Add to ORKGWe provide a computationally e±cient method, based on Harvey (1998) proposal, to estimate the underlying volatility of asset returns using the Long-Memory Stochastic Volatility (LMSV ) model. The performance of our procedure is illustrated with an application to three series of daily exhange rates returns. A comparison of long memory GARCH-type volatilities with our smoothed ones is also presented
A new stochastic volatility model, called A-LMSV, is proposed to cope simultaneously with leverage e...
We extend the currently most popular models for the volatility of financial time se-ries, Ornstein-U...
Inspired by the idea that regime switching may give rise to persistence that is observationally equi...
We provide a computationally e±cient method, based on Harvey (1998) proposal, to estimate the underl...
Recent studies have suggested that stock markets' volatility has a type of long-range dependenc...
This paper develops a multivariate long-memory stochastic volatility model which allows the multi-as...
The daily return and the realized volatility are simultaneously modeled in the stochastic volatility...
In this paper we fit the main features of financial returns by means of a two factor long memory sto...
In this paper we fit the main features of financial returns by means of a two factor long memory sto...
This thesis develops a new volatility model, Multivariate Long Memory Stochastic Volatility (MLMSV) ...
We discuss some of the issues pertaining to modelling and estimating long memory in volatility. The ...
This paper considers a flexible class of time series models generated by Gegenbauer polynomials inco...
It is well known that accurately measuring and forecasting financial volatility plays a central role...
We propose a new semiparametric estimator of the degree of persistence in volatility for long memory...
This paper considers the persistence found in the volatility of many financial time series by means ...
A new stochastic volatility model, called A-LMSV, is proposed to cope simultaneously with leverage e...
We extend the currently most popular models for the volatility of financial time se-ries, Ornstein-U...
Inspired by the idea that regime switching may give rise to persistence that is observationally equi...
We provide a computationally e±cient method, based on Harvey (1998) proposal, to estimate the underl...
Recent studies have suggested that stock markets' volatility has a type of long-range dependenc...
This paper develops a multivariate long-memory stochastic volatility model which allows the multi-as...
The daily return and the realized volatility are simultaneously modeled in the stochastic volatility...
In this paper we fit the main features of financial returns by means of a two factor long memory sto...
In this paper we fit the main features of financial returns by means of a two factor long memory sto...
This thesis develops a new volatility model, Multivariate Long Memory Stochastic Volatility (MLMSV) ...
We discuss some of the issues pertaining to modelling and estimating long memory in volatility. The ...
This paper considers a flexible class of time series models generated by Gegenbauer polynomials inco...
It is well known that accurately measuring and forecasting financial volatility plays a central role...
We propose a new semiparametric estimator of the degree of persistence in volatility for long memory...
This paper considers the persistence found in the volatility of many financial time series by means ...
A new stochastic volatility model, called A-LMSV, is proposed to cope simultaneously with leverage e...
We extend the currently most popular models for the volatility of financial time se-ries, Ornstein-U...
Inspired by the idea that regime switching may give rise to persistence that is observationally equi...