Ben Graham Was a Quant: Raising the IQ of the Intelligent Investor

by Steven P. Greiner

Overview

Innovative insights on creating models that will help you become a disciplined intelligent investor

The pioneer of value investing, Benjamin Graham, believed in a philosophy that continues to be followed by some of today's most successful investors, such as Warren Buffett. Part of this philosophy includes adhering to your stock selection process come "hell or high water" which, in his view, was one of the most important aspects of investing.

So, if a quant designs and implements mathematical models for predicting stock or market movements, what better way to remain objective, then to invest using algorithms or the quantitative method? This is exactly what Ben Graham Was a Quant will show you how to do. Opening with a brief history of quantitative investing, this book quickly moves on to focus on the fundamental and financial factors used in selecting "Graham" stocks, demonstrate how to test these factors, and discuss how to combine them into a quantitative model.

• Reveals how to create custom screens based on Ben Graham's methods for security selection
• Addresses what it takes to find those factors most influential in forecasting stock returns
• Explores how to design models based on other styles and international strategies

If you want to become a better investor, you need solid insights and the proper guidance. With Ben Graham Was a Quant, you'll receive this and much more, as you learn how to create quantitative models that follow in the footsteps of Graham's value philosophy.

Product Details

ISBN-13:	9781118013403
Publisher:	Wiley
Publication date:	02/09/2011
Series:	Wiley Finance , #600
Sold by:	JOHN WILEY & SONS
Format:	eBook
Pages:	352
File size:	5 MB

About the Author

STEVEN P. GREINER, Ph.D., has served as the senior quantitative strategist and portfolio manager for Allegiant Asset Management (now wholly owned by PNC Capital Advisors) and was a member of its Investment Committee. Prior to this, he was a senior quantitative strategist for large capitalization investments at Harris Investment Management. He has more than twenty years of quantitative and modeling experience. Currently, Dr. Greiner is the head of Risk Research for FactSet Research Systems. He received a BS in mathematics and chemistry from the University of Buffalo, an MS and PhD in physical chemistry from the University of Rochester, and attained postdoctoral experience from the Free University Berlin, Department of Physics.

Table of Contents

Preface.

Introduction: The Birth of the Quant.

Characterizing the Quant.

Active vs. Passive Investing.

Chapter 1: Desperately Seeking Alpha.

The Beginnings of the Modern Alpha Era.

Important History of Investment Management.

Methods of Alpha Searching.

Chapter 2: Risky Business.

Experienced vs. Exposed Risk.

The Black Swan: A Minor ELE Event, Are Quants to Blame?

Active vs. Passive Risk.

Other Risk Measures: VAR, CVAR, and ETL.

Summary.

Chapter 3: Beta Is Not Sharpe Enough.

Back to Beta.

Beta and Volatility.

The Way to a Better “Beta”: Introducing the G-Factor.

Tracking Error: The Deviant Differential Measurer.

Summary.

Chapter 4: Mr. Graham, I Give You Intelligence.

Fama-French Equation.

The Graham Formula.

Factors for Use in Quant Models.

Momentum: Increasing Investor Interest.

Volatility as a Factor in Alpha Models.

Chapter 5: Modeling Pitfalls and Perils.

Data Availability, Look-Ahead, and Survivorship Biases.

Building Models One Can Trust.

Scenario, Out-Of-Sample, and Shock Testing.

Data Snooping and Mining.

Statistical Significance and Other Fascinations.

Choosing an Investment Philosophy.

Growth, Value, Quality.

Investment Consultant as Dutch Uncle.

Where are the Relative Growth Managers?

Chapter 6: Testing the Graham “Crackers”...er, Factors.

The First Tests: Sorting.

Time-Series Plots.

The Next Tests: Scenario Analysis.

Chapter 7: Building Models from Factors.

Surviving Factors.

Weighting the Factors.

The Art versus Science of Modeling.

Time-Series of Returns.

Other Conditional Information.

The Final Model.

Other Methods of Measuring Performance: Attribution Analysis Via Brinson and Risk Decomposition.

Regression of the Graham Factors with Forward Returns.

Chapter 8: Building Portfolios from Models.

The Deming Way: Benchmarking Your Portfolio.

Portfolio Construction Issues.

Using an Online Broker: Fidelity, E*Trade, TD-Ameritrade, Schwab, Interactive Brokers, and TradeStation.

Working with A Professional Investment Management System: Bloomberg, Clarify, and Factset.

Chapter 9: Barguments: The Anti-Dementia Bacterium.

The Colossal Non-Failure of Asset Allocation.

The Stock Market as a Class of Systems.

Stochastic Portfolio Theory: An Introduction.

Portfolio Optimization: The Layman’s Perspective.

Tax Efficient Optimization.

Summary.

Chapter 10: Past and Future View.

Why did Global Contagion and Meltdown Occur?

Fallout of Crises.

The Rise of the Multi-National State Owned Enterprises.

The Emerged Markets.

The Future Quant.

Notes.

Acknowledgments.

About the Author.

Index.