School of StatPro: five things everyone should understand about Value at Risk

Date: January 5, 2017

School of Statpro

“In a world that is changing really quickly, the only strategy that is guaranteed to fail is not taking risks.” Mark Zuckerberg

“Risk comes from not knowing what you’re doing.”
Warren Buffett

What does risk really mean? Often, in investment, when we use the term “risk”, what we really mean is volatility – that is, the potential for the value of an investment to fluctuate, whether up or down. As we start 2017, the potential for volatility this year is very real.

But for many investors, volatility isn’t their primary concern – they are more worried about the potential for them to lose money on a particular asset or portfolio. Value at Risk (VaR) addresses that anxiety and calculating it can therefore be a useful risk management exercise. Here are five things you should know about VaR:

1. Can Value at Risk address the question of “How much could I lose?”

VaR is a statistical measure that helps investors understand how much they could lose on an investment or portfolio of investments. It measures three variables: the level of potential loss, the probability of that amount of loss, and the timeframe. So, for example, an asset manager might determine that on a particular portfolio, there is a one day Value at Risk of 2.5% of the portfolio with a 99% confidence level. Importantly, this means that the asset manager can expect to lose more than 2.5% in one day in a hundred. VaR does not quantify the maximum possible loss, but it does give asset managers a way to measure the risks they are taking over a specific time frame – and to adjust their portfolios accordingly, if required.


Alongside VaR, a historical risk simulation model can produce an expected set of returns for the portfolio and show the bell curve of likely returns. This can show the outliers of maximum potential loss (and gain) over a specific time period.

2. Looking closer and comparing to benchmark

In practice, few investment portfolios remain the same over an extended period. But as asset managers ponder the merits of adding additional investments to their portfolios, or selling existing holdings, they need to understand what consequences such actions might have for risk.

Being able to see the drivers of risk within the portfolio is very useful in these decisions. Drilling down to security level VaR quickly allows you to see the top drivers of risk and being able to see this at sector level is also valuable. Reducing levels of risk doesn’t necessarily mean selling out of the market to cash. Analysis can show how selling out of one sector and buying into another can have an impact on the overall portfolio VaR.

Relative VaR shows the portfolio level VaR in relation to its benchmark. This is very useful in showing how an investment strategy is managing risk as well as returns versus a benchmark. Combining all these measure of VaR allows an asset manager to see the overall picture of Value at Risk but also allows security level details to help with investment decisions and relative VaR to show management against a benchmark.

3. Value at risk is an important measure in the UCITS regulation

The UCITS directives set out the regulations under which collective investment schemes authorized in one member state of the European Union can operate in all the others. They include risk management and measurement requirements, including a proscribed approach to certain VaR statistics.

In this context, absolute VaR is defined as the VaR of a UCITS fund capped as percentage of its net asset value – in other words, the absolute risk of loss the fund is allowed to tolerate. Relative VaR, meanwhile, is the VaR of a fund divided by the VaR of a comparable benchmark – this might be an index measure or a benchmark portfolio devised for the purpose. A UCITS fund’s VaR should not be more than twice the VaR of its benchmark.

4. Expected shortfall adds more downside detail

VaR may be a useful predictor of what happens in a high proportion of scenarios, depending on the probability programmed into the measure, but what happens in other cases? The expected shortfall, or conditional VaR (CVaR) is useful here. It tells you the average of all losses that are greater or equal to the portfolio’s VaR.

So, for example, if a fund has a one day VaR of 2.5% with a 99% confidence level, the CVaR provides you with a measure of the average loss in those days where the 1% comes into play. But it’s still not the absolute worse-case scenario, which would be a total loss (or more in the case of a leveraged portfolio).

5. Having the ability to measure risk alongside performance in the same system with the same data set brings advantages

VaR measures provide asset managers with crucial data as they seek to manage risk and deliver portfolio performance within the parameters expected by their investors. Having your risk analytics within the same system as your performance measurement all working from the same data set, has its advantages versus separate siloed systems and the data management headaches they bring.

Make sure your system is up to the job.



  • Value at Risk measures the potential loss on a particular portfolio
  • Value at Risk is defined in terms of potential loss, the likelihood of that loss, and the timeframe covered
  • Having multiple levels of VaR calculations provides a more complete picture of portfolio and security level risk
  • Measuring risk alongside performance using the same data set adds value to your overall analytics capabilities



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