Construction of Financial Investment Risk Measurement Model Based on Big Data

Abstract

AbstractThe emergence of big data (BD) has made the traditional financial industry taking a big step towards the intelligent era. The introduction of BD technology in the financial sector has further promoted the transformation of traditional financial services and the innovation of financial business models. The correct analysis of investment portfolio risk measurement and financial risk control are essential for stabilizing the financial order. The purpose of this paper is to study the construction of a financial market security investment risk measurement model based on BD. According to investors’ different understandings of risks, this article provides a securities investment optimization model that is more in line with investor psychology, and illustrates the effectiveness, feasibility and practicality of the established models and methods through investment examples, so that securities Investment is more flexible and closer to reality. This paper uses the application of CVaR risk measurement model in investment portfolios. It is recommended to use CVaR instead of variance to define the average CVaR optimization model of asset portfolio under normal circumstances. On the basis of this model, this paper uses the two-chapter separation theorem, comparing it with the average variance models. Experiments show that in minCVaR (0.99), the average CVaR is 0.12575, and the average CVaR model is better than the mean deviation model, which can reflect the market trend and guide it.KeywordsBig dataFinancial marketPortfolio investmentRisk measurement model