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Author : Ana Perez Espartero
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (14 download)
Download or read book Estimation and identification in long-memory stochastic volatility models written by Ana Perez Espartero and published by . This book was released on 2000 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Libo Xie
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (144 download)
Download or read book Long-memory Stochastic Volatility Models written by Libo Xie and published by . This book was released on 2008 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Zhigang Tong
Publisher : LAP Lambert Academic Publishing
ISBN 13 : 9783659346279
Total Pages : 184 pages
Book Rating : 4.3/5 (462 download)
Download or read book Option Pricing with Long Memory Stochastic Volatility Models written by Zhigang Tong and published by LAP Lambert Academic Publishing. This book was released on 2013 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is now known that long memory stochastic volatility models can capture the well-documented evidence of volatility persistence. However, due to the complex structures of the long memory processes, the analytical formulas for option prices are not available yet. In this book, we propose two fractional continuous time stochastic volatility models which are built on the popular short memory stochastic volatility models. Using the tools from stochastic calculus, fractional calculus and Fourier transform, we derive the (approximate) analytical solutions for option prices. We also numerically study the effects of long memory on option prices. We show that the fractional integration parameter has the opposite effect to that of volatility of volatility parameter. We also find that long memory models can accommodate the short term options and the decay of volatility skew better than the corresponding short memory models. These findings would appeal to the researchers and practitioners in the areas of quantitative finance.
Author : Centre de recherche en économie et statistique (Paris, France)
Publisher :
ISBN 13 :
Total Pages : 54 pages
Book Rating : 4.:/5 (467 download)
Download or read book Long Memory in Continuous Time written by Centre de recherche en économie et statistique (Paris, France) and published by . This book was released on 1996 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Kai Li
Publisher :
ISBN 13 :
Total Pages : 35 pages
Book Rating : 4.:/5 (247 download)
Download or read book On Estimation, Diagnostic Testing and Smoothing of Long Memory Stochastic Volatility Models written by Kai Li and published by . This book was released on 2000 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Zhigang Tong
Publisher :
ISBN 13 : 9780494862469
Total Pages : pages
Book Rating : 4.8/5 (624 download)
Download or read book Option Pricing with Long Memory Stochastic Volatility Models written by Zhigang Tong and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, we propose two continuous time stochastic volatility models with long memory that generalize two existing models. More importantly, we provide analytical formulae that allow us to study option prices numerically, rather than by means of simulation. We are not aware about analytical results in continuous time long memory case. In both models, we allow for the non-zero correlation between the stochastic volatility and stock price processes. We numerically study the effects of long memory on the option prices. We show that the fractional integration parameter has the opposite effect to that of volatility of volatility parameter in short memory models. We also find that long memory models have the potential to accommodate the short term options and the decay of volatility skew better than the corresponding short memory stochastic volatility models.
Author : Shelton Peiris
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (953 download)
Download or read book Estimating and Forecasting Generalized Fractional Long Memory Stochastic Volatility Models written by Shelton Peiris and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Jaya P. N. Bishwal
Publisher : Springer Nature
ISBN 13 : 3031038614
Total Pages : 634 pages
Book Rating : 4.0/5 (31 download)
Download or read book Parameter Estimation in Stochastic Volatility Models written by Jaya P. N. Bishwal and published by Springer Nature. This book was released on 2022-08-06 with total page 634 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book develops alternative methods to estimate the unknown parameters in stochastic volatility models, offering a new approach to test model accuracy. While there is ample research to document stochastic differential equation models driven by Brownian motion based on discrete observations of the underlying diffusion process, these traditional methods often fail to estimate the unknown parameters in the unobserved volatility processes. This text studies the second order rate of weak convergence to normality to obtain refined inference results like confidence interval, as well as nontraditional continuous time stochastic volatility models driven by fractional Levy processes. By incorporating jumps and long memory into the volatility process, these new methods will help better predict option pricing and stock market crash risk. Some simulation algorithms for numerical experiments are provided.
Author : Alejandro Islas Camargo
Publisher :
ISBN 13 :
Total Pages : 56 pages
Book Rating : 4.:/5 (51 download)
Download or read book Long Memory Stochastic Volatility Models of Latin American Stock Markets written by Alejandro Islas Camargo and published by . This book was released on 2000 with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Frederi G. Viens
Publisher : John Wiley & Sons
ISBN 13 : 0470876883
Total Pages : 468 pages
Book Rating : 4.4/5 (78 download)
Download or read book Handbook of Modeling High-Frequency Data in Finance written by Frederi G. Viens and published by John Wiley & Sons. This book was released on 2011-12-20 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: CUTTING-EDGE DEVELOPMENTS IN HIGH-FREQUENCY FINANCIAL ECONOMETRICS In recent years, the availability of high-frequency data and advances in computing have allowed financial practitioners to design systems that can handle and analyze this information. Handbook of Modeling High-Frequency Data in Finance addresses the many theoretical and practical questions raised by the nature and intrinsic properties of this data. A one-stop compilation of empirical and analytical research, this handbook explores data sampled with high-frequency finance in financial engineering, statistics, and the modern financial business arena. Every chapter uses real-world examples to present new, original, and relevant topics that relate to newly evolving discoveries in high-frequency finance, such as: Designing new methodology to discover elasticity and plasticity of price evolution Constructing microstructure simulation models Calculation of option prices in the presence of jumps and transaction costs Using boosting for financial analysis and trading The handbook motivates practitioners to apply high-frequency finance to real-world situations by including exclusive topics such as risk measurement and management, UHF data, microstructure, dynamic multi-period optimization, mortgage data models, hybrid Monte Carlo, retirement, trading systems and forecasting, pricing, and boosting. The diverse topics and viewpoints presented in each chapter ensure that readers are supplied with a wide treatment of practical methods. Handbook of Modeling High-Frequency Data in Finance is an essential reference for academics and practitioners in finance, business, and econometrics who work with high-frequency data in their everyday work. It also serves as a supplement for risk management and high-frequency finance courses at the upper-undergraduate and graduate levels.
Author : Mark J. Jensen
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (137 download)
Download or read book Bayesian Inference of Long-Memory Stochastic Volatility Via Wavelets written by Mark J. Jensen and published by . This book was released on 2001 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper we are concerned with estimating the fractional order of integration associated with a long-memory stochastic volatility model. We develop a new Bayesian estimator based on the Markov chain Monte Carlo sampler and the wavelet representation of the log-squared returns to draw values of the fractional order of integration and latent volatilities from their joint posterior distribution. Unlike short-memory stochastic volatility models, long-memory stochastic volatility models do not have a state-space representation, and thus their sampler cannot employ the Kalman filters simulation smoother to update the chain of latent volatilities. Instead, we design a simulator where the latent long-memory volatilities are drawn quickly and efficiently from the near independent multivariate distribution of the long-memory volatility's wavelet coefficients. We find that sampling volatility in the wavelet domain, rather than in the time domain, leads to a fast and simulation-efficient sampler of the posterior distribution for the volatility's long-memory parameter and serves as a promising alternative estimator to the existing frequentist based estimators of long-memory volatility.
Author : Mark J. Jensen
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (137 download)
Download or read book Semiparametric Bayesian Inference of Long-Memory Stochastic Volatility Models written by Mark J. Jensen and published by . This book was released on 2004 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, a semiparametric, Bayesian estimator of the long-memory stochastic volatility model's fractional order of integration is presented. This new estimator relies on a highly efficient, Markov chain Monte Carlo (MCMC) sampler of the model's posterior distribution. The MCMC algorithm is set forth in the time-scale domain of the stochastic volatility model's wavelet representation. The key to and centerpiece of this new algorithm is the quick and efficient multi-state sampler of the latent volatility's wavelet coefficients. A multi-state sampler of the latent wavelet coefficients is only possible because of the near-independent multivariate distribution of the long-memory process's wavelet coefficients. Using simulated and empirical stock return data, we find that our algorithm produces uncorrelated draws of the posterior distribution and point estimates that rival existing long-memory stochastic volatility estimators.
Author : Per Skaarup Frederiksen
Publisher :
ISBN 13 :
Total Pages : 17 pages
Book Rating : 4.:/5 (129 download)
Download or read book Bias-Reduced Estimation of Long Memory Stochastic Volatility written by Per Skaarup Frederiksen and published by . This book was released on 2008 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose to use a variant of the local polynomial Whittle estimator to estimate the memory parameter in volatility for long memory stochastic volatility models with potential nonstationarity in the volatility process. We show that the estimator is asymptotically normal and capable of obtaining bias reduction as well as a rate of convergence arbitrarily close to the parametric rate, n1=2. A Monte Carlo study is conducted to support the theoretical results, and an analysis of daily exchange rates demonstrates the empirical usefulness of the estimators.
Author : Susanna Wing Yan Kwok
Publisher :
ISBN 13 :
Total Pages : 240 pages
Book Rating : 4.:/5 (49 download)
Download or read book A Multivariate Long Memory Stochastic Volatility Model with Applications to Financial Markets written by Susanna Wing Yan Kwok and published by . This book was released on 2001 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Manabu Asai
Publisher :
ISBN 13 :
Total Pages : 27 pages
Book Rating : 4.:/5 (13 download)
Download or read book Realized Stochastic Volatility Models with Generalized Gegenbauer Long Memory written by Manabu Asai and published by . This book was released on 2017 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years fractionally differenced processes have received a great deal of attention due to their flexibility in financial applications with long memory. In this paper, we develop a new realized stochastic volatility (RSV) model with general Gegenbauer long memory (GGLM), which encompasses a new RSV model with seasonal long memory (SLM). The RSV model uses the information from returns and realized volatility measures simultaneously. The long memory structure of both models can describe unbounded peaks apart from the origin in the power spectrum. For estimating the RSV-GGLM model, we suggest estimating the location parameters for the peaks of the power spectrum in the first step, and the remaining parameters based on the Whittle likelihood in the second step. We conduct Monte Carlo experiments for investigating the finite sample properties of the estimators, with a quasi-likelihood ratio test of RSV-SLM model against the RSV-GGLM model. We apply the RSV-GGLM and RSV-SLM model to three stock market indices. The estimation and forecasting results indicate the adequacy of considering general long memory.
Author : Adam McCloskey
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (137 download)
Download or read book Estimation of the Long-Memory Stochastic Volatility Model Parameters that is Robust to Level Shifts and Deterministic Trends written by Adam McCloskey and published by . This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: I provide conditions under which the trimmed FDQML estimator, advanced by McCloskey (2010) in the context of fully parametric short-memory models, can be used to estimate the long-memory stochastic volatility model parameters in the presence of additive low-frequency contamination in log-squared returns. The types of low-frequency contamination covered include level shifts as well as deterministic trends. I establish consistency and asymptotic normality in the presence or absence of such low-frequency contamination under certain conditions on the growth rate of the trimming parameter. I also provide theoretical guidance on the choice of trimming parameter by heuristically obtaining its asymptotic MSE-optimal rate under certain types of low-frequency contamination. A simulation study examines the finite sample properties of the robust estimator, showing substantial gains from its use in the presence of level shifts. The finite sample analysis also explores how different levels of trimming affect the parameter estimates in the presence and absence of low-frequency contamination and long-memory.
Author : Pedro J. F. De Lima
Publisher :
ISBN 13 :
Total Pages : 23 pages
Book Rating : 4.:/5 (476 download)
Download or read book Modeling Long-memory Stochastic Volatility written by Pedro J. F. De Lima and published by . This book was released on 1994 with total page 23 pages. Available in PDF, EPUB and Kindle. Book excerpt:
