"云计算风险价值度计算方法与实证研究：VaR方法及实证分析"

he relationship between risk and return is closely linked, and it is an important consideration for every investor. There are many methods for measuring risk, but Value at Risk (VaR) is currently the most popular and effective risk management technique in the market. This paper focuses on risk value, introducing the background and significance of VaR, as well as detailing several commonly used calculation methods: historical simulation, parametric method, and Monte Carlo simulation. These methods are thoroughly studied, exploring their calculation steps and respective advantages and disadvantages. While VaR has many advantages, each method still has its shortcomings and requires continuous improvement and innovation. Using soybean and wheat commodity futures as examples, this paper conducts empirical analysis on the three methods mentioned above. By comparing the expected VaR values with the actual profit and loss values, the strengths and weaknesses of these methods are effectively demonstrated. Additionally, improvements are made to the historical simulation method, introducing the concept of Conditional VaR (C-VaR), which has practical guidance in real-world applications. Overall, this research provides valuable insights into risk value measurement techniques in the financial industry, shedding light on the importance of VaR and its various calculation methods. By understanding and utilizing these techniques effectively, investors can better manage and mitigate potential risks in their investment portfolios. Keywords: risk value, historical simulation, Monte Carlo simulation, volatility, C-VaR