risk forecasts to the appropriate monetary authorities at the beginning of each trading day, using one or more risk models … to measure Value-at-Risk (VaR). The risk estimates of these models are used to determine capital requirements and … estimated VaR. In this paper we define risk management in terms of choosing from a variety of risk models, and discuss the …

daily risk forecasts to the appropriate monetary authorities at the beginning of each trading day, using one or more risk … models to measure Value-at-Risk (VaR). The risk estimates of these models are used to determine capital requirements and … estimated VaR. In this paper we define risk management in terms of choosing sensibly from a variety of risk models, discuss the …

: liquidity timing leads to tangible economic gains; a risk-averse investor will pay a high performance fee to switch from a … risk-adjusted returns. …

returns for constituents of the S&P 500 index. We assess the implication for one-day ahead 95% and 99% Value-at-Risk (VaR …

-threshold double autoregressive models, a new hyperbolic GARCH model, intraday value-at-risk: an asymmetric autoregressive conditional …

first partial moment is also obtained, which plays a vital role in financial risk management. The proof involves a …-sample distribution of the 2SLS estimatorof a structural parameter. Second, the Value at Risk and Expected Shortfall of a … quadraticportfolio with heavy-tailed risk factors. …

with a duration-based POT method, and extreme market risk and extreme value theory. … papers that were presented at the 2011 Madrid International Conference on “Risk Modelling and Management” (RMM2011). The … papers cover the following topics: currency hedging strategies using dynamic multivariate GARCH, risk management of risk …

risk of thestrategies increases proportionally. Second, we test whether the strategies can be implementedsuccessfully in …, we examine several popularexplanations for the excess returns. We find no evidence of higher market risk or lower …

risk and return of two pairs trading strategies: a conditional statistical arbitrage method and an implicit arbitrage one … uncertainty with risk and return of stock trading. In terms of methodology, we show the effect that using an encompassing prior … better results in terms of profit per capital engagement and risk than using a standard linear normalization. …