Download or read book Empirical Performance of Non Affine Stochastic Volatility Models written by Øystein Sivertsen Jensen and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis aims to test the empirical performance of 5 different non-affine specifications of the stochastic volatility model. The performance of the common affine square-root (SQR) specification is also investigated. The analysis is carried out by calibrating each model to option data by fitting the model-implied Black-Scholes volatilities to the marked-implied Black-Scholes volatilities. The data is collected from three months of very different financial climates; January 2007, October 2008, and July 2010. Three assets are considered; the S&P500 index, Apple Inc. and ExxonMobil Corporation. The findings confirm that model fit can be improved by choosing a non-affine model specification. The VAR model stands out as the best specification across all performance measures. The 3/2N model also consistently outperforms the SQR model. A separate estimation exercise based on maximum likelihood is also performed, confirming the better performance of the non-affine model specifications. The estimated parameters from the two estimation exercises show little sign of consistency, which indicates that all models are misspecified.

Download or read book Stochastic Volatility and Jumps written by Katja Ignatieva and published by . This book was released on 2009 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper analyzes exponentially affine and non-affine stochastic volatility models with jumps in returns and volatility. Markov Chain Monte Carlo (MCMC) technique is applied within a Bayesian inference to estimate model parameters and latent variables using daily returns from the Samp;P 500 stock index. There are two approaches to overcome the problem of misspecification of the square root stochastic volatility model. The first approach proposed by Christo ersen, Jacobs and Mimouni (2008) suggests to investigate some non-affine alternatives of the volatility process. The second approach consists in examining more heavily parametrized models by adding jumps to the return and possibly to the volatility process. The aim of this paper is to combine both model frameworks and to test whether the class of affine models is outperformed by the class of non-affine models if we include jumps into the stochastic processes. We conclude that the non-affine model structure have promising statistical properties and are worth further investigations. Further, we find affine models with jump components that perform similar to the non affine models without jump components. Since non affine models yield economically unrealistic parameter estimates, and research is rather developed for the affine model structures we have a tendency to prefer the affine jump diffusion models.

Download or read book Essays on Empirical Performance of Affine Jump diffusion Option Pricing Models written by Xiang Zhang and published by . This book was released on 2012 with total page 612 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Empirical Studies on Volatility in International Stock Markets written by Eugenie M.J.H. Hol and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: Empirical Studies on Volatility in International Stock Markets describes the existing techniques for the measurement and estimation of volatility in international stock markets with emphasis on the SV model and its empirical application. Eugenie Hol develops various extensions of the SV model, which allow for additional variables in both the mean and the variance equation. In addition, the forecasting performance of SV models is compared not only to that of the well-established GARCH model but also to implied volatility and so-called realised volatility models which are based on intraday volatility measures. The intended readers are financial professionals who seek to obtain more accurate volatility forecasts and wish to gain insight about state-of-the-art volatility modelling techniques and their empirical value, and academic researchers and students who are interested in financial market volatility and want to obtain an updated overview of the various methods available in this area.

Download or read book Testing the Empirical Performance of Stochastic Volatility Models of the Short Term Interest Rate written by Turan G. Bali and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: I introduce two-factor discrete time stochastic volatility models of the short-term interest rate to compare the relative performance of existing and alternative empirical specifications. I develop a nonlinear asymmetric framework that allows for comparisons of non-nested models featuring conditional heteroskedasticity and sensitivity of the volatility process to interest rate levels. A new class of stochastic volatility models with asymmetric drift and nonlinear asymmetric diffusion process is introduced in discrete time and tested against the popular continuous time and symmetric and asymmetric GARCH models. The existing models are rejected in favor of the newly proposed models because of the asymmetric drift of the short rate, and the presence of nonlinearity, asymmetry, GARCH, and level effects in its volatility. I test the predictive power of nested and non-nested models in capturing the stochastic behavior of the risk-free rate. Empirical evidence on three-, six-, and 12-month U.S. Treasury bills indicates that two-factor stochastic volatility models are better than diffusion and GARCH models in forecasting the future level and volatility of interest rate changes.

Download or read book Stochastic Volatility and Realized Stochastic Volatility Models written by Makoto Takahashi and published by Springer Nature. This book was released on 2023-04-18 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: This treatise delves into the latest advancements in stochastic volatility models, highlighting the utilization of Markov chain Monte Carlo simulations for estimating model parameters and forecasting the volatility and quantiles of financial asset returns. The modeling of financial time series volatility constitutes a crucial aspect of finance, as it plays a vital role in predicting return distributions and managing risks. Among the various econometric models available, the stochastic volatility model has been a popular choice, particularly in comparison to other models, such as GARCH models, as it has demonstrated superior performance in previous empirical studies in terms of fit, forecasting volatility, and evaluating tail risk measures such as Value-at-Risk and Expected Shortfall. The book also explores an extension of the basic stochastic volatility model, incorporating a skewed return error distribution and a realized volatility measurement equation. The concept of realized volatility, a newly established estimator of volatility using intraday returns data, is introduced, and a comprehensive description of the resulting realized stochastic volatility model is provided. The text contains a thorough explanation of several efficient sampling algorithms for latent log volatilities, as well as an illustration of parameter estimation and volatility prediction through empirical studies utilizing various asset return data, including the yen/US dollar exchange rate, the Dow Jones Industrial Average, and the Nikkei 225 stock index. This publication is highly recommended for readers with an interest in the latest developments in stochastic volatility models and realized stochastic volatility models, particularly in regards to financial risk management.

Download or read book The Empirical Performance of the Stochastic Volatility Model in Pricing FTSE 100 Index Options written by Krisda Phatcharoen and published by . This book was released on 1998 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Handbook of Volatility Models and Their Applications written by Luc Bauwens and published by John Wiley & Sons. This book was released on 2012-03-22 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete guide to the theory and practice of volatility models in financial engineering Volatility has become a hot topic in this era of instant communications, spawning a great deal of research in empirical finance and time series econometrics. Providing an overview of the most recent advances, Handbook of Volatility Models and Their Applications explores key concepts and topics essential for modeling the volatility of financial time series, both univariate and multivariate, parametric and non-parametric, high-frequency and low-frequency. Featuring contributions from international experts in the field, the book features numerous examples and applications from real-world projects and cutting-edge research, showing step by step how to use various methods accurately and efficiently when assessing volatility rates. Following a comprehensive introduction to the topic, readers are provided with three distinct sections that unify the statistical and practical aspects of volatility: Autoregressive Conditional Heteroskedasticity and Stochastic Volatility presents ARCH and stochastic volatility models, with a focus on recent research topics including mean, volatility, and skewness spillovers in equity markets Other Models and Methods presents alternative approaches, such as multiplicative error models, nonparametric and semi-parametric models, and copula-based models of (co)volatilities Realized Volatility explores issues of the measurement of volatility by realized variances and covariances, guiding readers on how to successfully model and forecast these measures Handbook of Volatility Models and Their Applications is an essential reference for academics and practitioners in finance, business, and econometrics who work with volatility models in their everyday work. The book also serves as a supplement for courses on risk management and volatility at the upper-undergraduate and graduate levels.

Download or read book Log Normal Stochastic Volatility Model written by Artur Sepp and published by . This book was released on 2016 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt: While empirical studies have established that the log-normal stochastic volatility (SV) model is superior to its alternatives, the model does not allow for the analytical solutions available for affine models. To circumvent this, we show that the joint moment generating function (MGF) of the log-price and the quadratic variance (QV) under the log-normal SV model can be decomposed into a leading term, which is given by an exponential-affine form, and a residual term, whose estimate depends on the higher order moments of the volatility process. We prove that the second-order leading term is theoretically consistent with the expected values and covariance matrix of the log-price and the quadratic variance. We further extend this approach to the log-normal SV model with jumps. We use Fourier inversion techniques to value vanilla options on the equity and the QV and, by comparison to Monte Carlo simulations, we show that the second-order leading term is precise for the valuation of vanilla options. We generalize the affine decomposition to other non-affine stochastic volatility models with polynomial drift and volatility functions, and with jumps in the volatility process.

Download or read book Switching to Non Affine Stochastic Volatility written by Nicolas Langrené and published by . This book was released on 2016 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Three Essays in Theoretical and Empirical Derivative Pricing written by Hamed Ghanbari and published by . This book was released on 2017 with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first essay investigates the option-implied investor preferences by comparing equilibrium option pricing models under jump-diffusion to option bounds extracted from discrete-time stochastic dominance (SD). We show that the bounds converge to two prices that define an interval comparable to the observed option bid-ask spreads for S&P 500 index options. Further, the bounds' implied distributions exhibit tail risk comparable to that of the return data and thus shed light on the dark matter of the divergence between option-implied and underlying tail risks. Moreover, the bounds can better accommodate reasonable values of the ex-dividend expected excess return than the equilibrium models' prices. We examine the relative risk aversion coefficients compatible with the boundary distributions extracted from index return data. We find that the SD-restricted range of admissible RRA values is consistent with the macro-finance studies of the equity premium puzzle and with several anomalous results that have appeared in earlier option market studies.The second essay examines theoretically and empirically a two-factor stochastic volatility model. We adopt an affine two-factor stochastic volatility model, where aggregate market volatility is decomposed into two independent factors; a persistent factor and a transient factor. We introduce a pricing kernel that links the physical and risk neutral distributions, where investor's equity risk preference is distinguished from her variance risk preference. Using simultaneous data from the S&P 500 index and options markets, we find a consistent set of parameters that characterizes the index dynamics under physical and risk-neutral distributions. We show that the proposed decomposition of variance factors can be characterized by a different persistence and different sensitivity of the variance factors to the volatility shocks. We obtain negative prices for both variance factors, implying that investors are willing to pay for insurance against increases in volatility risk, even if those increases have little persistence. We also obtain negative correlations between shocks to the market returns and each volatility factor, where correlation is less significant in transient factor and therefore has a less significant effect on the index skewness. Our empirical results indicate that unlike stochastic volatility model, join restrictions do not lead to the poor performance of two-factor SV model, measured by Vega-weighted root mean squared errors.In the third essay, we develop a closed-form equity option valuation model where equity returns are related to market returns with two distinct systematic components; one of which captures transient variations in returns and the other one captures persistent variations in returns. Our proposed factor structure and closed-form option pricing equations yield separate expressions for the exposure of equity options to both volatility components and overall market returns. These expressions allow a portfolio manager to hedge her portfolio's exposure to the underlying risk factors. In cross-sectional analysis our model predicts that firms with higher transient beta have a steeper term structure of implied volatility and a steeper implied volatility moneyness slope. Our model also predicts that variances risk premiums have more significant effect on the equity option skew when the transient beta is higher. On the empirical front, for the firms listed on the Dow Jones index, our model provides a good fit to the observed equity option prices.

Download or read book Hedging in Affine Stochastic Volatility Models written by Richard Vierthauer and published by . This book was released on 2010 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Pricing Models of Volatility Products and Exotic Variance Derivatives written by Yue Kuen Kwok and published by CRC Press. This book was released on 2022-05-08 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pricing Models of Volatility Products and Exotic Variance Derivatives summarizes most of the recent research results in pricing models of derivatives on discrete realized variance and VIX. The book begins with the presentation of volatility trading and uses of variance derivatives. It then moves on to discuss the robust replication strategy of variance swaps using portfolio of options, which is one of the major milestones in pricing theory of variance derivatives. The replication procedure provides the theoretical foundation of the construction of VIX. This book provides sound arguments for formulating the pricing models of variance derivatives and establishes formal proofs of various technical results. Illustrative numerical examples are included to show accuracy and effectiveness of analytic and approximation methods. Features Useful for practitioners and quants in the financial industry who need to make choices between various pricing models of variance derivatives Fabulous resource for researchers interested in pricing and hedging issues of variance derivatives and VIX products Can be used as a university textbook in a topic course on pricing variance derivatives

Download or read book An Empirical Analysis of Stochastic Volatility Models written by Adrien-Paul Lambillon and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this paper is to explain and apply the stochastic volatility models of Heston and GARCH to model the S&P 500 index volatility. The maximum likelihood estimate of the CIR process in the volatility equation of the Heston model and GARCH(1,1) with different underlying distributions are compared. It is shown that the model with strongest mean reversion, the CIR model, is the best volatility estimation for the overall period. For periods of volatility clustering, however, GARCH models capture the behaviour more accurately.

Download or read book True Stochastic Volatility and a Generalized Class of Affine Models written by Pierre Collin-Dufresne and published by . This book was released on 2011 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most term structure models with stochastic volatility are restrictive in that they assume the risk in derivative securities can be perfectly hedged by a portfolio consisting solely of bonds. Below, we demonstrate that this prediction fails in practice. In particular, we find that the changes in the term structure of swap rates have scant explanatory power for the returns of at-the-money straddles (long cap and floor). To account for this observation, we introduce a parsimonious Heath-Jarrow-Morton (1990) term structure model with stochastic volatility that is consistent with this empirical finding. Closed-form solutions are obtained for bond-options, and thus cap- and floor-prices. We then identify a general class of models with a generalized affine-structure that significantly expands the class studied by Duffie, Pan, and Singleton (2000). Some special cases are investigated, including an arbitrage-free model of a long-rate, similar in spirit to that proposed by Brennan and Schwartz (1979, 1982).

Download or read book Affine Diffusion Modeling of Commodity Futures Price Term Structure written by and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Diffusion modeling of commodity price behavior is important for commodity risk management. This research seeks to improve upon the existing commodity diffusion models by incorporating stochastic volatility and seasonality through the affine diffusion framework. In particular, it evaluates affine diffusion models' performance at modeling commodity futures price term structure. Six affine diffusion models are studied in this research. They are one, two, three-factor Gaussian model and one, two, three-factor stochastic volatility model with a single stochastic volatility factor. Seasonality is modeled by allowing the forcing terms of the instantaneous drift and the instantaneous covariance to be seasonal. Model estimation is done through Q-MLE, for which the state variables are filtered through the Kalman Filter. To build the connection between affine diffusion models and known market regularities, affine state variables are interpreted. Factor interpretations used include the log of the spot price, a spot drift factor, and a spot variance factor. Empirical analysis covers models' performance at fitting and predicting futures price term structures; behavior of the interpretable models; and model stability. Empirical studies are applied to the corn and the unleaded gasoline markets. The following conclusions can be drawn from both markets: 1. For the purpose of modeling futures price dynamics alone, stochastic volatility models have no advantage over Gaussian models; 2. At least two factors are needed to adequately model commodity futures price term structures; the advantage of three-factor models, which is better capturing the curvature of the term structures, become evident under extreme market conditions; 3. State independent seasonality modeling is effective under most market conditions, but under extreme market conditions, seasonality can be mis-represented and it is the source of big measurement errors and prediction errors. 4. Two and three-factor affine diffusio.

Download or read book On Moment Non Explosions for Wishart Based Stochastic Volatility Models written by José Da Fonseca and published by . This book was released on 2018 with total page 15 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper provides a result on moment non-explosions for a stock following a Wishart multidimensional stochastic volatility dynamic or a Wishart affine stochastic correlation dynamic when the parameter values satisfy certain constraints. By reformulating the stock dynamic in terms of the volatility path along with standard results on matrix Lyapunov and Riccati equations, a non-explosion result of the moment of order greater than one can be obtained. It extends to these frameworks a property well known for the Heston model.