Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Download Stochastic Equity Volatility Related To The Leverage Effect full books in PDF, epub, and Kindle. Read online Stochastic Equity Volatility Related To The Leverage Effect ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Author : Alain Bensoussan
Publisher :
ISBN 13 : 9782854185287
Total Pages : 23 pages
Book Rating : 4.1/5 (852 download)
Download or read book Stochastic Equity Volatility Related to the Leverage Effect written by Alain Bensoussan and published by . This book was released on 1994 with total page 23 pages. Available in PDF, EPUB and Kindle. Book excerpt: Résumé en anglais
Author : Alain Bensoussan
Publisher :
ISBN 13 : 9782854185492
Total Pages : 34 pages
Book Rating : 4.1/5 (854 download)
Download or read book Stochastic Equity Volatility Related to the Leverage Effect II written by Alain Bensoussan and published by . This book was released on 1995 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Amaan Mehrabian
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (841 download)
Download or read book The Leverage Effect in Stochastic Volatility written by Amaan Mehrabian and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: A striking empirical feature of many financial time series is that when the price drops, the future volatility increases. This negative correlation between the financial return and future volatility processes was initially addressed in Black 76 and explained based on financial leverage, or a firm's debt-to-equity ratio: when the price drops, financial leverage increases, the firm becomes riskier, and hence, the future expected volatility increases. The phenomenon is, therefore, traditionally been named the leverage effect. In a discrete time Stochastic Volatility (SV) model framework, the leverage effect is often modelled by a negative correlation between the innovation processes of return and volatility equations. These models can be represented as state space models in which the returns and the volatilities are considered as the observed and the latent state variables respectively. Including the leverage effect in the SV model not only results in a better fit ...
Download or read book Research Report written by and published by . This book was released on 1998 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Hong Jiang
Publisher :
ISBN 13 :
Total Pages : 125 pages
Book Rating : 4.:/5 (915 download)
Download or read book A Stochastic Volatility Model with Leverage Effect and Regime Switching written by Hong Jiang and published by . This book was released on 2014 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Ionut Florescu
Publisher :
ISBN 13 :
Total Pages : 25 pages
Book Rating : 4.:/5 (13 download)
Download or read book A Study About the Existence of the Leverage Effect in Stochastic Volatility Models written by Ionut Florescu and published by . This book was released on 2018 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt: The empirical relationship between the return of an asset and the volatility of the asset has been well documented in the financial literature. Named the leverage e ffect or sometimes risk-premium effect, it is observed in real data that, when the return of the asset decreases, the volatility increases and vice-versa.Consequently, it is important to demonstrate that any formulated model for the asset price is capable to generate this eff ect observed in practice. Furthermore, we need to understand the conditions on the parameters present in the model that guarantee the apparition of the leverage effect. In this paper we analyze two general speci cations of stochastic volatility models and their capability of generating the perceived leverage effect. We derive conditions for the apparition of leverage e ffect in both of these stochastic volatility models. We exemplify using stochastic volatility models used in practice and we explicitly state the conditions for the existence of the leverage effect in these examples.
Author : Dinghai Xu
Publisher :
ISBN 13 :
Total Pages : 26 pages
Book Rating : 4.:/5 (837 download)
Download or read book Empirical Evidence of the Leverage Effect in a Stochastic Volatility Model written by Dinghai Xu and published by . This book was released on 2010 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Antoine Petrus Cornelius van der Ploeg
Publisher : Rozenberg Publishers
ISBN 13 : 9051705778
Total Pages : 358 pages
Book Rating : 4.0/5 (517 download)
Download or read book Stochastic volatility and the pricing of financial derivatives written by Antoine Petrus Cornelius van der Ploeg and published by Rozenberg Publishers. This book was released on 2006 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Ole Eiler Barndorff-Nielsen
Publisher :
ISBN 13 :
Total Pages : 18 pages
Book Rating : 4.:/5 (247 download)
Download or read book Incorporation of a Leverage Effect in a Stochastic Volatility Model written by Ole Eiler Barndorff-Nielsen and published by . This book was released on 1998 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Bent Jesper Christensen
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (837 download)
Download or read book The Risk-return Tradeoff and Leverage Effect in a Stochastic Volatility-in-mean Model written by Bent Jesper Christensen and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Eric Jacquier
Publisher :
ISBN 13 :
Total Pages : 31 pages
Book Rating : 4.:/5 (129 download)
Download or read book Bayesian Analysis of a Stochastic Volatility Model with Leverage Effect and Fat Tails written by Eric Jacquier and published by . This book was released on 2001 with total page 31 pages. Available in PDF, EPUB and Kindle. Book excerpt: The basic univariate stochastic volatility model specifies that conditional volatility follows a log-normal auto-regressive model with innovations assumed to be independent of the innovations in the conditional mean equation. Since the introduction of practical methods for inference in the basic volatility model (JPR-(1994)), it has been observed that the basic model is too restrictive for many financial series. We extend the basic SVOL to allow for a so-called quot;Leverage effectquot; via correlation between the volatility and mean innovations, and for fat-tails in the mean equation innovation. A Bayesian Markov Chain Monte Carlo algorithm is developed for the extended volatility model. Thus far, likelihood-based inference for the correlated SVOL model has not appeared in the literature. We develop Bayes Factors to assess the importance of the leverage and fat-tail extensions. Sampling experiments reveal little loss in precision from adding the model extensions but a large loss from using the basic model in the presence of mis-specification. For both equity and exchange rate data, there is overwhelming evidence in favor of models with fat-tailed volatility innovations, and for a leverage effect in the case of equity indices. We also find that volatility estimates from the extended model are markedly different from those produced by the basic SVOL.
Author : Stephen J. Taylor
Publisher : World Scientific
ISBN 13 : 9812770852
Total Pages : 297 pages
Book Rating : 4.8/5 (127 download)
Download or read book Modelling Financial Time Series written by Stephen J. Taylor and published by World Scientific. This book was released on 2008 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains several innovative models for the prices of financial assets. First published in 1986, it is a classic text in the area of financial econometrics. It presents ARCH and stochastic volatility models that are often used and cited in academic research and are applied by quantitative analysts in many banks. Another often-cited contribution of the first edition is the documentation of statistical characteristics of financial returns, which are referred to as stylized facts. This second edition takes into account the remarkable progress made by empirical researchers during the past two decades from 1986 to 2006. In the new Preface, the author summarizes this progress in two key areas: firstly, measuring, modelling and forecasting volatility; and secondly, detecting and exploiting price trends. Sample Chapter(s). Chapter 1: Introduction (1,134 KB). Contents: Features of Financial Returns; Modelling Price Volatility; Forecasting Standard Deviations; The Accuracy of Autocorrelation Estimates; Testing the Random Walk Hypothesis; Forecasting Trends in Prices; Evidence Against the Efficiency of Futures Markets; Valuing Options; Appendix: A Computer Program for Modelling Financial Time Series. Readership: Academic researchers in finance & economics; quantitative analysts.
Author : Jun Yu
Publisher :
ISBN 13 :
Total Pages : 18 pages
Book Rating : 4.:/5 (224 download)
Download or read book On Leverage in a Stochastic Volatility Model written by Jun Yu and published by . This book was released on 2004 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper is concerned with specification for modelling finanical leverage effect in the context of stochastic volatility models.
Author : Joann Jasiak
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (129 download)
Download or read book Stochastic Volatility and Time Deformation written by Joann Jasiak and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, we study stochastic volatility models with time deformation. Such processes relate to the early work by Mandelbrot and Taylor (1967), Clark (1973), Tauchen and Pitts (1983), among others. In our setup, the latent process of stochastic volatility evolves in an operational time which differs from calendar time. The time deformation can be determined by past volume of trade, past returns, possibly with an asymmetric leverage effect, and other variables setting the pace of information arrival. The econometric specification exploits the state-space approach for stochastic volatility models proposed by Harvey, Ruiz and Shephard (1994) as well as the matching moment estimation procedure using SNP densities of stock returns and trading volume estimated by Gallant, Rossi and Tauchen (1992). Daily data on returns and trading volume of the NYSE are used in the empirical application. Supporting evidence for a time deformation representation is found and its impact on the behavior of returns and volume is analyzed. We find that increases in volume accelerate operational time, resulting in volatility being less persistent and subject to shocks with a higher innovation variance. Downward price movements have similar effects while upward price movements increase the persistence in volatility and decrease the dispersion of shocks by slowing down market time. We present the basic model as well as several extensions; in particular, we formulate and estimate a bivariate return-volume stochastic volatility model with time deformation. The latter is examined through bivariate impulse response profiles following the example of Gallant, Rossi and Tauchen (1993).
Author : Christina Dan Wang
Publisher :
ISBN 13 :
Total Pages : 44 pages
Book Rating : 4.:/5 (13 download)
Download or read book The Estimation of Leverage Effect with High Frequency Data written by Christina Dan Wang and published by . This book was released on 2014 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage effect has become an extensively studied phenomenon which describes the negative relation between the stock return and its volatility. Although this characteristic of stock returns is well acknowledged, most studies about it are based on cross-sectional calibration with parametric models. Other than that, most previous work are over daily or longer return horizons and usually do not specify the quantitative measure of it. This paper provides nonparametric estimation of a class of stochastic measures of leverage effect for both cases with and without microstructure noise, and studies the statistical properties of the estimators when the log price process is a quite general continuous semimartingale, in the stochastic volatility context and for high frequency data. The consistency and limit distribution of the estimators are derived, and simulation results present the properties accordingly. This estimator also provides the opportunity to study the empirical relation between skewness and leverage effect, which further leads to the prediction of skewness. Furthermore, adopting similar ideas to these in this paper, it is easy to extend the study to other important aspects of the stock returns, e.g. volatility of volatility.
Author : Alireza Javaheri
Publisher : John Wiley & Sons
ISBN 13 : 1118943988
Total Pages : 325 pages
Book Rating : 4.1/5 (189 download)
Download or read book Inside Volatility Filtering written by Alireza Javaheri and published by John Wiley & Sons. This book was released on 2015-07-27 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: A new, more accurate take on the classical approach to volatility evaluation Inside Volatility Filtering presents a new approach to volatility estimation, using financial econometrics based on a more accurate estimation of the hidden state. Based on the idea of "filtering", this book lays out a two-step framework involving a Chapman-Kolmogorov prior distribution followed by Bayesian posterior distribution to develop a robust estimation based on all available information. This new second edition includes guidance toward basing estimations on historic option prices instead of stocks, as well as Wiener Chaos Expansions and other spectral approaches. The author's statistical trading strategy has been expanded with more in-depth discussion, and the companion website offers new topical insight, additional models, and extra charts that delve into the profitability of applied model calibration. You'll find a more precise approach to the classical time series and financial econometrics evaluation, with expert advice on turning data into profit. Financial markets do not always behave according to a normal bell curve. Skewness creates uncertainty and surprises, and tarnishes trading performance, but it's not going away. This book shows traders how to work with skewness: how to predict it, estimate its impact, and determine whether the data is presenting a warning to stay away or an opportunity for profit. Base volatility estimations on more accurate data Integrate past observation with Bayesian probability Exploit posterior distribution of the hidden state for optimal estimation Boost trade profitability by utilizing "skewness" opportunities Wall Street is constantly searching for volatility assessment methods that will make their models more accurate, but precise handling of skewness is the key to true accuracy. Inside Volatility Filtering shows you a better way to approach non-normal distributions for more accurate volatility estimation.
Author : Makoto Takahashi
Publisher : Springer Nature
ISBN 13 : 981990935X
Total Pages : 120 pages
Book Rating : 4.8/5 (199 download)
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.
