Abstract
An investment method based on traditional subjective judgments faces huge challenges, while the strategy of quantitative investment is to find the optimal alpha model to judge the best timing of selling and buying and designing the most effective investment portfolio. Therefore, compared with traditional investment methods, quantitative investment breaks through the limitations of subjective judgment with its qualitative and quantitative advantages. The futures market attracts many investors with its low transaction costs and the two-way nature of transactions. However, most of the investment strategies that are frequently used in the market have low stability and do not guarantee correlation with the general market trend. This makes the investments risky, particularly for individual investors. Therefore, this paper will explore both futures investment and risk hedging strategies, aiming to ensure that every buy and sell is the correct choice as much as possible, such that futures investment is relatively stable and has high returns. This article focuses on using the moving average cross strategy through the python programming language to achieve the judgment of buying and selling in the process of futures trading and drawing the net worth curve of the real-time futures market data and perform a correlation analysis to determine which commodity sector is the most suitable using the trend strategy. For risk hedging, the article mainly uses the correlation analysis to study the relation between the prices of different types of futures. Furthermore, the futures and options market price fluctuations are discussed in depth, and also analysed is how to use and balance hedge parameters for risk hedging.
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More From: Advances in Economics, Management and Political Sciences
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