A value at risk (VaR) measure/ method that only uses two main variables or parameters as inputs: the mean and standard deviation of a portfolio. Additionally, the principal assumption that underlies calculation is that the portfolio’s returns are normally distributed (that is, follow normal distribution). The calculated standard deviation is used to derive a standard normal z score to size up the position with a confidence degree/ confidence level (according to a pre-determined table).
The normal distribution is used as a proxy for expected returns (return normality). Furthermore, the returns are premised to be serially independent: no prior return influences the return that is generated thereafter.
For example, if the two parameters for a portfolio were determined to be:
- Standard deviation (in monetary terms): CU 100,000
- Mean (in monetary terms): CU 40,000
- Z Score for 95% confidence: 1.5
Assuming confidence was set at 95%, parametric VaR for the period is calculated as follows:
40,000 – 100,000 (1.5) = CU -110,000
This measure of VaR is also known as a variance/ covariance value at risk (variance/ covariance VaR).
Hello, would you please explain where 40,000 come from in the equation above?
Hello, Adam. It represents the mean as given in the above example.