The stochastic volatility model is used to estimate daily asset price dynamics. The model is
estimated by integrating latent volatility out of the joint density of prices and volatility to obtain …

… Jon Danielsson London School of Economics j.danielsson@lse.ac.uk Hyun Song Shin London
… The reader is referred to Danielsson, Shin and Zigrand (2002), Danielsson and Zigrand (…

The quality of statistical risk models is much lower than often assumed. Such models are
useful for measuring the risk of frequent small events, such as in internal risk management, but …

This paper considers the properties of risk measures, primarily value-at-risk (VaR), from
both internal and external (regulatory) points of view. It is argued that since market data is …

… Determination of 3 J HNHα couplings indicates that the hydrophobic regions tend to have
a β propensity in aqueous solution [37]. NMR relaxation measurements have shown that the …

This paper evaluates the model risk of models used for forecasting systemic and market risk.
Model risk, which is the potential for different models to provide inconsistent outcomes, is …

We study the effects of stock market volatility on risk-taking and financial crises by constructing
a cross-country database spanning up to 211 years and across 60 countries. Prolonged …

Alzheimer's disease is the most common of the protein misfolding (“amyloid”) diseases. The
deposits in the brains of afflicted patients contain as a major fraction an aggregated …

Many financial applications, such as risk analysis, and derivatives pricing, depend on time
scaling of risk. A common method for this purpose is the square-root-of-time rule where an …

Financial institutions rely heavily on Value-at-Risk (VaR) as a risk measure, even though it
is not globally subadditive. First, we theoretically show that the VaR portfolio measure is …