Statistical models and methods for financial markets
著者
書誌事項
Statistical models and methods for financial markets
（Springer texts in statistics）
Springer, c2008
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注記
Includes bibliographical reference (p. [337]-347) and index
内容説明・目次
内容説明
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.
目次
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.
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