The Application of Big Data Analytics to Stock and Derivatives Trading Strategies

Authors

  • Yilin Fu Brandeis International Business School, Brandeis University, Waltham, Massachusetts, 02453, USA Author

DOI:

https://doi.org/10.71222/k5gw0z43

Keywords:

big data analysis, stock trading, derivatives trading, market forecast, risk management

Abstract

Big data analysis technology has gradually become a key trend in the development of the financial industry in improving trading strategies of stocks and their derivatives. Through the collection and in-depth analysis of a large amount of market information, investors can extract key intelligence, so as to optimize their trading choices and enhance the implementation efficiency of trading strategies. This paper explains the basic theory of price formation and risk management in the stock and derivative markets, and then analyzes the diversified application of big data technology in stock trading strategies, such as market prediction, stock screening, risk early warning model construction and quantitative trading practices. Then it discusses the specific role of big data in the field of derivatives trading, focusing on its application in the optimization of derivatives pricing model, market risk management, arbitrage strategy formulation and market trend prediction.

References

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Published

24 May 2025

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Section

Article

How to Cite

Fu, Y. (2025). The Application of Big Data Analytics to Stock and Derivatives Trading Strategies. Economics and Management Innovation, 2(3), 21-27. https://doi.org/10.71222/k5gw0z43