The Value at Risk (VAR) reports the maximum loss for an investment over a given time period.
Measurement of ‘worst case’ scenario downside risk to an investment or portfolio based on expected volatility.
In other words, it can estimate how much of your investment you might lose (with a given probability), at given normal market conditions, over a given period based on the probability of past performance.
Given portfolio value
Time horizon (days)
Value at risk
This calculator lets you set the amount of your position, its periodic volatility as well as the confidence level (a value between 90% and 99.9%). Once you have set your parameters, click the 'Calculate' button to get your VaR number.
Disclaimer: Please note that this result is theoretical only and is based on the normal distribution of returns assumption.
Given Portfolio Value: The new investment you want to make
Expected Volatility (Standard Deviation): Includes the variance-covariance method It assumes a normal distribution in returns or expected return
Confidence Level: Also called ‘periodic volatility’.
Time Horizon (Days): The square root of the given period over how many trading days are there in a year
Result: Future value of risk, informational purposes, estimate
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On the pros side, the VaR measurement is widely used by many financial industry professionals and, as a measurement, it is easy to understand. By any means, VaR offers clarity.
VaR can tell us things like with 99% certainty, losses will not exceed X, however, it can tell you nothing about what happens beyond that confidence level (losses can be much larger).
There are a few pros and cons to using Value at Risk calculation in risk measurement. The model is developed to work this way because the probabilities in VaR are based on a normal distribution of returns. But, we need to have in mind that financial markets are known to have extreme outlier events on a regular basis— far more than a would predict.
Finally, the VaR calculation requires several statistical measurements such as variance, covariance, and standard deviation. With a two-asset simple portfolio, this is relatively straightforward, but the complexity increases exponentially for a highly diversified portfolio with many instruments.
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