Download or read book Estimating Covariance Via Fourier Method in the Presence of Asynchronous Trading and Microstructure Noise written by Maria Elvira Mancino and published by . This book was released on 2013 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt: We analyze the effects of market microstructure noise on the Fourier estimator of multivariate volatilities. We prove that the estimator is consistent in the case of asynchronous data and robust in the presence of microstructure noise. This result is obtained through an analytical computation of the bias and the mean squared error of the Fourier estimator and confirmed by Monte Carlo experiments.

Download or read book Fourier Malliavin Volatility Estimation written by Maria Elvira Mancino and published by Springer. This book was released on 2017-03-01 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is a user-friendly presentation of the main theoretical properties of the Fourier-Malliavin volatility estimation, allowing the readers to experience the potential of the approach and its application in various financial settings. Readers are given examples and instruments to implement this methodology in various financial settings and applications of real-life data. A detailed bibliographic reference is included to permit an in-depth study.

Download or read book Financial Econometrics Modeling Market Microstructure Factor Models and Financial Risk Measures written by G. Gregoriou and published by Springer. This book was released on 2010-12-13 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book proposes new methods to build optimal portfolios and to analyze market liquidity and volatility under market microstructure effects, as well as new financial risk measures using parametric and non-parametric techniques. In particular, it investigates the market microstructure of foreign exchange and futures markets.

Download or read book Covariance Estimation and Dynamic Asset Allocation Under Microstructure Effects Via Fourier Methodology written by Simona Sanfelici and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We analyze the properties of different estimators of multivariate volatilities in the presence of microstructure noise, with particular focus on the Fourier estimator. This estimator is consistent in the case of asynchronous data and robust to microstructure effects; further we prove the positive semi-definiteness of the estimated covariance matrix. The in sample and forecasting properties of Fourier method are analyzed through Monte Carlo simulations. We study the economic benefit of applying the Fourier covariance estimation methodology over other estimators in the presence of market microstructure noise from the perspective of an asset-allocation decision problem. We find that using Fourier methodology yields statistically significant economic gains under strong microstructure effects.

Download or read book Quantitative Trading written by Xin Guo and published by CRC Press. This book was released on 2017-01-06 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first part of this book discusses institutions and mechanisms of algorithmic trading, market microstructure, high-frequency data and stylized facts, time and event aggregation, order book dynamics, trading strategies and algorithms, transaction costs, market impact and execution strategies, risk analysis, and management. The second part covers market impact models, network models, multi-asset trading, machine learning techniques, and nonlinear filtering. The third part discusses electronic market making, liquidity, systemic risk, recent developments and debates on the subject.

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.

Download or read book High Frequency Financial Econometrics written by Yacine Aït-Sahalia and published by Princeton University Press. This book was released on 2014-07-21 with total page 683 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

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 2012-04-17 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 Covariance Measurement in the Presence of Non Synchronous Trading and Market Microstructure Noise written by Jim E. Griffin and published by . This book was released on 2010 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Multivariate Volatility Estimation with High Frequency Data Using Fourier Method written by Maria Elvira Mancino and published by . This book was released on 2013 with total page 53 pages. Available in PDF, EPUB and Kindle. Book excerpt: Availability of high frequency data has improved the capability of computing volatility in an efficient way. Nevertheless, measuring volatility/covariance from the observation of the asset price is challenging for two main reasons: observed asset prices are generally affected by noise microstructure effects and tick-by-tick returns are asynchronous across different assets. In this paper we review the definition and the statistical properties of the so called Fourier estimator of multivariate volatility, with particular focus on using high frequency data. Exploiting the fact that the method allows to compute both the integrated and the instantaneous volatility, we show how to obtain estimators of the volatility of the volatility and the leverage as well. Further, we study the performance of the estimator in forecasting and in terms of portfolio utility in the presence of microstructure noise contaminations.

Download or read book Estimating Covariation written by Lan Zhang and published by . This book was released on 2008 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper is about how to estimate the integrated covariance lt;X, Ygt;_T of two price processes over a fixed time horizon [0, T], when the observations about X and Y are contaminated and when such noisy observations are at discrete, but not synchronized, times. We show that the usual covariance estimator is biased, and the size of the bias is more pronounced for less liquid assets. We also provide optimal sampling frequency which balances the tradeoff between the bias and various sources of stochastic error terms, including nonsynchronous trading, microstructure noise, and time discretization.

Download or read book A Bayesian High Frequency Estimator of the Multivariate Covariance of Noisy and Asynchronous Returns written by Stefano Peluso and published by . This book was released on 2014 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: A multivariate positive definite estimator of the integrated covariance matrix of noisy and asynchronously observed asset returns is proposed. We adopt a Bayesian Dynamic Linear Model where microstructure noise is interpreted as measurement error, and asynchronous trading as missing observations in an otherwise synchronous series. Missing observations are treated as any other parameter, as typical in a Bayesian framework. An augmented Gibbs algorithm is used since all full conditionals are available and its convergence and robustness are discussed. A realistic simulation study compares our estimator with existing alternatives, under different liquidity and microstructure noise conditions. The results suggest that our estimator is superior in terms of RMSE particularly under severe conditions, such as portfolios of assets with heterogeneous liquidity and high level of microstructure noise. The application to the empirical dataset of ten tick-by-tick stock price series confirms the simulation results.

Download or read book Integrated Covariance Estimation Using High Frequency Data in the Presence of Noise written by Valeri Voev and published by . This book was released on 2006 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: We analyze the effects of non-synchronicity and market microstructure noise on realized covariance type estimators. It is shown that non-synchronicity leads to severe biases, whenever synchronization methods that employ last-tick interpolation are used. We study a simple estimator which resolves that problem and is unbiased and consistent for the integrated covariance in the absence of noise. When noise is present, however, we show that this estimator is biased and suggest a simple bias correction procedure. Furthermore, a subsampling version of the estimator is proposed, which could improve its efficiency. Finally, a simulation experiment is carried out to illustrate the theoretical results.

Download or read book Missing in Asynchronicity written by Fulvio Corsi and published by . This book was released on 2012 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A No arbitrage Approach to Range based Estimation of Return Covariances and Correlations written by Michael W. Brandt and published by . This book was released on 2005 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Blocking and Regularization Approach to High Dimensional Realized Covariance Estimation written by Nikolaus Hautsch and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Knowing Factors Or Factor Loadings Or Neither Evaluating Estimators of Large Covariance Matrices with Noisy and Asynchronous Data written by Chaoxing Dai and published by . This book was released on 2017 with total page 61 pages. Available in PDF, EPUB and Kindle. Book excerpt: We investigate estimators of factor-model-based large covariance (and precision) matrices using high-frequency data, which are asynchronous and potentially contaminated by the market microstructure noise. Our estimation strategies rely on the pre-averaging method with refresh time to solve the microstructure problems, while using three different specifications of factor models with a variety of thresholding methods, respectively, to battle the curse of dimensionality. To estimate a factor model, we either adopt the time-series regression (TSR) to recover loadings if factors are known, or use the cross-sectional regression (CSR) to recover factors from known loadings, or use the principal component analysis (PCA) if neither factors nor their loadings are assumed known. We compare the convergence rates in these scenarios using the joint in-fill and increasing dimensionality asymptotics. To evaluate the empirical trade-off between robustness to model misspecification and statistical efficiency among all 30 combinations of estimation strategies, we run a horse race on the out-of-sample portfolio allocation with Dow Jones 30, S&P 100, and S&P 500 index constituents, respectively, and find the pre-averaging-based strategy using TSR or PCA with location thresholding dominates, especially over the subsampling-based alternatives.