000 05728cam a2200517Mu 4500
999 _c34162
_d34162
003 OCoLC
005 20200714222252.0
006 m d
007 cr cnu---unuuu
008 170715s2018 flu o 000 0 eng d
020 _a9781351981903
_q(electronic bk.)
020 _a1351981900
_q(electronic bk.)
035 _a1556648
035 _a(OCoLC)993779290
040 _aEBLCP
_beng
_cEBLCP
_dCRCPR
_dN$T
_dOCLCO
_dN$T
049 _aMAIN
050 4 _aHG176.5
_b.S49 2018
072 7 _aMAT
_x029000
_2bisacsh
072 7 _aBUS
_x027000
_2bisacsh
100 1 _aSeverini, Thomas A.
_q(Thomas Alan),
_d1959-
_eauthor.
245 1 0 _aIntroduction to statistical methods for financial models
_h[electronic resource] /
_cThomas A. Severini.
264 1 _aBoca Raton, FL :
_bCRC Press,
_c[2018]
300 _a1 online resource (355 p.)
490 1 _aChapman & Hall/CRC Texts in Statistical Science
500 _aDescription based upon print version of record.
505 0 _aTitle Page; Copyright Page; Dedication; Table of Contents; Preface; 1 Introduction; 2 Returns; 2.1 Introduction; 2.2 Basic Concepts; 2.3 Adjusted Prices; 2.4 Statistical Properties of Returns; 2.5 Analyzing Return Data; 2.6 Suggestions for Further Reading; 2.7 Exercises; 3 Random Walk Hypothesis; 3.1 Introduction; 3.2 Conditional Expectation; 3.3 Efficient Markets and the Martingale Model; 3.4 Random Walk Models for Asset Prices; 3.5 Tests of the Random Walk Hypothesis; 3.6 Do Stock Returns Follow the Random Walk Model?; 3.7 Suggestions for Further Reading; 3.8 Exercises; 4 Portfolios
505 8 _a4.1 Introduction4.2 Basic Concepts; 4.3 Negative Portfolio Weights: Short Sales; 4.4 Optimal Portfolios of Two Assets; 4.5 Risk-Free Assets; 4.6 Portfolios of Two Risky Assets and a Risk-Free Asset; 4.7 Suggestions for Further Reading; 4.8 Exercises; 5 Efficient Portfolio Theory; 5.1 Introduction; 5.2 Portfolios of N Assets; 5.3 Minimum-Risk Frontier; 5.4 The Minimum-Variance Portfolio; 5.5 The Efficient Frontier; 5.6 Risk-Aversion Criterion; 5.7 The Tangency Portfolio; 5.8 Portfolio Constraints; 5.9 Suggestions for Further Reading; 5.10 Exercises; 6 Estimation; 6.1 Introduction
505 8 _a6.2 Basic Sample Statistics6.3 Estimation of the Mean Vector and Covariance Matrix; 6.4 Weighted Estimators; 6.5 Shrinkage Estimators; 6.6 Estimation of Portfolio Weights; 6.7 Using Monte Carlo Simulation to Study the Properties of Estimators; 6.8 Suggestions for Further Reading; 6.9 Exercises; 7 Capital Asset Pricing Model; 7.1 Introduction; 7.2 Security Market Line; 7.3 Implications of the CAPM; 7.4 Applying the CAPM to a Portfolio; 7.5 Mispriced Assets; 7.6 The CAPM without a Risk-Free Asset; 7.7 Using the CAPM to Describe the Expected Returns on a Set of Assets
505 8 _a7.8 Suggestions for Further Reading7.9 Exercises; 8 The Market Model; 8.1 Introduction; 8.2 Market Indices; 8.3 The Model and Its Estimation; 8.4 Testing the Hypothesis that an Asset Is Priced Correctly; 8.5 Decomposition of Risk; 8.6 Shrinkage Estimation and Adjusted Beta; 8.7 Applying the Market Model to Portfolios; 8.8 Diversification and the Market Model; 8.9 Measuring Portfolio Performance; 8.10 Standard Errors of Estimated Performance Measures; 8.11 Suggestions for Further Reading; 8.12 Exercises; 9 The Single-Index Model; 9.1 Introduction; 9.2 The Model
505 8 _a9.3 Covariance Structure of Returns under the Single-Index Model9.4 Estimation; 9.5 Applications to Portfolio Analysis; 9.6 Active Portfolio Management and the Treynor-Black Method; 9.7 Suggestions for Further Reading; 9.8 Exercises; 10 Factor Models; 10.1 Introduction; 10.2 Limitations of the Single-Index Model; 10.3 The Model and Its Estimation; 10.4 Factors; 10.5 Arbitrage Pricing Theory; 10.6 Factor Premiums; 10.7 Applications of Factor Models; 10.8 Suggestions for Further Reading; 10.9 Exercises; References; Index
520 2 _a"This book provides an introduction to the use of statistical concepts and methods to model and analyze financial data. The ten chapters of the book fall naturally into three sections. Chapters 1 to 3 cover some basic concepts of finance, focusing on the properties of returns on an asset. Chapters 4 through 6 cover aspects of portfolio theory and the methods of estimation needed to implement that theory. The remainder of the book, Chapters 7 through 10, discusses several models for financial data, along with the implications of those models for portfolio theory and for understanding the properties of return data. The audience for the book is students majoring in Statistics and Economics as well as in quantitative fields such as Mathematics and Engineering. Readers are assumed to have some background in statistical methods along with courses in multivariate calculus and linear algebra. "--Provided by publisher.
590 _aMaster record variable field(s) change: 050, 072, 082
650 0 4 _aStatistics for Business, Finance & Economics.
650 0 4 _aFinancial Mathematics.
650 0 4 _aFinance.
650 0 _aFinance
_xStatistical methods.
650 0 _aFinance
_xMathematical models.
650 0 7 _aMATHEMATICS / Probability & Statistics / General.
_2bisacsh
650 7 _aBUSINESS & ECONOMICS / Finance
_2bisacsh
776 0 8 _iPrint version:
_aSeverini, Thomas A
_tIntroduction to Statistical Methods for Financial Models
_dMilton : CRC Press,c2017
_z9781138198371
830 0 _aChapman & Hall/CRC Texts in Statistical Science.
850 _aSHTL
856 4 0 _3EBSCOhost
_uhttp://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=1556648
856 4 0 _3ProQuest
_uhttps://ebookcentral.proquest.com/lib/vajira-ebooks/detail.action?docID=4901484
942 _cEBK
_2nlm