Tag Archives: Value at Risk

Historical Value at Risk versus historical Expected Shortfall

Comparing the behavior of the two on the S&P 500. Previously There have been a few posts about Value at Risk (VaR) and Expected Shortfall (ES) including an introduction to Value at Risk and Expected Shortfall. Data and model The underlying data are daily returns for the S&P 500 from 1950 to the present. The VaR and … Continue reading

Posted in R language, Risk | Tagged , , , | 1 Comment

Changeability of Value at Risk estimators

How does Value at Risk change through time for the same portfolio? Previously There has been a number of posts on Value at Risk, including a basic introduction to Value at Risk and Expected Shortfall. The components garch model was also described. Issue The historical method for Value at Risk is by far the most commonly … Continue reading

Posted in R language, Risk | Tagged , , | Leave a comment

The scaling of Expected Shortfall

Getting Expected Shortfall given the standard deviation or Value at Risk. Previously There have been a few posts about Value at Risk and Expected Shortfall. Properties of the stable distribution were discussed. Scaling One way of thinking of Expected Shortfall is that it is just some number times the standard deviation, or some other number … Continue reading

Posted in R language, Risk | Tagged , , , | 2 Comments

Value at Risk with exponential smoothing

More accurate than historical, simpler than garch. Previously We’ve discussed exponential smoothing in “Exponential decay models”. The same portfolios were submitted to the same sort of analysis in “A look at historical Value at Risk”. Issue Markets experience volatility clustering.  As the previous post makes clear, historical VaR suffers dramatically from this.  An alternative is … Continue reading

Posted in R language, Risk | Tagged , | Leave a comment

An infelicity with Value at Risk

More risk does not necessarily mean bigger Value at Risk. Previously “The incoherence of risk coherence” suggested that the failure of Value at Risk (VaR) to be coherent is of little practical importance. Here we look at an attribute that is not a part of the definition of coherence yet is a desirable quality. Thought … Continue reading

Posted in R language, Risk | Tagged , , | 3 Comments

The incoherence of risk coherence

What coherent risk measures are, why some people think coherence is important, and why I don’t. The rules A risk measure is considered to be coherent if it satisfies some mathematical properties.  They are formulated in various ways — here is one set: (monotonicity) If the value of portfolio X is always bigger than the … Continue reading

Posted in Risk | Tagged , , | 2 Comments

A look at historical Value at Risk

Historical Value at Risk (VaR) is very popular because it is easy and intuitive: use the empirical distribution of some specific number of past returns for the portfolio. Previously “The estimation of Value at Risk and Expected Shortfall” included an R function to estimate historical VaR. Generating portfolios A useful tool to explore risk models … Continue reading

Posted in R language, Random portfolios, Risk | Tagged | Leave a comment

The estimation of Value at Risk and Expected Shortfall

An introduction to estimating Value at Risk and Expected Shortfall, and some hints for doing it with R. Previously “The basics of Value at Risk and Expected Shortfall” provides an introduction to the subject. Starting ingredients Value at Risk (VaR) and Expected Shortfall (ES) are always about a portfolio. There are two basic ingredients that … Continue reading

Posted in R language, Risk | Tagged , , | Leave a comment

The basics of Value at Risk and Expected Shortfall

Value at Risk and Expected Shortfall are common risk measures.  Here is a quick explanation. Ingredients The first two ingredients are each a number: The time horizon — how many days do we look ahead? The probability level — how far in the tail are we looking? Ingredient number 3 is a prediction distribution of … Continue reading

Posted in R language, Risk | Tagged , , | 3 Comments

Recap of London Quant Group Spring Seminar

The London Quant Group Spring Seminar took place this Monday and Tuesday 2011 May 16-17. There were 9 talks — I give a brief (and biased) summary of each. Dan di Bartolomeo Dan talked about the information ratios that active managers have.  He claims that the information ratio is upwardly biased compared to what we … Continue reading

Posted in Quant finance | Tagged , , | 4 Comments