Realized Variance in the Presence of Non-Iid Microstructure Noise

Realized Variance in the Presence of Non-Iid Microstructure Noise PDF Author: Bart Frijns
Publisher:
ISBN:
Category :
Languages : en
Pages : 38

Get Book Here

Book Description
It is a well known fact that at high sampling frequencies, the contamination of microstructure noise causes the Realized Variance to be a biased measure of the Integrated Variance. Recent developments in this field propose sampling on lower frequencies, sub-sampling techniques, or bias corrections using the autocorrelation patterns in the data. In this paper we propose a structural decomposition of the efficient price process and the microstructure noise. At the highest sampling frequency, we allow for potential correlation between the efficient price and the microstructure noise. For 20 actively traded stocks at Nasdaq, we find that the method provides a lower bound on Realized Variance. Applying a recently introduced bias correction reveals a very long persistence in transaction by transaction returns corrects the Realized Variance upwards to a level equal to low frequency Realized Variance. It remains questionable, however, whether this long persistence should be seen as microstructure noise, or is an inherent feature of the price process.

Realized Variance in the Presence of Non-Iid Microstructure Noise

Realized Variance in the Presence of Non-Iid Microstructure Noise PDF Author: Bart Frijns
Publisher:
ISBN:
Category :
Languages : en
Pages : 38

Get Book Here

Book Description
It is a well known fact that at high sampling frequencies, the contamination of microstructure noise causes the Realized Variance to be a biased measure of the Integrated Variance. Recent developments in this field propose sampling on lower frequencies, sub-sampling techniques, or bias corrections using the autocorrelation patterns in the data. In this paper we propose a structural decomposition of the efficient price process and the microstructure noise. At the highest sampling frequency, we allow for potential correlation between the efficient price and the microstructure noise. For 20 actively traded stocks at Nasdaq, we find that the method provides a lower bound on Realized Variance. Applying a recently introduced bias correction reveals a very long persistence in transaction by transaction returns corrects the Realized Variance upwards to a level equal to low frequency Realized Variance. It remains questionable, however, whether this long persistence should be seen as microstructure noise, or is an inherent feature of the price process.

Bias-correcting the Realized Range-based Variance in the Presence of Market Microstructure Noise

Bias-correcting the Realized Range-based Variance in the Presence of Market Microstructure Noise PDF Author: Kim Christensen
Publisher:
ISBN:
Category :
Languages : en
Pages :

Get Book Here

Book Description


Covariance Measurement in the Presence of Non-Synchronous Trading and Market Microstructure Noise

Covariance Measurement in the Presence of Non-Synchronous Trading and Market Microstructure Noise PDF Author: Jim E. Griffin
Publisher:
ISBN:
Category :
Languages : en
Pages : 25

Get Book Here

Book Description
This paper studies the problem of covariance estimation when prices are observed non-synchronously and contaminated by i.i.d. microstructure noise. We derive closed form expressions for the bias and variance of three popular covariance estimators, namely realised covariance, realised covariance plus lead- and lag-adjustments, and the Hayashi and Yoshida estimator, and present a comprehensive investigation into their properties and relative efficiency. Our main finding is that the ordering of the covariance estimators in terms of efficiency crucially depends on the level of microstructure noise, as well as the level of correlation. In fact, for sufficiently high levels of noise, the standard realised covariance estimator (without any corrections for non-synchronous trading) can be most efficient. We also propose a sparse sampling implementation of the Hayashi and Yoshida estimator, study the robustness of our findings using simulations with stochastic volatility and correlation, and highlight some important practical considerations.

Market Risk Analysis, Practical Financial Econometrics

Market Risk Analysis, Practical Financial Econometrics PDF Author: Carol Alexander
Publisher: John Wiley & Sons
ISBN: 0470998016
Category : Business & Economics
Languages : en
Pages : 437

Get Book Here

Book Description
Written by leading market risk academic, Professor Carol Alexander, Practical Financial Econometrics forms part two of the Market Risk Analysis four volume set. It introduces the econometric techniques that are commonly applied to finance with a critical and selective exposition, emphasising the areas of econometrics, such as GARCH, cointegration and copulas that are required for resolving problems in market risk analysis. The book covers material for a one-semester graduate course in applied financial econometrics in a very pedagogical fashion as each time a concept is introduced an empirical example is given, and whenever possible this is illustrated with an Excel spreadsheet. All together, the Market Risk Analysis four volume set illustrates virtually every concept or formula with a practical, numerical example or a longer, empirical case study. Across all four volumes there are approximately 300 numerical and empirical examples, 400 graphs and figures and 30 case studies many of which are contained in interactive Excel spreadsheets available from the the accompanying CD-ROM. Empirical examples and case studies specific to this volume include: Factor analysis with orthogonal regressions and using principal component factors; Estimation of symmetric and asymmetric, normal and Student t GARCH and E-GARCH parameters; Normal, Student t, Gumbel, Clayton, normal mixture copula densities, and simulations from these copulas with application to VaR and portfolio optimization; Principal component analysis of yield curves with applications to portfolio immunization and asset/liability management; Simulation of normal mixture and Markov switching GARCH returns; Cointegration based index tracking and pairs trading, with error correction and impulse response modelling; Markov switching regression models (Eviews code); GARCH term structure forecasting with volatility targeting; Non-linear quantile regressions with applications to hedging.

High-Frequency Financial Econometrics

High-Frequency Financial Econometrics PDF Author: Yacine Aït-Sahalia
Publisher: Princeton University Press
ISBN: 0691161437
Category : Business & Economics
Languages : en
Pages : 683

Get Book Here

Book Description
A comprehensive introduction to the statistical and econometric methods for analyzing high-frequency financial data High-frequency trading is an algorithm-based computerized trading practice that allows firms to trade stocks in milliseconds. Over the last fifteen years, the use of statistical and econometric methods for analyzing high-frequency financial data has grown exponentially. This growth has been driven by the increasing availability of such data, the technological advancements that make high-frequency trading strategies possible, and the need of practitioners to analyze these data. This comprehensive book introduces readers to these emerging methods and tools of analysis. Yacine Aït-Sahalia and Jean Jacod cover the mathematical foundations of stochastic processes, describe the primary characteristics of high-frequency financial data, and present the asymptotic concepts that their analysis relies on. Aït-Sahalia and Jacod also deal with estimation of the volatility portion of the model, including methods that are robust to market microstructure noise, and address estimation and testing questions involving the jump part of the model. As they demonstrate, the practical importance and relevance of jumps in financial data are universally recognized, but only recently have econometric methods become available to rigorously analyze jump processes. Aït-Sahalia and Jacod approach high-frequency econometrics with a distinct focus on the financial side of matters while maintaining technical rigor, which makes this book invaluable to researchers and practitioners alike.

Market Risk Analysis, Boxset

Market Risk Analysis, Boxset PDF Author: Carol Alexander
Publisher: John Wiley & Sons
ISBN: 0470997990
Category : Business & Economics
Languages : en
Pages : 1691

Get Book Here

Book Description
Market Risk Analysis is the most comprehensive, rigorous and detailed resource available on market risk analysis. Written as a series of four interlinked volumes each title is self-contained, although numerous cross-references to other volumes enable readers to obtain further background knowledge and information about financial applications. Volume I: Quantitative Methods in Finance covers the essential mathematical and financial background for subsequent volumes. Although many readers will already be familiar with this material, few competing texts contain such a complete and pedagogical exposition of all the basic quantitative concepts required for market risk analysis. There are six comprehensive chapters covering all the calculus, linear algebra, probability and statistics, numerical methods and portfolio mathematics that are necessary for market risk analysis. This is an ideal background text for a Masters course in finance. Volume II: Practical Financial Econometrics provides a detailed understanding of financial econometrics, with applications to asset pricing and fund management as well as to market risk analysis. It covers equity factor models, including a detailed analysis of the Barra model and tracking error, principal component analysis, volatility and correlation, GARCH, cointegration, copulas, Markov switching, quantile regression, discrete choice models, non-linear regression, forecasting and model evaluation. Volume III: Pricing, Hedging and Trading Financial Instruments has five very long chapters on the pricing, hedging and trading of bonds and swaps, futures and forwards, options and volatility as well detailed descriptions of mapping portfolios of these financial instruments to their risk factors. There are numerous examples, all coded in interactive Excel spreadsheets, including many pricing formulae for exotic options but excluding the calibration of stochastic volatility models, for which Matlab code is provided. The chapters on options and volatility together constitute 50% of the book, the slightly longer chapter on volatility concentrating on the dynamic properties the two volatility surfaces the implied and the local volatility surfaces that accompany an option pricing model, with particular reference to hedging. Volume IV: Value at Risk Models builds on the three previous volumes to provide by far the most comprehensive and detailed treatment of market VaR models that is currently available in any textbook. The exposition starts at an elementary level but, as in all the other volumes, the pedagogical approach accompanied by numerous interactive Excel spreadsheets allows readers to experience the application of parametric linear, historical simulation and Monte Carlo VaR models to increasingly complex portfolios. Starting with simple positions, after a few chapters we apply value-at-risk models to interest rate sensitive portfolios, large international securities portfolios, commodity futures, path dependent options and much else. This rigorous treatment includes many new results and applications to regulatory and economic capital allocation, measurement of VaR model risk and stress testing.

Handbook of Volatility Models and Their Applications

Handbook of Volatility Models and Their Applications PDF Author: Luc Bauwens
Publisher: John Wiley & Sons
ISBN: 0470872519
Category : Business & Economics
Languages : en
Pages : 566

Get Book Here

Book Description
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.

Handbook of Financial Time Series

Handbook of Financial Time Series PDF Author: Torben Gustav Andersen
Publisher: Springer Science & Business Media
ISBN: 3540712976
Category : Business & Economics
Languages : en
Pages : 1045

Get Book Here

Book Description
The Handbook of Financial Time Series gives an up-to-date overview of the field and covers all relevant topics both from a statistical and an econometrical point of view. There are many fine contributions, and a preamble by Nobel Prize winner Robert F. Engle.

Handbook of Volatility Models and Their Applications

Handbook of Volatility Models and Their Applications PDF Author: Luc Bauwens
Publisher: John Wiley & Sons
ISBN: 1118272056
Category : Business & Economics
Languages : en
Pages : 566

Get Book Here

Book Description
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.

Parameter Estimation in Stochastic Volatility Models

Parameter Estimation in Stochastic Volatility Models PDF Author: Jaya P. N. Bishwal
Publisher: Springer Nature
ISBN: 3031038614
Category : Mathematics
Languages : en
Pages : 634

Get Book Here

Book Description
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.