One widely used measure to quantify and regulate risk is the Value-at-risk
(VaR) which is an indicator of the extremes within which the stock trading returns of an investment in a specific asset or portfolio fluctuates (Giot and Laurent, 2004).
The risk analytics system will allow Standard Life Investments to analyse solutions from multiple perspectives, illustrating the impact of alternative allocation strategies on the Value-at-Risk
and expected returns of portfolios.
and expected shortfall using fractionally integrated models of conditional volatility: international evidence.
The mandate will also include a synthetic value-at-risk
solution, including pooled cash positions across all markets and a consolidated view of all risk.
Zangari analyzed possibilities of using the properties of distributions other than the normal distribution to calculate the value-at-risk
. He used the mixed normal distribution and the distribution of GED (generalized error distribution) to model the distribution of profits, showing that both of these modifications allow one to model in a much better way the phenomenon of "fat tails", but in the case of really large price movements these approximations are not accurate enough.
They cover probability distances and metrics, choice under uncertainty, a classification of probability distances, risk and uncertainty, average value-at-risk
and computing it through Monte Carlo, and stochastic dominance.
Based Risk Management: Optimal Policies and Asset Prices, Review of Financial Studies
with Time-Varying Copula: Evidence from the Americas", MPRA Paper, Munich Personal RePec Arhive, No.
We find that for an explicitly specified confidence level, the Value-at-Risk
satisfies the regulator's condition and is the "most efficient" capital requirement in the sense that it minimizes some reasonable cost function.
Included among the most popular of these techniques are Potential Future Exposure (PFE) and Credit Value-at-Risk
(CVAR) using Monte Carlo simulations.