ABSTRACT Even with studies to confront different risk models for gold, there is no consensus about what is the best approach or models when considering the presence of extreme negative values. To that, we employ a backtesting in conditional models with distinct distributions in order to estimate VaR and ES risk measures and, thus, find a pattern for the risk of investments in gold. We verify that the EVT approach has more conservative and volatile risk estimates, with satisfactory results in extreme situations
This paper examines volatility and correlation dynamics in price returns of gold, silver, platinum a...
In this study we investigate the performance of the generalised lambda distribution (GLD), the gener...
A range of statistical models for the joint distribution of different financial market returns has b...
Even with studies to confront different risk models for gold, there is no consensus about what is th...
Extreme value theory (EVT) has been widely applied in fields such as hydrology and insurance. It is ...
Risk management tools such as value-at-risk (VaR) are highly dependent on the underlying distributio...
Financial risk model validation is a key part of the internal model-based approach to market risk ma...
We investigate the volatility dynamics of gold markets. While there are a number of recent studies e...
VaR (Value at Risk) in the gold market was measured and predicted by combining stochastic volatility...
One of the key components of financial risk management is risk measurement. This typically requires ...
Purpose The purpose of the paper is to back-test value-at-risk (VaR) models for conditional distribu...
We investigate the volatility dynamics of gold markets. While there are a number of recent studies e...
This paper conducts a comparative evaluation of the predictive performance of various Value-at-Risk ...
Financial markets frequently experience extreme movements in the negative side. Accurate computation...
Value-at-Risk (VaR) is used to analyze the market downside risk associated with investments in six k...
This paper examines volatility and correlation dynamics in price returns of gold, silver, platinum a...
In this study we investigate the performance of the generalised lambda distribution (GLD), the gener...
A range of statistical models for the joint distribution of different financial market returns has b...
Even with studies to confront different risk models for gold, there is no consensus about what is th...
Extreme value theory (EVT) has been widely applied in fields such as hydrology and insurance. It is ...
Risk management tools such as value-at-risk (VaR) are highly dependent on the underlying distributio...
Financial risk model validation is a key part of the internal model-based approach to market risk ma...
We investigate the volatility dynamics of gold markets. While there are a number of recent studies e...
VaR (Value at Risk) in the gold market was measured and predicted by combining stochastic volatility...
One of the key components of financial risk management is risk measurement. This typically requires ...
Purpose The purpose of the paper is to back-test value-at-risk (VaR) models for conditional distribu...
We investigate the volatility dynamics of gold markets. While there are a number of recent studies e...
This paper conducts a comparative evaluation of the predictive performance of various Value-at-Risk ...
Financial markets frequently experience extreme movements in the negative side. Accurate computation...
Value-at-Risk (VaR) is used to analyze the market downside risk associated with investments in six k...
This paper examines volatility and correlation dynamics in price returns of gold, silver, platinum a...
In this study we investigate the performance of the generalised lambda distribution (GLD), the gener...
A range of statistical models for the joint distribution of different financial market returns has b...