David Spiegelhalter gave a fascinating talk on Communicating Risk and Uncertainty to the Public & Policymakers at the Grantham Institute of the Imperial College in London last Tuesday.In a very engaging way David gave many examples and anecdotes fr...
Conference The first EARL Conference (Effective Applications of the R Language) was held 2014 September 15-17 in London. Talk My talk was “Effective risk management with R” (annotated slides). Instability hypothesis When I was preparing for the talk, one of my ideas was to show the Google trend for searches for Minsky’s instability hypothesis. I … Continue reading →
Risk, Insurance, and the Actuary Risk is an inherent part of our daily life. As a result, most of us, take out insurance policies as a means of protection against scenarios which, were they to occur, may cause hardship whether … Continue reading →
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 →
Tomorrow, around noon, I will be giving a talk on predictive modeling for actuaries. In the introduction, I will get back shortly on the idea that a prediction is usually a best estimate, in the sense of getting an expected value. And because it is natural to use least square ideas. In order to illustrate all those concepts, we will use a simple dataset, with the sex, the height and…
About half a year ago Ian Branagan, Chief Risk Officer of Renaissance Re - a Bermudian reinsurance company with a focus on property catastrophe insurance, gave a talk about the usage of models in risk management and how they evolved over the last twent...
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 →
Exactly one month ago, I entered the Bellagio casino to gamble at the roulette. It was actually a request from my daughter’s godfather (who happens to be a probabilist, actually). On a comment on a previous post, he suggested the following deal, In the Bellagio you put 10$ for me on the 33 and 10$ for you as well. If 33 shows up, you bring me to a French “3…
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 →
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 →
