What are the applications of big data technology in quantitative trading?

Investment decision-making, risk management and other scenarios, reshaping traditional financial services and other aspects have applications.

With the widespread popularity and maturity of big data technology, the application of financial big data has become a hot trend in the industry in terms of transaction fraud identification, precision marketing, black product prevention, consumer credit and credit risk assessment.

Supply chain finance, stock market forecast, stock price forecast, intelligent investment, insurance fraud identification, risk pricing and other specific businesses involving banks, securities, insurance and other fields have been widely used. The application analysis ability of big data is becoming the core competitive factor for the future development of financial institutions.

Stock market forecast:

Big data can effectively broaden the dimensions of securities companies' quantitative investment data and help them understand market conditions more accurately. With the wide application of big data, the explosive growth of data scale and the remarkable improvement of data analysis and processing ability, quantitative investment will acquire broader data resources, build more quantitative factors and improve the investment and research mode.

Securities companies use big data to continuously track and monitor a large number of individual investor samples, and make statistics and weighted summary of a series of indicators such as return on investment, position rate and capital flow.

Understand the changes of individual investors' trading behavior, the state and development trend of investment confidence, market expectations and current risk preferences. , and forecast the market situation.