We present several estimates of measures of risk amongst the most well-known, using both high and low frequency data. The aim of the article is to show which lower frequency measures can be an acceptable substitute to the high precision measures, when transaction data is unavailable for a long...

"Constant proportion portfolio insurance" (CPPI) is nowadays one of the most popular techniques for portfolio insurance strategies. It simply consists of reallocating the risky part of a portfolio with respect to market conditions, via a leverage parameter - called the multiple - guaranteeing a...

This paper presents a general theory that works out the relation between coherent risk measures, valuation bounds, and certain classes of portfolio optimization problems. It is economically general in the sense that it works for any cash stream spaces, be it in dynamic trading settings, one-step...

VaR models are related to statistical forecast systems. Within that framework different forecast tasks including Value-at-Risk and shortfall are discussed and motivated. A backtesting method based on the shortfall is developed and applied to VaR forecasts of areal portfolio. The analysis shows...

Starting from the objective of banking supervision - to minimize the overall costs of banking to the general public - we show that the current standard of quantifying market risk is flawed. It is perfectly aligned with the interests of banks' shareholders and management, but not with the...

We analyzed the volatility dynamics of three developed markets (U.K., U.S. and Japan), during the period 2003-2011, by comparing the performance of several multivariate volatility models, namely Constant Conditional Correlation (CCC), Dynamic Conditional Correlation (DCC) and consistent DCC...

The empirical evidence of heavy tails in stock return data is recognised by risk managers as an important factor in assessing the Value-at-Risk and risk profile of investment portfolios. Tail index estimation appears to be a tailor-made tool for estimating the extreme quantiles of heavy tailed...

In this paper we propose a new tool for backtesting that examines the quality of Value-at- Risk (VaR) forecasts. To date, the most distinguished regression-based backtest, proposed by Engle and Manganelli (2004), relies on a linear model. However, in view of the di- chotomic character of the...

In this paper various Value-at-Risk techniques are applied tot the Dutch stock market index AEX and to the Dow Jones Industrial Average. the main conclusions are: (1) Changing volatility over time is the most important characteristic of stock returns when modelling value-at-risk; (2) For high...