Risk Calculations

Introduction
Risk calculations are a fundamental component of PRIIPs KID production, providing investors with insights into the potential risks associated with their investments. This blog will delve into the methodologies and data points used in calculating the Summary Risk Indicator (SRI).

Risk calculations for PRIIPs involve several preparatory steps and metrics, including:

Value at Risk (VaR)
The VaR Return Space is calculated using the Cornish-Fisher expansion, which adjusts for skewness and kurtosis in the return distribution. The VaR provides an estimate of the maximum loss that could be incurred over a specified holding period with a given level of confidence.

VaR-Equivalent Volatility (VEV)

The VEV is an important metric in the risk calculation process, as it forms the basis of the Market Risk Measure (MRM). The VEV is calculated using following formula:

Market Risk Measure (MRM)
The MRM is derived from the VEV and used to determine the MRM class. The MRM class is mapped based on the VEV value, and the most frequent MRM value over a period of four months becomes the overall MRM. The MRM class ranges from 1 to 7, with higher values indicating higher risk. The MRM class is a key input in the calculation of the Summary Risk Indicator (SRI).

Summary Risk Indicator (SRI)
The SRI ranges from 1 to 7 and combines the MRM and Credit Risk Measure (CRM) to provide a comprehensive risk assessment. The SRI is visualized in a standardized format on the PRIIPs document, helping investors understand the risk profile of their investments. The regulation allows a product manufacturer to increase the SRI if deemed too low, but it cannot be reduced. The SRI provides a clear and concise summary of the product's risk, making it easier for investors to compare different products.

Preparatory Calculations
Several statistical measures are calculated as part of the preparatory steps, including:

• Mean: The average of all observed returns in the price history. The mean return provides a measure of the central tendency of the returns.
• Standard Deviation (σ): The square root of the second moment. The standard deviation measures the dispersion of returns around the mean, providing an indication of the volatility of the product.
• Skewness (μ1): The third moment divided by the standard deviation raised to the power of 3. Skewness measures the asymmetry of the return distribution, indicating whether the returns are more likely to be above or below the mean.
• Excess Kurtosis (μ2): The fourth moment divided by the standard deviation raised to the power of 4, minus 3. Excess kurtosis measures the "tailedness" of the return distribution, indicating the likelihood of extreme returns.