Risk Measurement and Portfolio Optimization Based on NASDAQ 100

This paper analyzes the historical data of the NASDAQ 100 stock pool to understand the historical performance of specific stock weights, so as to optimize the investment portfolio and explore optimization methods to better avoid the financial risks brought by market fluctuations. This paper mainly uses mathematical statistics principle and mathematical model to quantify the possibility and influence degree of risk occurrence, and adopts value at risk (VaR), conditional value at risk (CVaR), maximum retracement (MD) and other analysis indicators. This paper will take the top 20 stocks by market capitalization in NASDAQ 100 index as the stock pool to analyze and judge the future return risk of different stock weighted asset portfolios. The ultimate goal of risk analysis is to control risks more effectively. Once risks are identified and quantified, investors can take corresponding risk management measures. Therefore, when calculating the risk of a certain portfolio, this paper will find the corresponding portfolio weight according to different situations, so as to optimize the portfolio. As a result, different optimization methods have made progress in different aspects. Among them, the optimization method of E[X]-CVaR is the best for the stock index, and its optimization results can obtain the maximum return and the future risk is minimal.