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...

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...

A novel simulation-based methodology is proposed to test the validity of a set of marginal time series models, where the dependence structure between the time series is taken ‘directly’ from the observed data. The procedure is useful when one wants to summarize the test results for several...

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...

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

The new Basel II regulation contains a number of new regulatory features. Most importantly, internal ratings will be given a central role in the evaluation of the riskiness of bank loans. Another novelty is that retail credit and loans to small and medium-sized enterprises will receive a special...

A drawback of available portfolio credit risk models is that they fail to allow for default risk dependency across loans other than through common risk factors. Thereby, thesemodels ignore that close ties can exist between companies due to legal, financial and business relations. In this paper,...