bitcoin is changed to 5%: 1%, 2%: 1%, 1%: 1%, and 1%: 5% respectively, and detailed analysis is conducted. When the transaction cost in the model changes, the final asset changes are 90.53%, 115.35%, 98.73%, and 113.90%. Therefore, the final asset value obtained by this model is relatively insensitive to the change of transaction cost. Last but not least, we conclude the results of our model.

關鍵字

Time Sequence Model ； Dynamic Linear Programming Model ； Double Sample Z‐Test ； Trading Strategy Formulation Model ； Sensitivity Analysis

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