Research On Quantitative Trading Strategy Based On COT

Quantitative trading originated in the United States in the 1970 s.After more than40 years of development,the theory and technology of quantitative trading has gradually matured and its application in financial markets has become more extensive.The current mainstream quantitative trading models at home and abroad are mainly based on historical price data and trading volume data,and the trading volume data does not include trading objects.This article starts from the trader’s position report COT(Commitment of Traders),studies the relationship between futures prices and COT data,and then obtains a COT-based quantitative trading model.The improvement of the model is a supplement to the traditional model,which has the development of quantitative trading.Certain theoretical significance.This article builds a COT quantitative trading model through the MetaTrader4 quantitative trading platform.First,it uses the COT sentiment indicators to construct a preliminary COT quantitative trading strategy.It selects gold,silver,crude oil,natural gas,raw sugar,corn,soybeans,cocoa,coffee,and cotton.Commodities with active market transactions perform backtesting on the quantitative trading model to verify the performance of the quantitative model under different parameter combinations.Secondly,the COT sentiment index and the MACD technical indicators are combined to optimize the COT quantitative trading model,and the genetic algorithm is used to find the best MACD parameter combination.After the optimization,the COT quantitative trading model is tested out of samples,and the test results are evaluated in both revenue and risk.This paper finally draws the following conclusions through research andempirical research: First,the commercial net position in commodity COT positions is most closely related to price,and the effect of COT sentiment indicators constructed by price sentiment indicators is better.Second,the quantitative trading model constructed by the separate COT sentiment indicators achieves an annualized positive return of 20.55%,but the risk control needs to be optimized and improved.Third,the test effect of the quantitative trading model combining the COT sentiment index and the MACD technical indicator is better.The optimized COT quantitative trading model in the out-of-sample test has higher returns,smaller maximum drawdowns,more stable net value curves,and annualized returns The rate increased from 20.55%to 28.54%,the maximum drawdown was reduced from 9.21% to 4.86%,and the Sharpe ratio increased from 0.48 to 0.76.The research of COT quantitative trading model hopes to provide reference for investors and hedgers,and contribute to the development of quantitative trading theory and practice.