Value at Risk
An estimate of the maximum loss that will not be exceeded with a given probability over a set period.
Value at Risk is a way of expressing a portfolio's risk as a single money figure: how much can be lost over a chosen period such that a deeper drawdown remains a rare outcome. The estimate always comes with two parameters, without which it cannot be read: the horizon (a day, a week, a month) and the confidence level. One and the same portfolio produces different VaR figures at a daily and a monthly horizon, so only estimates set up in the same way can be compared.
Where the number comes from
VaR is calculated in several ways. The historical method takes the actual daily changes in the portfolio's value over a past period, ranks them from worst to best and cuts off the tail at the given probability — the cut-off point is the estimate. The parametric method assumes that returns are normally distributed and derives the answer from the portfolio's volatility multiplied by the confidence-level coefficient. The Monte Carlo method simulates a large number of scenarios from given parameters and looks at the tail of the resulting distribution. For a portfolio of several securities, correlation plays the decisive role: as long as the assets do not move in step, the combined VaR is smaller than the sum of the individual ones, and it is exactly this difference that puts a number on the effect delivered by diversification.
An example using the platform's data
Historical VaR for a position in a single security is built directly from its series of daily changes — the very one shown on the one-year chart:
We take the daily changes over the year, sort them, cut off the worst tail and convert the relative change at the boundary into roubles at the current value of the position. The resulting amount is the daily VaR at the chosen confidence level.
Where VaR is misunderstood
The first mistake is to treat VaR as a property of the security rather than of the position. It is a money amount: it grows with the size of the investment and rises sharply when leverage is used, even though the asset itself does not change.
The second is the unspoken assumption that the position can be closed at the market price within the calculation horizon. For illiquid securities this is not true: the actual time needed to exit is set by the liquidity horizon, and when the calculation horizon is shorter than that, the estimate refers to a period within which the position could not be sold.
The third is trusting the model in a regime that was not in the sample. Historical VaR knows nothing of events that fell outside the calculation window, while parametric VaR understates the tail, because real return distributions have heavier tails than the normal one. This is precisely model risk: the error comes not from the market but from the assumptions of the calculation.