In todays video we learn how to calculate VaR or Value at Risk.
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What is VAR?
The most popular and traditional measure of risk is volatility. The main problem with volatility, however, is that it does not care about the direction of an investment's movement: a stock can be volatile because it suddenly jumps higher. Of course, investors do not get upset about gains. For investors, risk is about losing money, and VAR is based on that idea. By assuming investors care about the odds of a really big loss, VAR answers the question, “How much might I lose in a normal bad day?" and “How much could I lose in a really bad day?"
Now let's get specific. A VAR statistic has three components: a time period, a confidence level and a loss amount (or loss percentage).
You can see how the "VAR question" has three elements: a relatively high level of confidence (typically either 95% or 99%), a time period (a day, a month or a year) and an estimate of investment loss (expressed either in dollar or percentage terms).
There are three methods of calculating VAR: the historical method, the variance-covariance method also known as the model approach) and the Monte Carlo simulation. I have covered Monte Carlo in a separate video. In this video we look at the Historical method and the model approach.
What is the Historical method for calculating Value at Risk?
The historical method simply re-organizes actual historical returns, putting them in order from worst to best. It then assumes that history will repeat itself, from a risk perspective.
What is the Variance-Covariance Method or the model approach for calculating Value at Risk?
This method assumes that stock returns are normally distributed. In other words, it requires that we estimate only two factors - an expected (or average) return and a standard deviation - which allow us to plot a normal distribution curve. The idea behind the variance-covariance is similar to the ideas behind the historical method - except that we use the familiar curve instead of actual data. The advantage of the normal curve is that we automatically know where the worst 5% and 1% lie on the curve. They are a function of our desired confidence and the standard deviation
What is the Monte Carlo Simulation approach to calculating Value at Risk?
The third method involves developing a model for future stock price returns and running multiple hypothetical trials through the model. A Monte Carlo simulation refers to any method that randomly generates trials, but by itself does not tell us anything about the underlying methodology. I have created a separate video on that topic which you can find here. [ Ссылка ]
