A volatility model must be able to forecast volatility; this is the central requirement in almost all financial applications. In this paper we outline some stylised facts about volatility that should be incorporated in a model; pronounced persistence and mean-reversion, asymmetry such that the sign of an innovation also affects volatility and the possibility of exogenous or pre-determined variables influencing volatility. We use data on the Dow Jones Industrial index to illustrate these stylised facts, and the ability of GARCH-type models to capture these features. We conclude with some challenges for future research in this area
It is sometimes argued that an increase in stock market volatility raises required stock returns, an...
In this paper we estimate minimum capital risk requirements for short and long positions with three ...
Volatility is unobservable and an indispensible contribution to the pricing models and for risk mana...
A volatility model must be able to forecast volatility; this is the central requirement in almost al...
The forecasting ability of the most popular volatility forecasting models is examined and an alterna...
This study provides comprehensive analysis of the possible influences of the real body, and both upp...
[[abstract]]This study uses exchange-traded fund (ETF) data to investigate the ability of the time-s...
This paper examines the predictive power of idiosyncratic volatility in the context of daily stock m...
Volatility is considered among the most vital concepts of the financial market and is frequently use...
Volatility is arguably one of the most important measures in financial economics since it is often u...
This Chapter reviews the main classes of models that incorporate volatility, with a focus on the mos...
The three main purposes of forecasting volatility are for risk management, for asset alloca-tion, an...
Modern institutions from multinationals to nation states use the global derivatives market in order ...
Abstract: Volatility is a key parameter used inmany financial applications, from deriva-tives valuat...
Volatility in financial markets has both low and high–frequency components which determine its dynam...
It is sometimes argued that an increase in stock market volatility raises required stock returns, an...
In this paper we estimate minimum capital risk requirements for short and long positions with three ...
Volatility is unobservable and an indispensible contribution to the pricing models and for risk mana...
A volatility model must be able to forecast volatility; this is the central requirement in almost al...
The forecasting ability of the most popular volatility forecasting models is examined and an alterna...
This study provides comprehensive analysis of the possible influences of the real body, and both upp...
[[abstract]]This study uses exchange-traded fund (ETF) data to investigate the ability of the time-s...
This paper examines the predictive power of idiosyncratic volatility in the context of daily stock m...
Volatility is considered among the most vital concepts of the financial market and is frequently use...
Volatility is arguably one of the most important measures in financial economics since it is often u...
This Chapter reviews the main classes of models that incorporate volatility, with a focus on the mos...
The three main purposes of forecasting volatility are for risk management, for asset alloca-tion, an...
Modern institutions from multinationals to nation states use the global derivatives market in order ...
Abstract: Volatility is a key parameter used inmany financial applications, from deriva-tives valuat...
Volatility in financial markets has both low and high–frequency components which determine its dynam...
It is sometimes argued that an increase in stock market volatility raises required stock returns, an...
In this paper we estimate minimum capital risk requirements for short and long positions with three ...
Volatility is unobservable and an indispensible contribution to the pricing models and for risk mana...