Add to ORKGIt is commonly accepted that some financial data may exhibit long-range dependence, while other financial data exhibit intermediate-range dependence or short-range dependence. These behaviors may be fitted to a continuous-time fractional stochastic model. The estimation procedure proposed in this paper is based on a continuous-time version of the Gauss–Whittle objective function to find the parameter estimates that minimize the discrepancy between the spectral density and the data periodogram. As a special case, the proposed estimation procedure is applied to a class of fractional stochastic volatility models to estimate the drift, standard deviation and memory parameters of the volatility process under consideration. As an application, the...
Stochastic volatility (SV) models are substantial for financial markets and decision making because ...
We treat the problem of option pricing under a stochastic volatility model that exhibits long-range ...
The standard Black-Scholes model is a continuous time model to predict asset movement. For the stand...
It is commonly accepted that some financial data may exhibit long-range dependence, while other fina...
It is commonly accepted that some financial data may exhibit long-range dependence, while other fina...
2004 © Applied Probability TrustThis paper considers a class of continuous-time long-range-dependent...
In recent years fractionally differenced processes have received a great deal of attention due to it...
In recent years fractionally differenced processes have received a great deal of attention due to it...
We discuss some of the issues pertaining to modelling and estimating long memory in volatility. The ...
Recent studies have suggested that stock markets' volatility has a type of long-range dependenc...
In this paper we introduce a fractionally integrated exponential continuous time GARCH(p,d,q) proces...
This paper proposes a novel stochastic volatility model that draws from the exist- ing literature on...
This thesis conducts three exercises on volatility modeling of financial assets. We are essentially ...
One of the typical ways of measuring risk associated with persistence in financial data set can be d...
Earlier we proposed the stochastic point process model, which reproduces a variety of self-affine ti...
Stochastic volatility (SV) models are substantial for financial markets and decision making because ...
We treat the problem of option pricing under a stochastic volatility model that exhibits long-range ...
The standard Black-Scholes model is a continuous time model to predict asset movement. For the stand...
It is commonly accepted that some financial data may exhibit long-range dependence, while other fina...
It is commonly accepted that some financial data may exhibit long-range dependence, while other fina...
2004 © Applied Probability TrustThis paper considers a class of continuous-time long-range-dependent...
In recent years fractionally differenced processes have received a great deal of attention due to it...
In recent years fractionally differenced processes have received a great deal of attention due to it...
We discuss some of the issues pertaining to modelling and estimating long memory in volatility. The ...
Recent studies have suggested that stock markets' volatility has a type of long-range dependenc...
In this paper we introduce a fractionally integrated exponential continuous time GARCH(p,d,q) proces...
This paper proposes a novel stochastic volatility model that draws from the exist- ing literature on...
This thesis conducts three exercises on volatility modeling of financial assets. We are essentially ...
One of the typical ways of measuring risk associated with persistence in financial data set can be d...
Earlier we proposed the stochastic point process model, which reproduces a variety of self-affine ti...
Stochastic volatility (SV) models are substantial for financial markets and decision making because ...
We treat the problem of option pricing under a stochastic volatility model that exhibits long-range ...
The standard Black-Scholes model is a continuous time model to predict asset movement. For the stand...