Quantitative Equity Investing Techniques and Strategies

ISBN-10: 0470262478

ISBN-13: 9780470262474

Edition: 2010

Authors: Frank J. Fabozzi, Sergio M. Focardi, Petter N. Kolm

List price: $80.00
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Book details

List price: $80.00
Copyright year: 2010
Publisher: John Wiley & Sons, Limited
Publication date: 3/19/2010
Binding: Hardcover
Pages: 528
Size: 6.00" wide x 9.00" long x 1.50" tall
Weight: 1.628
Language: English

Douglas J. Lucas is Executive Director and Head of CDO Research at UBS. He is also Chairman of The Bond Market Association's CDO Research Committee and ranked top three in CDO research in the Institutional Investor's fixed income analyst survey. Lucas has been involved in the CDO market for nearly two decades, having developed Moody's rating methodology for CDOs in 1989.LAURIE S. GOODMAN, PhD, is Managing Director and co-Head of Global Fixed Income Research at UBS. She manages U.S. Securitized Products and Treasury/Agency/Derivatives Research. Goodman has worked on Wall Street for over twenty years and is well regarded by the investor community, having won more #1 slots on the Institutional Investor All-American Fixed Income Team than any other analyst.FRANK J. FABOZZI, PhD, CFA, CPA, is an Adjunct Professor of Finance and Becton Fellow at Yale University's School of Management and a Fellow of the International Center for Finance. Fabozzi is the Editor of the Journal of Portfolio Management.

FRANK J. FABOZZI, PHD, CFA, CPA, is the Frederick Frank Adjunct Professor of Finance at Yale University's School of Management and a Fellow of the International Center for Finance. Prior to joining the Yale faculty, Fabozzi was a visiting professor of finance in the Sloan School of Management at MIT. Fabozzi is the Editor of the Journal of Portfolio Management.Sergio M. Focardi is a founding partner of the Paris-based consulting firm, The Intertek Group. He consults on, trains on, and implements quantitative financial models. He is also a member of the editorial board of the Journal of Portfolio Management and author of numerous articles and books on financial modeling.Petter N. Kolm, PHD, is a doctoral student in finance at Yale University's School of Management and a financial consultant in New York City. Previously, he worked in the Quantitative Strategies group at Goldman Sachs Asset Management where he developed quantitative investment models and strategies.

Preface
About the Authors
Introduction
In Praise of Mathematical Finance
Studies of the Use of Quantitative Equity Management
Looking Ahead for Quantitative Equity Investing
Financial Econometrics I: Linear Regressions
Historical Notes
Covariance and Correlation
Regressions, Linear Regressions, and Projections
Multivariate Regression
Quantile Regressions
Regression Diagnostic
Robust Estimation of Regressions
Classification and Regression Trees
Summary
Financial Econometrics II: Time Series
Stochastic Processes
Time Series
Stable Vector Autoregressive Processes
Integrated and Cointegrated Variables
Estimation of Stable Vector Autoregressive (VAR) Models
Estimating the Number of Lags
Autocorrelation and Distributional Properties of Residuals
Stationary Autoregressive Distributed Lag Models
Estimation of Nonstationary VAR Models
Estimation with Canonical Correlations
Estimation with Principal Component Analysis
Estimation with the Eigenvalues of the Companion Matrix
Nonlinear Models in Finance
Causality
Summary
Common Pitfalls in Financial Modeling
Theory and Engineering
Engineering and Theoretical Science
Engineering and Product Design in Finance
Learning, Theoretical, and Hybrid Approaches to Portfolio Management
Sample Biases
The Bias in Averages
Pitfalls in Choosing from Large Data Sets
Time Aggregation of Models and Pitfalls in the Selection of Data Frequency
Model Risk and its Mitigation
Summary
Factor Models and their Estimation
The Notion of Factors
Static Factor Models
Factor Analysis and Principal Components Analysis
Why Factor Models of Returns
Approximate Factor Models of Returns
Dynamic Factor Models
Summary
Factor-Based Trading Strategies I: Factor Construction and Analysis
Factor-Based Trading
Developing Factor-Based Trading Strategies
Risk to Trading Strategies
Desirable Properties of Factors
Sources for Factors
Building Factors from Company Characteristics
Working with Data
Analysis of Factor Data
Summary
Factor-Based Trading Strategies II: Cross-Sectional Models and Trading Strategies
Cross-Sectional Methods for Evaluation of Factor Premiums
Factor Models
Performance Evaluation of Factors
Model Construction Methodologies for a Factor-Based Trading Strategy
Backtesting
Backtesting Our Factor Trading Strategy
Summary
Portfolio Optimization: Basic Theory and Practice
Mean-Variance Analysis: Overview
Classical Framework for Mean-Variance Optimization
Mean-Variance Optimization with a Risk-Free Asset
Portfolio Constraints Commonly Used in Practice
Estimating the Inputs Used in Mean-Variance Optimization: Expected Return and Risk
Portfolio Optimization with Other Risk Measures
Summary
Portfolio Optimization: Bayesian Techniques and the Black-Litterman Model
Practical Problems Encountered in Mean-Variance Optimization
Shrinkage Estimation
The Black-Litterman Model
Summary
Robust Portfolio Optimization
Robust Mean-Variance Formulations
Using Robust Mean-Variance Portfolio Optimization in Practice
Some Practical Remarks on Robust Portfolio Optimization Models
Summary
Transaction Costs and Trade Execution
A Taxonomy of Transaction Costs
Liquidity and Transaction Costs
Market Impact Measurements and Empirical Findings
Forecasting and Modeling Market Impact
Incorporating Transaction Costs in Asset-Allocation Models
Integrated Portfolio Management: Beyond Expected Return and Portfolio Risk
Summary
Investment Management and Algorithmic Trading
Market Impact and the Order Book
Optimal Execution
Impact Models
Popular Algorithmic Trading Strategies
What Is Next?
Some Comments about the High-Frequency Arms Race
Summary
Data Descriptions and Factor Definitions
The MSCI World Index
One-Month LIBOR
The Compustat Point-in-Time, IBES Consensus Databases and Factor Definitions
Summary of Well-Known Factors and Their Underlying Economic Rationale
Review of Eigenvalues and Eigenvectors
The SWEEP Operator
Index
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