Modeling and Forecasting Daily Stock Return Volatility with Intra-day Price Fluctuation Information PDF Download

Author: Yansong Lu
Publisher:
ISBN:
Category :
Languages : en
Pages : 107

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Author: Michiel de Pooter
Publisher: Rozenberg Publishers
ISBN: 9051709153
Category :
Languages : en
Pages : 286

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This dissertation consists of a collection of studies on two areas in quantitative finance: asset return volatility and the term structure of interest rates. The first part of this dissertation offers contributions to the literature on how to test for sudden changes in unconditional volatility, on modelling realized volatility and on the choice of optimal sampling frequencies for intraday returns. The emphasis in the second part of this dissertation is on the term structure of interest rates.

Author: Ana-Maria Fuertes
Publisher:
ISBN:
Category :
Languages : en
Pages : 72

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Several recent studies advocate the use of nonparametric estimators of daily price variability that exploit intraday information. This paper compares four such estimators, realised volatility, realised range, realised power variation and realised bipower variation, by examining their in-sample distributional properties and out-of-sample forecast ranking when the object of interest is the conventional conditional variance. The analysis is based on a 7-year sample of transaction prices for 14 NYSE stocks. The forecast race is conducted in a GARCH framework and relies on several loss functions. The realized range fares relatively well in the in-sample fit analysis, for instance, regarding the extent to which it brings normality in returns. However, overall the realised power variation provides the most accurate 1-day-ahead forecasts. Forecast combination of all four intraday measures produces the smallest forecast errors in about half of the sampled stocks. A market conditions analysis reveals that the additional use of intraday data on day t-1 to forecast volatility on day t is most advantageous when day t is a low volume or an up-market day. The results have implications for value-at-risk analysis.

Author: Dexiang Mei
Publisher: Scientific Research Publishing, Inc. USA
ISBN: 164997048X
Category : Business & Economics
Languages : en
Pages : 139

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The volatility has been one of the cores of the financial theory research, in addition to the stock markets and the futures market are an important part of modern financial markets. Forecast volatility of the stock market and oil futures market is an important part of the theory of financial markets research.

Author: Xuna Gao
Publisher:
ISBN:
Category : Econometric models
Languages : en
Pages : 162

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The purpose of this study is to investigate stock volatility and forecasting performance of different volatility models over high-frequency intervals. The multiplicative component model that decomposes the conditional variance into a daily component and a periodicity component is studied with different specifications. This model is applied to 30 stocks. For the daily component, both parametric and non-parametric measures are considered. 12 models that capture the long memory feature of volatility are examined. Our results show the HAR-MEM model with overnight jump and the HAR-MEM model have the best forecasting performance among 12 models, and adding an overnight return term improves model's forecasting ability. Periodicity component is captured by the proportion of summation of intraday volatility to summation of daily volatility over some time period. In comparison with the literature, our specification of periodicity component has slightly better forecasting performance in the first 2-hour volatility.

Author: Jeremias Bekierman
Publisher:
ISBN:
Category :
Languages : en
Pages :

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We propose a mixed frequency stochastic volatility (MFSV) model for the dynamics of intraday asset return volatility. In order to account for long-memory we separate stochastic daily and intraday volatility patterns by introducing a long-run component that changes at daily frequency and a short-run component that captures the remaining intraday volatility dynamics. An additional component captures deterministic intraday patterns. We analyze the stochastic properties of the resulting non-linear state-space model both on the daily and the intraday frequency and show how the model can be estimated in a single step using simulated maximum likelihood based on Efficient Importance Sampling (EIS). We apply the model to intraday returns of five New York Stock Exchange traded stocks. The estimation results indicate distinct dynamic patterns for daily and intradaily volatility components, where about 50% of intraday volatility dynamics are explained by the daily component. In-sample diagnostic tests and an out-of-sample forecasting experiment indicate that already the very basic model specification successfully accounts for the complex dynamic and distributional properties of asset returns both on the intraday and the daily frequency.

Author: Xingyi Li
Publisher:
ISBN:
Category :
Languages : en
Pages : 33

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Book Description
There is evidence that volatility forecasting models that use intraday data provide better forecast accuracy as compared with that delivered by the models that use daily data. Exactly how much better is still unknown. The present paper fills this gap in the literature and extends previous studies on forecasting stock market volatility in several important directions. First, we employ an extensive set of intraday data on 31 individual stocks over a sample period of 19 years. Second, we use forecast horizons ranging from 1 day to 6 months. Third, we evaluate the precision of volatility forecast provided by various competing models. Fourth, we conduct several robustness checks to assess the sensitivity of our results to various alternative choices. The major finding of our empirical study is that the gains from using intraday data are rather significant and persist over longer forecast horizons. Depending on the forecast horizon, the improvement in forecast precision varies from 30 to 50 percent. We demonstrate that our main results on the forecast accuracy gains are robust to the choice of intraday data frequency and the choice of measure of realized daily volatility.

Author: Luc Bauwens
Publisher: Springer Science & Business Media
ISBN: 147573381X
Category : Business & Economics
Languages : en
Pages : 192

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Book Description
Over the past 25 years, applied econometrics has undergone tremen dous changes, with active developments in fields of research such as time series, labor econometrics, financial econometrics and simulation based methods. Time series analysis has been an active field of research since the seminal work by Box and Jenkins (1976), who introduced a gen eral framework in which time series can be analyzed. In the world of financial econometrics and the application of time series techniques, the ARCH model of Engle (1982) has shifted the focus from the modelling of the process in itself to the modelling of the volatility of the process. In less than 15 years, it has become one of the most successful fields of 1 applied econometric research with hundreds of published papers. As an alternative to the ARCH modelling of the volatility, Taylor (1986) intro duced the stochastic volatility model, whose features are quite similar to the ARCH specification but which involves an unobserved or latent component for the volatility. While being more difficult to estimate than usual GARCH models, stochastic volatility models have found numerous applications in the modelling of volatility and more particularly in the econometric part of option pricing formulas. Although modelling volatil ity is one of the best known examples of applied financial econometrics, other topics (factor models, present value relationships, term structure 2 models) were also successfully tackled.

Author: Riccardo Rebonato
Publisher: John Wiley & Sons
ISBN: 0470091401
Category : Business & Economics
Languages : en
Pages : 864

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Book Description
In Volatility and Correlation 2nd edition: The Perfect Hedger and the Fox, Rebonato looks at derivatives pricing from the angle of volatility and correlation. With both practical and theoretical applications, this is a thorough update of the highly successful Volatility & Correlation – with over 80% new or fully reworked material and is a must have both for practitioners and for students. The new and updated material includes a critical examination of the ‘perfect-replication’ approach to derivatives pricing, with special attention given to exotic options; a thorough analysis of the role of quadratic variation in derivatives pricing and hedging; a discussion of the informational efficiency of markets in commonly-used calibration and hedging practices. Treatment of new models including Variance Gamma, displaced diffusion, stochastic volatility for interest-rate smiles and equity/FX options. The book is split into four parts. Part I deals with a Black world without smiles, sets out the author’s ‘philosophical’ approach and covers deterministic volatility. Part II looks at smiles in equity and FX worlds. It begins with a review of relevant empirical information about smiles, and provides coverage of local-stochastic-volatility, general-stochastic-volatility, jump-diffusion and Variance-Gamma processes. Part II concludes with an important chapter that discusses if and to what extent one can dispense with an explicit specification of a model, and can directly prescribe the dynamics of the smile surface. Part III focusses on interest rates when the volatility is deterministic. Part IV extends this setting in order to account for smiles in a financially motivated and computationally tractable manner. In this final part the author deals with CEV processes, with diffusive stochastic volatility and with Markov-chain processes. Praise for the First Edition: “In this book, Dr Rebonato brings his penetrating eye to bear on option pricing and hedging.... The book is a must-read for those who already know the basics of options and are looking for an edge in applying the more sophisticated approaches that have recently been developed.” —Professor Ian Cooper, London Business School “Volatility and correlation are at the very core of all option pricing and hedging. In this book, Riccardo Rebonato presents the subject in his characteristically elegant and simple fashion...A rare combination of intellectual insight and practical common sense.” —Anthony Neuberger, London Business School

Author: George M. Constantinides
Publisher: Newnes
ISBN: 0444594655
Category : Business & Economics
Languages : en
Pages : 1732

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Book Description
This two-volume set of 23 articles authoritatively describes recent scholarship in corporate finance and asset pricing. Volume 1 concentrates on corporate finance, encompassing topics such as financial innovation and securitization, dynamic security design, and family firms. Volume 2 focuses on asset pricing with articles on market liquidity, credit derivatives, and asset pricing theory, among others. Both volumes present scholarship about the 2008 financial crisis in contexts that highlight both continuity and divergence in research. For those who seek insightful perspectives and important details, they demonstrate how corporate finance studies have interpreted recent events and incorporated their lessons. Covers core and newly-developing fields Explains how the 2008 financial crises affected theoretical and empirical research Exposes readers to a wide range of subjects described and analyzed by the best scholars