Estimation of Risk Related to Agricultural Crops Using the Value at Risk (VaR) Approach

The present study was conducted with the objective of estimating the risk related to agricultural crops using the widely used and applied measure of risk, i.e., Value at Risk (VaR). Two major crops of Pakistan (wheat and rice) were used, and the data regarding their weekly wholesale prices were collected from the official website of the Pakistan Bureau of Statistics (PBS). The data spanned from the 1st week of January 2013 to the last week of October 2023, yielding 565 observations. The collected data were analyzed using MATLAB 2022a. We used different MATLAB packages for the analysis. The results showed that both price series follow leptokurtic (heavy-tailed) behavior, indicating that a fat-tailed distribution is needed to estimate the true Value at Risk (VaR) for both crops. Mean returns were positive, indicating prices increased over the period. Wheat and rice returns showed very high volatility and volatility clustering, which can be interpreted as riskiness. The returns deviate from normality due to negative skewness, indicating variability in both; using VaR, we found that Rice is riskier than Wheat. Likewise, the prices were calculated through value at risk, historical value at risk and historical predictable shortfall. This shows that normal-distribution VaR can significantly underestimate historical VaR.