• Corpus ID: 238253004

Stochastic volatility model with range-based correction and leverage

@inproceedings{Kurose2021StochasticVM,
  title={Stochastic volatility model with range-based correction and leverage},
  author={Yuta Kurose},
  year={2021}
}
This study presents contemporaneous modeling of asset return and price range within the framework of stochastic volatility with leverage. A new representation of the probability density function for the price range is provided, and its accurate sampling algorithm is developed. A Bayesian estimation using Markov chain Monte Carlo (MCMC) method is provided for the model parameters and unobserved variables. MCMC samples can be generated rigorously, despite the estimation procedure requiring… 
View PDF on arXiv

Figures and Tables from this paper

References

SHOWING 1-10 OF 47 REFERENCES
Matrix exponential stochastic volatility with cross leverage
Realized stochastic volatility with leverage and long memory
Volatility Forecasting With Range-Based EGARCH Models
We provide a simple, yet highly effective framework for forecasting return volatility by combining exponential generalized autoregressive conditional heteroscedasticity models with data on the range.…
Bayesian range-based estimation of stochastic volatility models
Range-Based Estimation of Stochastic Volatility Models
We propose using the price range in the estimation of stochastic volatility models. We show theoretically, numerically, and empirically that range-based volatility proxies are not only highly…
Bayesian analysis of stochastic volatility models with fat-tails and correlated errors
Stochastic volatility with leverage: Fast and efficient likelihood inference
Volatility and Quantile Forecasts by Realized Stochastic Volatility Models with Generalized Hyperbolic Distribution
Estimating stochastic volatility models using daily returns and realized volatility simultaneously
Using Daily Range Data to Calibrate Volatility Diffusions and Extract the Forward Integrated Variance
Acommon model for security price dynamics is the continuous-time stochastic volatility model. For this model, Hull and White (1987) show that the price of a derivative claim is the conditional…
...
...