Futures contracts represent a suitable instrument for hedging. One conse- quence of their standardized nature is the presence of basis risk. In order to mitigate it an agent might aim to minimize Value at Risk or Expected Shortfall. Among numerous approaches to their modelling, CAViaR models which build upon quantile regression are appealing due to the limited set of assumptions and decent empirical performance. We propose alternative specifications for CAViaR model - power and exponential CAViaR, and an alternative, flexible way of computing Expected Shortfall within CAViaR framework - Implied Expectile Level. Empirical analysis suggests that ex- ponential CAViaR yields competitive results both in Value at Risk and Ex- pected Shortfall mod...
Value-at-Risk (VaR) is commonly used for financial risk measurement. It has recently become even mor...
textabstractValue-at-Risk (VaR) is commonly used for financial risk measurement. It has recently bec...
International audienceThis paper introduces a new class of models for the Value-at-Risk (VaR) and Ex...
We consider alternative specifications of conditional autoregressive quantile models to estimate Val...
Value at Risk (VaR) has become the standard measure of market risk employed by financial institution...
This paper analyzes the predictive performance of the Conditional Autoregressive Value at Risk (CAVi...
Instead of assuming the distribution of return series, Engle and Manganelli (2004) propose a new Val...
This paper proposes value‐at risk (VaR) estimation methods that are a synthesis of conditional autor...
Statistical volatility models rely on the assumption that the shape of the conditional distribution ...
Statistical volatility models rely on the assumption that the shape of the conditional distribution ...
Although Value at Risk (VaR) and Conditional Value at Risk (CVaR) have been established as standard ...
The aim of the research is to compare VaR methods/models for commodities. For risk measurement Condi...
Instead of assuming the distribution of return series, Engle and Manganelli (2004) propose a new Val...
none2noWe propose an innovative theoretical model to determine the optimal hedge ratio (OHR) with fu...
Recently, Bayesian solutions to the quantile regression problem, via the likeli-hood of a Skewed-Lap...
Value-at-Risk (VaR) is commonly used for financial risk measurement. It has recently become even mor...
textabstractValue-at-Risk (VaR) is commonly used for financial risk measurement. It has recently bec...
International audienceThis paper introduces a new class of models for the Value-at-Risk (VaR) and Ex...
We consider alternative specifications of conditional autoregressive quantile models to estimate Val...
Value at Risk (VaR) has become the standard measure of market risk employed by financial institution...
This paper analyzes the predictive performance of the Conditional Autoregressive Value at Risk (CAVi...
Instead of assuming the distribution of return series, Engle and Manganelli (2004) propose a new Val...
This paper proposes value‐at risk (VaR) estimation methods that are a synthesis of conditional autor...
Statistical volatility models rely on the assumption that the shape of the conditional distribution ...
Statistical volatility models rely on the assumption that the shape of the conditional distribution ...
Although Value at Risk (VaR) and Conditional Value at Risk (CVaR) have been established as standard ...
The aim of the research is to compare VaR methods/models for commodities. For risk measurement Condi...
Instead of assuming the distribution of return series, Engle and Manganelli (2004) propose a new Val...
none2noWe propose an innovative theoretical model to determine the optimal hedge ratio (OHR) with fu...
Recently, Bayesian solutions to the quantile regression problem, via the likeli-hood of a Skewed-Lap...
Value-at-Risk (VaR) is commonly used for financial risk measurement. It has recently become even mor...
textabstractValue-at-Risk (VaR) is commonly used for financial risk measurement. It has recently bec...
International audienceThis paper introduces a new class of models for the Value-at-Risk (VaR) and Ex...
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