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Linear factor models in finance

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Linear factor models in finance/ John Knight and Stephen Satchell.
Author:	Knight, John L.
other author:	Satchell, S.
Published:	Oxford ;Elsevier/Butterworth-Heinemann, : 2005.,
Description:	1 online resource (xiv, 282 p.)
Subject:	Finance - Mathematical models. -
Online resource:	http://www.sciencedirect.com/science/book/9780750660068
ISBN:	9780750660068

Linear factor models in finance
Knight, John L.

Linear factor models in finance[electronic resource] /John Knight and Stephen Satchell. - Oxford ;Elsevier/Butterworth-Heinemann,2005. - 1 online resource (xiv, 282 p.) - Quantitative finance series. - Quantitative finance series..

Includes bibliographical references and index.

Review of the literature on multifactor asset pricing, M. Pitsillis. Estimating UK factor models using multivariate skew normal distribution, C. Adcock. Misspecification in the Linear Pricing Model, I. Lo. Bayesian estimation of Risk-Premia in an APT context, T. Darsinos and S. Satchell. Sharpe Style Analysis in the MSCI Sector Portfolios, G. Christodoulakis. Implication of the method of portfolio formation on asset pricing tests, I. Lo. The Small Noise Arbitrage Pricing Theory, S. Satchell. Risk Attribution in a Global Country Sector, A. Scowcroft and J. Sefton. Predictability of Fund of Hedge Fund Returns Using Dynaporte, G. Gregoriou and F. Rouah. Estimating a Combined Linear Model, A. Stroyny. Attributing Equity Risk with a Statistical Factor Model, T. Wilding Making Covariance-based Portfolio Risk Models Sensitive to the rate at which markets reflect new information, D. Di Bartolomeo and S. Warrick. Decomposing Factor Exposure for Equity Portfolios, D. Tien et al.

The determination of the values of stocks, bonds, options, futures, and derivatives is done by the scientific process of asset pricing, which has developed dramatically in the last few years due to advances in financial theory and econometrics. This book covers the science of asset pricing by concentrating on the most widely used modelling technique called: Linear Factor Modelling. Linear Factor Models covers an important area for Quantitative Analysts/Investment Managers who are developing Quantitative Investment Strategies. Linear factor models (LFM) are part of modern investment processes that include asset valuation, portfolio theory and applications, linear factor models and applications, dynamic asset allocation strategies, portfolio performance measurement, risk management, international perspectives, and the use of derivatives. The book develops the building blocks for one of the most important theories of asset pricing - Linear Factor Modelling. Within this framework, we can include other asset pricing theories such as the Capital Asset Pricing Model (CAPM), arbitrage pricing theory and various pricing formulae for derivatives and option prices. As a bare minimum, the reader of this book must have a working knowledge of basic calculus, simple optimisation and elementary statistics. In particular, the reader must be comfortable with the algebraic manipulation of means, variances (and covariances) of linear combination(s) of random variables. Some topics may require a greater mathematical sophistication. * Covers the latest methods in this area. * Combines actual quantitative finance experience with analytical research rigour * Written by both quantitative analysts and academics who work in this area.

ISBN: 9780750660068

Source: 102903:102923Elsevier Science & Technologyhttp://www.sciencedirect.comSubjects--Topical Terms:

557653
Finance
--Mathematical models.Index Terms--Genre/Form:

554714
Electronic books.

LC Class. No.: HG106 / .K55 2005eb

Dewey Class. No.: 332.015118

Linear factor models in finance
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504 $a Includes bibliographical references and index.
505 0 $a Review of the literature on multifactor asset pricing, M. Pitsillis. Estimating UK factor models using multivariate skew normal distribution, C. Adcock. Misspecification in the Linear Pricing Model, I. Lo. Bayesian estimation of Risk-Premia in an APT context, T. Darsinos and S. Satchell. Sharpe Style Analysis in the MSCI Sector Portfolios, G. Christodoulakis. Implication of the method of portfolio formation on asset pricing tests, I. Lo. The Small Noise Arbitrage Pricing Theory, S. Satchell. Risk Attribution in a Global Country Sector, A. Scowcroft and J. Sefton. Predictability of Fund of Hedge Fund Returns Using Dynaporte, G. Gregoriou and F. Rouah. Estimating a Combined Linear Model, A. Stroyny. Attributing Equity Risk with a Statistical Factor Model, T. Wilding Making Covariance-based Portfolio Risk Models Sensitive to the rate at which markets reflect new information, D. Di Bartolomeo and S. Warrick. Decomposing Factor Exposure for Equity Portfolios, D. Tien et al.
520 $a The determination of the values of stocks, bonds, options, futures, and derivatives is done by the scientific process of asset pricing, which has developed dramatically in the last few years due to advances in financial theory and econometrics. This book covers the science of asset pricing by concentrating on the most widely used modelling technique called: Linear Factor Modelling. Linear Factor Models covers an important area for Quantitative Analysts/Investment Managers who are developing Quantitative Investment Strategies. Linear factor models (LFM) are part of modern investment processes that include asset valuation, portfolio theory and applications, linear factor models and applications, dynamic asset allocation strategies, portfolio performance measurement, risk management, international perspectives, and the use of derivatives. The book develops the building blocks for one of the most important theories of asset pricing - Linear Factor Modelling. Within this framework, we can include other asset pricing theories such as the Capital Asset Pricing Model (CAPM), arbitrage pricing theory and various pricing formulae for derivatives and option prices. As a bare minimum, the reader of this book must have a working knowledge of basic calculus, simple optimisation and elementary statistics. In particular, the reader must be comfortable with the algebraic manipulation of means, variances (and covariances) of linear combination(s) of random variables. Some topics may require a greater mathematical sophistication. * Covers the latest methods in this area. * Combines actual quantitative finance experience with analytical research rigour * Written by both quantitative analysts and academics who work in this area.
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