scholarly journals Estimating Stochastic Volatility under the Assumption of Stochastic Volatility of Volatility

Risks ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 35
Author(s):  
Moawia Alghalith ◽  
Christos Floros ◽  
Konstantinos Gkillas

We propose novel nonparametric estimators for stochastic volatility and the volatility of volatility. In doing so, we relax the assumption of a constant volatility of volatility and therefore, we allow the volatility of volatility to vary over time. Our methods are exceedingly simple and far simpler than the existing ones. Using intraday prices for the Standard & Poor’s 500 equity index, the estimates revealed strong evidence that both volatility and the volatility of volatility are stochastic. We also proceeded in a Monte Carlo simulation analysis and found that the estimates were reasonably accurate. Such evidence implies that the stochastic volatility models proposed in the literature with constant volatility of volatility may fail to approximate the discrete-time short rate dynamics.

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Michael Grabchak ◽  
Eliana Christou

AbstractIn this paper we consider the problem of estimating expected shortfall (ES) for discrete time stochastic volatility (SV) models. Specifically, we develop Monte Carlo methods to evaluate ES for a variety of commonly used SV models. This includes both models where the innovations are independent of the volatility and where there is dependence. This dependence aims to capture the well-known leverage effect. The performance of our Monte Carlo methods is analyzed through simulations and empirical analyses of four major US indices.


2013 ◽  
Vol 411-414 ◽  
pp. 1089-1094
Author(s):  
Jun Mei Ma ◽  
Gui Ding Gu

This paper studied the pricing of variance swap derivatives under the multi-factor stochastic volatility models by Monte Carlo simulation. Control variate technique was well used to reduce the variance of the simulation effectively. How to choose the high efficient control variate was also contained. Then the numerical results show the high efficiency of the speed up method. The pricing structure in the paper is also applicable for the valuation of other types of variance swaps and other financial derivatives under multi-factor models.


2019 ◽  
Vol 17 (4) ◽  
pp. 22
Author(s):  
Omar Abbara ◽  
Mauricio Zevallos

<p>The paper assesses the method proposed by Shumway and Stoffer (2006, Chapter 6, Section 10) to estimate the parameters and volatility of stochastic volatility models. First, the paper presents a Monte Carlo evaluation of the parameter estimates considering several distributions for the perturbations in the observation equation. Second, the method is assessed empirically, through backtesting evaluation of VaR forecasts of the S&amp;P 500 time series returns. In both analyses, the paper also evaluates the convenience of using the Fuller transformation.</p>


Sign in / Sign up

Export Citation Format

Share Document