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Statistical Models and Methods for Financial Markets / by Tze Leung Lai, Haipeng Xing
(Springer Texts in Statistics. ISSN:21974136)

1st ed. 2008.
出版者 (New York, NY : Springer New York : Imprint: Springer)
出版年 2008
本文言語 英語
大きさ XX, 356 p : online resource
著者標目 *Lai, Tze Leung author
Xing, Haipeng author
SpringerLink (Online service)
件 名 LCSH:Finance, Public
LCSH:Probabilities
LCSH:Statistics 
LCSH:Social sciences -- Mathematics  全ての件名で検索
FREE:Public Economics
FREE:Probability Theory
FREE:Statistics in Business, Management, Economics, Finance, Insurance
FREE:Mathematics in Business, Economics and Finance
一般注記 Basic Statistical Methods and Financial Applications -- Linear Regression Models -- Multivariate Analysis and Likelihood Inference -- Basic Investment Models and Their Statistical Analysis -- Parametric Models and Bayesian Methods -- Time Series Modeling and Forecasting -- Dynamic Models of Asset Returns and Their Volatilities -- Advanced Topics in Quantitative Finance -- Nonparametric Regression and Substantive-Empirical Modeling -- Option Pricing and Market Data -- Advanced Multivariate and Time Series Methods in Financial Econometrics -- Interest Rate Markets -- Statistical Trading Strategies -- Statistical Methods in Risk Management
This book presents statistical methods and models of importance to quantitative finance and links finance theory to market practice via statistical modeling and decision making. Part I provides basic background in statistics, which includes linear regression and extensions to generalized linear models and nonlinear regression, multivariate analysis, likelihood inference and Bayesian methods, and time series analysis. It also describes applications of these methods to portfolio theory and dynamic models of asset returns and their volatilities. Part II presents advanced topics in quantitative finance and introduces a substantive-empirical modeling approach to address the discrepancy between finance theory and market data. It describes applications to option pricing, interest rate markets, statistical trading strategies, and risk management. Nonparametric regression, advanced multivariate and time series methods in financial econometrics, and statistical models for high-frequency transactions data are also introduced in this connection. The book has been developed as a textbook for courses on statistical modeling in quantitative finance in master's level financial mathematics (or engineering) and computational (or mathematical) finance programs. It is also designed for self-study by quantitative analysts in the financial industry who want to learn more about the background and details of the statistical methods used by the industry. It can also be used as a reference for graduate statistics and econometrics courses on regression, multivariate analysis, likelihood and Bayesian inference, nonparametrics, and time series, providing concrete examples and data from financial markets to illustrate the statistical methods. Tze Leung Lai is Professor of Statistics and Director of Financial Mathematics at Stanford University. He received the Ph.D. degree in 1971 from Columbia University, where he remained on the faculty until moving to Stanford University in 1987. He received the Committee of Presidents of Statistical Societies Award in 1983 and is an elected member of Academia Sinica and the International Statistical Institute. His research interests include quantitative finance and risk management, sequential statistical methodology, stochastic optimization and adaptive control, probability theory and stochastic processes, econometrics, and biostatistics. Haipeng Xing is Assistant Professor of Statistics at Columbia University. He received the Ph.D. degree in 2005 from Stanford University. His research interests include financial econometrics and engineering, time series modeling and adaptive control, fault detection, and change-point problems
HTTP:URL=https://doi.org/10.1007/978-0-387-77827-3
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Springer eBooks 9780387778273
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データ種別 電子ブック
分 類 LCC:HJ9-9940
DC23:336
書誌ID 4000116040
ISBN 9780387778273

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