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Synopsis
This book is intended as a statistics textbook for masters students in mathematical finance/computational finance/financial mathematics. It is also intended for analysts in the financial industry.
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From the Back Cover
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.
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Statistical Models and Methods for Financial Markets
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Statistical Models and Methods for Financial Markets
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Statistical Models and Methods for Financial Markets
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ISBN 10: 1441926682
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Statistical Models and Methods for Financial Markets
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ISBN 10: 1441926682
ISBN 13: 9781441926685
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The idea of writing this bookarosein 2000when the rst author wasassigned to teach the required course STATS 240 (Statistical Methods in Finance) in the new M. S. program in nancial mathematics at Stanford, which is an interdisciplinary program that aims to provide a master's-level education in applied mathematics, statistics, computing, nance, and economics. Students in the programhad di erent backgroundsin statistics. Some had only taken a basic course in statistical inference, while others had taken a broad spectrum of M. S. - and Ph. D. -level statistics courses. On the other hand, all of them had already taken required core courses in investment theory and derivative pricing, and STATS 240 was supposed to link the theory and pricing formulas to real-world data and pricing or investment strategies. Besides students in theprogram,thecoursealso attractedmanystudentsfromother departments in the university, further increasing the heterogeneity of students, as many of them had a strong background in mathematical and statistical modeling from the mathematical, physical, and engineering sciences but no previous experience in nance. To address the diversity in background but common strong interest in the subject and in a potential career as a 'quant' in the nancialindustry,thecoursematerialwascarefullychosennotonlytopresent basic statistical methods of importance to quantitative nance but also to summarize domain knowledge in nance and show how it can be combined with statistical modeling in nancial analysis and decision making. The course material evolved over the years, especially after the second author helped as the head TA during the years 2004 and 2005. 376 pp. Englisch. Seller Inventory # 9781441926685
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Statistical Models and Methods for Financial Markets
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Statistical methods and models are of importance to quantitative financeExhibits links between finance theory, market practice and statistical modeling and decision makingUses concrete examples and data from financial markets to illustrate . Seller Inventory # 4173169
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Statistical Models and Methods for Financial Markets
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - The idea of writing this bookarosein 2000when the rst author wasassigned to teach the required course STATS 240 (Statistical Methods in Finance) in the new M. S. program in nancial mathematics at Stanford, which is an interdisciplinary program that aims to provide a master's-level education in applied mathematics, statistics, computing, nance, and economics. Students in the programhad di erent backgroundsin statistics. Some had only taken a basic course in statistical inference, while others had taken a broad spectrum of M. S. - and Ph. D. -level statistics courses. On the other hand, all of them had already taken required core courses in investment theory and derivative pricing, and STATS 240 was supposed to link the theory and pricing formulas to real-world data and pricing or investment strategies. Besides students in theprogram,thecoursealso attractedmanystudentsfromother departments in the university, further increasing the heterogeneity of students, as many of them had a strong background in mathematical and statistical modeling from the mathematical, physical, and engineering sciences but no previous experience in nance. To address the diversity in background but common strong interest in the subject and in a potential career as a 'quant' in the nancialindustry,thecoursematerialwascarefullychosennotonlytopresent basic statistical methods of importance to quantitative nance but also to summarize domain knowledge in nance and show how it can be combined with statistical modeling in nancial analysis and decision making. The course material evolved over the years, especially after the second author helped as the head TA during the years 2004 and 2005. Seller Inventory # 9781441926685
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Statistical Models and Methods for Financial Markets
Published by
Springer New York, Springer US Nov 2010, 2010
ISBN 10: 1441926682
ISBN 13: 9781441926685
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Taschenbuch. Condition: Neu. Neuware -The idea of writing this bookarosein 2000when the rst author wasassigned to teach the required course STATS 240 (Statistical Methods in Finance) in the new M. S. program in nancial mathematics at Stanford, which is an interdisciplinary program that aims to provide a master¿s-level education in applied mathematics, statistics, computing, nance, and economics. Students in the programhad di erent backgroundsin statistics. Some had only taken a basic course in statistical inference, while others had taken a broad spectrum of M. S. - and Ph. D. -level statistics courses. On the other hand, all of them had already taken required core courses in investment theory and derivative pricing, and STATS 240 was supposed to link the theory and pricing formulas to real-world data and pricing or investment strategies. Besides students in theprogram,thecoursealso attractedmanystudentsfromother departments in the university, further increasing the heterogeneity of students, as many of them had a strong background in mathematical and statistical modeling from the mathematical, physical, and engineering sciences but no previous experience in nance. To address the diversity in background but common strong interest in the subject and in a potential career as a ¿quant¿ in the nancialindustry,thecoursematerialwascarefullychosennotonlytopresent basic statistical methods of importance to quantitative nance but also to summarize domain knowledge in nance and show how it can be combined with statistical modeling in nancial analysis and decision making. The course material evolved over the years, especially after the second author helped as the head TA during the years 2004 and 2005.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 376 pp. Englisch. Seller Inventory # 9781441926685
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Statistical Models and Methods for Financial Markets (Springer Texts in Statistics)
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Statistical Models and Methods for Financial Markets (Springer Texts in Statistics)
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