Download or read book Range based Covariance Estimation Using High frequency Data written by and published by . This book was released on 2008 with total page 41 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 High Frequency Covariance Matrix Estimation Using Price Durations written by Xiaolu Zhao and published by . This book was released on 2018 with total page 57 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose a price duration based covariance matrix estimator using high frequency transactions data. The effect of the last-tick time-synchronisation methodology, together with effects of important market microstructure components is analysed through a comprehensive Monte Carlo study. To decrease the number of negative eigenvalues produced by the non positive-semi-definite (psd) covariance matrix, we devise an average covariance estimator by taking an average of a wide range of duration based covariance matrix estimators. Empirically, candidate covariance estimators are implemented on 19 stocks from the DJIA. The duration based covariance estimator is shown to provide comparably accurate estimates with smaller variation compared with competing estimators. An out-of-sample GMV portfolio allocation problem is studied. A simple shrinkage technique is introduced to make the sample matrices psd and well-conditioned. Compared to competing high-frequency covariance matrix estimators, the duration based estimator is shown to give more stable portfolio weights and higher Sharpe ratios while maintaining comparably low portfolio variances.
Download or read book Handbook of Financial Econometrics and Statistics written by Cheng-Few Lee and published by Springer. This book was released on 2014-09-28 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Financial Econometrics and Statistics provides, in four volumes and over 100 chapters, a comprehensive overview of the primary methodologies in econometrics and statistics as applied to financial research. Including overviews of key concepts by the editors and in-depth contributions from leading scholars around the world, the Handbook is the definitive resource for both classic and cutting-edge theories, policies, and analytical techniques in the field. Volume 1 (Parts I and II) covers all of the essential theoretical and empirical approaches. Volumes 2, 3, and 4 feature contributed entries that showcase the application of financial econometrics and statistics to such topics as asset pricing, investment and portfolio research, option pricing, mutual funds, and financial accounting research. Throughout, the Handbook offers illustrative case examples and applications, worked equations, and extensive references, and includes both subject and author indices.
Download or read book Modelling and Forecasting High Frequency Financial Data written by Stavros Degiannakis and published by Springer. This book was released on 2016-04-29 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: The global financial crisis has reopened discussion surrounding the use of appropriate theoretical financial frameworks to reflect the current economic climate. There is a need for more sophisticated analytical concepts which take into account current quantitative changes and unprecedented turbulence in the financial markets. This book provides a comprehensive guide to the quantitative analysis of high frequency financial data in the light of current events and contemporary issues, using the latest empirical research and theory. It highlights and explains the shortcomings of theoretical frameworks and provides an explanation of high-frequency theory, emphasising ways in which to critically apply this knowledge within a financial context. Modelling and Forecasting High Frequency Financial Data combines traditional and updated theories and applies them to real-world financial market situations. It will be a valuable and accessible resource for anyone wishing to understand quantitative analysis and modelling in current financial markets.
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 High Dimensional Covariance Estimation written by Mohsen Pourahmadi and published by John Wiley & Sons. This book was released on 2013-06-24 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: Methods for estimating sparse and large covariance matrices Covariance and correlation matrices play fundamental roles in every aspect of the analysis of multivariate data collected from a variety of fields including business and economics, health care, engineering, and environmental and physical sciences. High-Dimensional Covariance Estimation provides accessible and comprehensive coverage of the classical and modern approaches for estimating covariance matrices as well as their applications to the rapidly developing areas lying at the intersection of statistics and machine learning. Recently, the classical sample covariance methodologies have been modified and improved upon to meet the needs of statisticians and researchers dealing with large correlated datasets. High-Dimensional Covariance Estimation focuses on the methodologies based on shrinkage, thresholding, and penalized likelihood with applications to Gaussian graphical models, prediction, and mean-variance portfolio management. The book relies heavily on regression-based ideas and interpretations to connect and unify many existing methods and algorithms for the task. High-Dimensional Covariance Estimation features chapters on: Data, Sparsity, and Regularization Regularizing the Eigenstructure Banding, Tapering, and Thresholding Covariance Matrices Sparse Gaussian Graphical Models Multivariate Regression The book is an ideal resource for researchers in statistics, mathematics, business and economics, computer sciences, and engineering, as well as a useful text or supplement for graduate-level courses in multivariate analysis, covariance estimation, statistical learning, and high-dimensional data analysis.
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 Estimating the Covariance Matrix from Unsynchronized High Frequency Financial Data Classic Reprint written by Bin Zhou and published by Forgotten Books. This book was released on 2018-02-23 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: Excerpt from Estimating the Covariance Matrix From Unsynchronized High Frequency Financial Data The estimation of the covariance matrix of financial prices is necessary in port folio optimization and risk management. Besides sample covariance, many other estimators have been proposed (stein 1975, Dey and Srinivasan However, estimating the covariance matrix from daily data can have serious problems. Jobson and Korkie (1980) indicated that, in some cases, it is better to use the identical matrix instead of the sample covariance matrix in the port folio selection. The problem is that the number of observations is not enough to estimate all entries of a big covariance matrix. To get around the problem, one may want to collect more data over longer time interval. However, the changing condition of markets may prevent us to do so. Another approach is to impose constrains on the covariance matrix to reduce the number of free parameters (frost and Savaino, The constrain may be subjective and not reflect the reality of the market. This paper explores another possibility of using high frequency data. Because of fast-growing computer power, data is now available in ultra - high frequency, such as tick-by - tick. Exchange rates, for example, can easily have over one million observations in one year. About the Publisher Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.
Download or read book Efficient Covariance Estimation for Asynchronous Noisy High frequency Data written by Markus Bibinger and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Conceptual Econometrics Using R written by and published by Elsevier. This book was released on 2019-08-20 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Conceptual Econometrics Using R, Volume 41 provides state-of-the-art information on important topics in econometrics, including quantitative game theory, multivariate GARCH, stochastic frontiers, fractional responses, specification testing and model selection, exogeneity testing, causal analysis and forecasting, GMM models, asset bubbles and crises, corporate investments, classification, forecasting, nonstandard problems, cointegration, productivity and financial market jumps and co-jumps, among others. Presents chapters authored by distinguished, honored researchers who have received awards from the Journal of Econometrics or the Econometric Society Includes descriptions and links to resources and free open source R, allowing readers to not only use the tools on their own data, but also jumpstart their understanding of the state-of-the-art
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 Estimating the Covariance Matrix from Unsynchronized High Frequency Financial Data written by Bin Zhou and published by . This book was released on 2001 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper proposes an estimator of the covariance matrix of currencies using unsynchronized and noisy high frequency observations. The estimator allows us to estimate the covariance matrix over a shorter time interval with more accuracy. The estimator is not f-consistent when there are so-called observation noises. Increasing observation frequency infinitely does not always increase the accuracy of the estimation. Optimal observation frequency is dependent on the ratio of the total volatility over the noise level. Daily covariance matrices of three exchange rates are calculated to demonstrate the methodology. The empirical results show that the correlations of the three currencies are strong but vary over time.
Download or read book Covariance Estimation in Dynamic Portfolio Optimization written by Lada M. Kyj and published by . This book was released on 2009 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt: Realized covariance estimation for large dimension problems is little explored and poses challenges in terms of computational burden and estimation error. In a global minimum volatility setting, we investigate the performance of covariance conditioning techniques applied to the realized covariance matrices of the 30 DJIA stocks. We find that not only is matrix conditioning necessary to deliver the benefits of high frequency data, but a single factor model, with a smoothed covariance estimate, outperforms the fully estimated realized covariance in one-step ahead forecasts. Furthermore, a mixed-frequency single-factor model - with factor coefficients estimated using low-frequency data and variances estimated using high-frequency data performs better than the realized single-factor estimator. The mixed-frequency model is not only parsimonious but it also avoids estimation of high-frequency covariances, an attractive feature for less frequently traded assets. Volatility dimension curves reveal that it is difficult to distinguish among estimators at low portfolio dimensions, but for well-conditioned estimators the performance gain relative to the benchmark 1/N portfolio increases with N.
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 Some Recent Developments in Statistical Theory and Applications written by Kuldeep Kumar and published by Universal-Publishers. This book was released on 2012 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is part of the proceedings of The International Conference on Recent Developments in Statistics, Econometrics and Forecasting 2010, which was organized to provide opportunities for academics and researchers to share their knowledge on recent developments in this area. The conference featured the most up-to-date research results and applications in statistics, econometrics and forecasting. The book has fifteen chapters contributed by different authors and can be divided into five parts: Time Series and Econometric Modeling, Linear Models, Non-parametrics, Statistical Applications and Statistical Methodology. This book will be helpful to graduate students, researchers and applied statisticians working in the area of time series, statistical and econometric modeling.
Download or read book Large Dimensional Factor Analysis written by Jushan Bai and published by Now Publishers Inc. This book was released on 2008 with total page 90 pages. Available in PDF, EPUB and Kindle. Book excerpt: Large Dimensional Factor Analysis provides a survey of the main theoretical results for large dimensional factor models, emphasizing results that have implications for empirical work. The authors focus on the development of the static factor models and on the use of estimated factors in subsequent estimation and inference. Large Dimensional Factor Analysis discusses how to determine the number of factors, how to conduct inference when estimated factors are used in regressions, how to assess the adequacy pf observed variables as proxies for latent factors, how to exploit the estimated factors to test unit root tests and common trends, and how to estimate panel cointegration models.
