VIX valuation and its futures pricing through a generalized affine realized volatility model with hidden components and jump

2020 ◽  
Vol 116 ◽  
pp. 105845 ◽  
Author(s):  
Qi Wang ◽  
Zerong Wang
Keyword(s):  
Realized Volatility ◽  
Volatility Model ◽  
Futures Pricing

scholarly journals Apreçamento de Ativos Referenciados em Volatilidade

2006 ◽  
Vol 4 (2) ◽  
pp. 203
Author(s):  
Alan De Genaro Dario
Keyword(s):  
Stochastic Volatility ◽  
Foreign Currency ◽  
Asset Price ◽  
Realized Volatility ◽  
Contingent Claims ◽  
Stochastic Volatility Model ◽  
Currency Options ◽  
Variance Swaps ◽  
Volatility Model ◽  
Future Realized Volatility

Volatility swaps are contingent claims on future realized volatility. Variance swaps are similar instruments on future realized variance, the square of future realized volatility. Unlike a plain vanilla option, whose volatility exposure is contaminated by its asset price dependence, volatility and variance swaps provide a pure exposure to volatility alone. This article discusses the risk-neutral valuation of volatility and variance swaps based on the framework outlined in the Heston (1993) stochastic volatility model. Additionally, the Heston (1993) model is calibrated for foreign currency options traded at BMF and its parameters are used to price swaps on volatility and variance of the BRL / USD exchange rate.

scholarly journals Forecasting Multivariate Volatility using the VARFIMA Model on Realized Covariance Cholesky Factors

2011 ◽  
Vol 231 (1) ◽  
Author(s):  
Roxana Halbleib ◽  
Valeri Voev
Keyword(s):  
Evaluation Criteria ◽  
Forecast Accuracy ◽  
Realized Volatility ◽  
Covariance Matrices ◽  
Risk Averse ◽  
Return Distribution ◽  
Volatility Model ◽  
Realized Covariance ◽  
Dominance Tests ◽  
Multivariate Volatility

SummaryThis paper analyzes the forecast accuracy of the multivariate realized volatility model introduced by Chiriac and Voev (2010), subject to different degrees of model parametrization and economic evaluation criteria. Bymodelling the Cholesky factors of the covariance matrices, the model generates positive definite, but biased covariance forecasts. In this paper, we provide empirical evidence that parsimonious versions of the model generate the best covariance forecasts in the absence of bias correction. Moreover, we show by means of stochastic dominance tests that any risk averse investor, regardless of the type of utility function or return distribution, would be better-off from using this model than from using some standard approaches.

scholarly journals GARCH-Type Model with Continuous and Jump Variation for Stock Volatility and Its Empirical Study in China

2014 ◽  
Vol 2014 ◽  
pp. 1-8
Author(s):  
Huannan Zhang ◽  
Qiujun Lan
Keyword(s):  
High Frequency ◽  
Predictive Power ◽  
Sample Path ◽  
Realized Volatility ◽  
Type Model ◽  
Stock Volatility ◽  
Estimated Parameters ◽  
Volatility Model ◽  
The Future ◽  
Security Valuation

On the basis of GARCH-RV-type model, we decomposed the realized volatility into continuous sample path variation and discontinuous jump variation, then proposed a new volatility model which we call the GARCH-type model with continuous and jump variation (GARCH-CJ-type model). By using the 5-minute high frequency data of HUSHEN 300 index in China, we estimated parameters of the GARCH-type model, the GARCH-RV-type model, and the GARCH-CJ-type model and compared the three types of models’ predictive power to the future volatility. The results show that the realized volatility and the continuous sample path variation have certain predictive power for future volatility, but the discontinuous jump variation does not have that kind of function. What is more, the GARCH-CJ-type model has a more power to predict the future volatility than the other two types of models. Therefore, the GARCH-CJ-type model is much more useful for the research on the capital assets pricing, the derivative security valuation, and so on.

VIX term structure and VIX futures pricing with realized volatility

2018 ◽  
Vol 39 (1) ◽  
pp. 72-93 ◽  
Author(s):  
Zhuo Huang ◽  
Chen Tong ◽  
Tianyi Wang
Keyword(s):  
Term Structure ◽  
Realized Volatility ◽  
Vix Futures ◽  
Futures Pricing

scholarly journals A Bayesian Semiparametric Realized Stochastic Volatility Model

2021 ◽  
Vol 14 (12) ◽  
pp. 617
Author(s):  
Jia Liu
Keyword(s):  
Stochastic Volatility ◽  
Asset Returns ◽  
Realized Volatility ◽  
Stochastic Volatility Model ◽  
Estimation Bias ◽  
Bayesian Nonparametric ◽  
Proposed Model ◽  
Volatility Model ◽  
Flexible Framework ◽  
Density Forecasts

This paper proposes a semiparametric realized stochastic volatility model by integrating the parametric stochastic volatility model utilizing realized volatility information and the Bayesian nonparametric framework. The flexible framework offered by Bayesian nonparametric mixtures not only improves the fitting of asymmetric and leptokurtic densities of asset returns and logarithmic realized volatility but also enables flexible adjustments for estimation bias in realized volatility. Applications to equity data show that the proposed model offers superior density forecasts for returns and improved estimates of parameters and latent volatility compared with existing alternatives.

PRICING JOINT CLAIMS ON AN ASSET AND ITS REALIZED VARIANCE IN STOCHASTIC VOLATILITY MODELS

2013 ◽  
Vol 16 (01) ◽  
pp. 1350005 ◽  
Author(s):  
LORENZO TORRICELLI
Keyword(s):  
Stochastic Volatility ◽  
Realized Volatility ◽  
Numerical Results ◽  
Quadratic Variation ◽  
Stochastic Volatility Model ◽  
Realized Variance ◽  
Joint Function ◽  
Stochastic Volatility Models ◽  
Volatility Models ◽  
Volatility Model

In the setting of a stochastic volatility model, we find a general pricing equation for the class of payoffs depending on the terminal value of a market asset and its final quadratic variation. This provides a pricing tool for European-style claims paying off at maturity a joint function of the underlying and its realized volatility or variance. We study the solution under various specific stochastic volatility models, give a formula for the computation of the delta and gamma of these claims, and introduce some new interesting payoffs that can be valued by means of the general pricing equation. Numerical results are given and compared to those from plain vanilla derivatives.

scholarly journals Forecasting Return Volatility of the CSI 300 Index Using the Stochastic Volatility Model with Continuous Volatility and Jumps

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Xu Gong ◽  
Zhifang He ◽  
Pu Li ◽  
Ning Zhu
Keyword(s):  
Stochastic Volatility ◽  
Prediction Accuracy ◽  
Financial Risk ◽  
Sample Path ◽  
Realized Volatility ◽  
Stochastic Volatility Model ◽  
Stock Index ◽  
Return Volatility ◽  
Volatility Model ◽  
Continuous Volatility

The logarithmic realized volatility is divided into the logarithmic continuous sample path variation and the logarithmic discontinuous jump variation on the basis of the SV-RV model in this paper, which constructs the stochastic volatility model with continuous volatility (SV-CJ model). Then, we use high-frequency transaction data for five minutes of the CSI 300 stock index as the study sample, which, respectively, make parameter estimation on the SV, SV-RV, and SV-CJ model. We also comparatively analyze these three models' prediction accuracy by using the loss functions and SPA test. The results indicate that the prior logarithmic realized volatility and the logarithmic continuous sample path variation can be used to predict the future return volatility in China's stock market, while the logarithmic discontinuous jump variation is poor at its prediction accuracy. Besides, the SV-CJ model has an obvious advantage over the SV and SV-RV model as to the prediction accuracy of the return volatility, and it is more suitable for the research concerning the problems of financial practice such as the financial risk management.

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