Quantitative equity portfolio management combines theories and advanced techniques from several disciplines, including financial economics, accounting, mathematics, and operational research. While many texts are devoted to these disciplines, few deal with quantitative equity investing in a systematic and mathematical framework that is suitable for
Quantitative Equity Portfolio Management brings the orderly structure of fundamental asset management to the often-chaotic world of active equity management. Straightforward and accessible, it provides you with nuts-and-bolts details for selecting and aggregating factors, building a risk model, and much more.
Discover foundational and advanced techniques in quantitative equity trading from a veteran insider In Quantitative Portfolio Management: The Art and Science of Statistical Arbitrage, distinguished physicist-turned-quant Dr. Michael Isichenko delivers a systematic review of the quantitative trading of equities, or statistical arbitrage. The book teaches you how to source financial data, learn patterns of asset returns from historical data, generate and combine multiple forecasts, manage risk, build a stock portfolio optimized for risk and trading costs, and execute trades. In this important book, you’ll discover: Machine learning methods of forecasting stock returns in efficient financial markets How to combine multiple forecasts into a single model by using secondary machine learning, dimensionality reduction, and other methods Ways of avoiding the pitfalls of overfitting and the curse of dimensionality, including topics of active research such as “benign overfitting” in machine learning The theoretical and practical aspects of portfolio construction, including multi-factor risk models, multi-period trading costs, and optimal leverage Perfect for investment professionals, like quantitative traders and portfolio managers, Quantitative Portfolio Management will also earn a place in the libraries of data scientists and students in a variety of statistical and quantitative disciplines. It is an indispensable guide for anyone who hopes to improve their understanding of how to apply data science, machine learning, and optimization to the stock market.
A comprehensive look at the tools and techniques used in quantitative equity management Some books attempt to extend portfolio theory, but the real issue today relates to the practical implementation of the theory introduced by Harry Markowitz and others who followed. The purpose of this book is to close the implementation gap by presenting state-of-the art quantitative techniques and strategies for managing equity portfolios. Throughout these pages, Frank Fabozzi, Sergio Focardi, and Petter Kolm address the essential elements of this discipline, including financial model building, financial engineering, static and dynamic factor models, asset allocation, portfolio models, transaction costs, trading strategies, and much more. They also provide ample illustrations and thorough discussions of implementation issues facing those in the investment management business and include the necessary background material in probability, statistics, and econometrics to make the book self-contained. Written by a solid author team who has extensive financial experience in this area Presents state-of-the art quantitative strategies for managing equity portfolios Focuses on the implementation of quantitative equity asset management Outlines effective analysis, optimization methods, and risk models In today's financial environment, you have to have the skills to analyze, optimize and manage the risk of your quantitative equity investments. This guide offers you the best information available to achieve this goal.
This self-contained book presents the main techniques of quantitative portfolio management and associated statistical methods in a very didactic and structured way, in a minimum number of pages. The concepts of investment portfolios, self-financing portfolios and absence of arbitrage opportunities are extensively used and enable the translation of all the mathematical concepts in an easily interpretable way. All the results, tested with Python programs, are demonstrated rigorously, often using geometric approaches for optimization problems and intrinsic approaches for statistical methods, leading to unusually short and elegant proofs. The statistical methods concern both parametric and non-parametric estimators and, to estimate the factors of a model, principal component analysis is explained. The presented Python code and web scraping techniques also make it possible to test the presented concepts on market data. This book will be useful for teaching Masters students and for professionals in asset management, and will be of interest to academics who want to explore a field in which they are not specialists. The ideal pre-requisites consist of undergraduate probability and statistics and a familiarity with linear algebra and matrix manipulation. Those who want to run the code will have to install Python on their pc, or alternatively can use Google Colab on the cloud. Professionals will need to have a quantitative background, being either portfolio managers or risk managers, or potentially quants wanting to double check their understanding of the subject.
Two pioneers and innovators in the money management field present their choice of groundbreaking, peer-reviewed articles on subjects including portfolio engineering and long-short investment strategy. More than just a collection of classic review pieces, however, Equity Management provides new material to introduce, interpret, and integrate the pieces, with an introduction that provides an authoritative overview of the chapters. Important and innovative, it is destined to become the "Graham and Dodd" of quantitative equity investing. About the Authors: Bruce I. Jacobs and Kenneth N. Levy are Principals of Jacobs Levy Equity Management. Based in Florham Park, New Jersey, Jacobs Levy Equity Management is widely recognized as a leading provider of quantitative equity strategies for institutional clients. Jacobs Levy currently manages over $15 billion in various strategies for a prestigious global roster of 50 corporate pension plans, public retirement systems, multi-employer funds, endowments, and foundations, including over 25 of Pensions & Investments' "Top 200 Pension Funds/Sponsors." Bruce I. Jacobs holds a PhD in finance from the Wharton School of the University of Pennsylvania. He is the author of Capital Ideas and Market Realities: Option Replication, Investor Behavior, and Stock Market Crashes and co-editor, with Ken Levy, of Market Neutral Strategies. He serves on the advisory board of the Journal of Portfolio Management. Kenneth N. Levy holds an MBA and an MA in applied economics from the Wharton School of the University of Pennsylvania. He is co-editor, with Bruce Jacobs, of Market Neutral Strategies. A Chartered Financial Analyst, he has served on the CFA Institute's candidate curriculum committee and on the advisory board of POSIT.
You have great investment ideas. If you turn them into highly profitable portfolios, this book is for you. Advanced Portfolio Management: A Quant’s Guide for Fundamental Investors is for fundamental equity analysts and portfolio managers, present, and future. Whatever stage you are at in your career, you have valuable investment ideas but always need knowledge to turn them into money. This book will introduce you to a framework for portfolio construction and risk management that is grounded in sound theory and tested by successful fundamental portfolio managers. The emphasis is on theory relevant to fundamental portfolio managers that works in practice, enabling you to convert ideas into a strategy portfolio that is both profitable and resilient. Intuition always comes first, and this book helps to lay out simple but effective "rules of thumb" that require little effort to implement and understand. At the same time, the book shows how to implement sophisticated techniques in order to meet the challenges a successful investor faces as his or her strategy grows in size and complexity. Advanced Portfolio Management also contains more advanced material and a quantitative appendix, which benefit quantitative researchers who are members of fundamental teams. You will learn how to: Separate stock-specific return drivers from the investment environment’s return drivers Understand current investment themes Size your cash positions based on Your investment ideas Understand your performance Measure and decompose risk Hedge the risk you don’t want Use diversification to your advantage Manage losses and control tail risk Set your leverage Author Giuseppe A. Paleologo has consulted, collaborated, taught, and drank strong wine with some of the best stock-pickers in the world; he has traded tens of billions of dollars hedging and optimizing their books and has helped them navigate through big drawdowns and even bigger recoveries. Whether or not you have access to risk models or advanced mathematical background, you will benefit from the techniques and the insights contained in the book—and won't find them covered anywhere else.
A detailed look at equity valuation and portfolio management Equity valuation is a method of valuing stock prices using fundamental analysis to determine the worth of the business and discover investment opportunities. In Equity Valuation and Portfolio Management Frank J. Fabozzi and Harry M. Markowitz explain the process of equity valuation, provide the necessary mathematical background, and discuss classic and new portfolio strategies for investment managers. Divided into two comprehensive parts, this reliable resource focuses on valuation and portfolio strategies related to equities. Discusses both fundamental and new techniques for valuation and strategies Fabozzi and Markowitz are experts in the fields of investment management and economics Includes end of chapter bullet point summaries, key chapter take-aways, and study questions Filled with in-depth insights and practical advice, Equity Valuation and Portfolio Management will put you in a better position to excel at this challenging endeavor.
The classic guide to quantitative investing—expanded and updated for today’s increasingly complex markets From Bruce Jacobs and Ken Levy—two pioneers of quantitative equity management—the go-to guide to stock selection has been substantially updated to help you build portfolios in today’s transformed investing landscape. A powerful combination of in-depth research and expert insights gained from decades of experience, Equity Management, Second Edition includes 24 new peer-reviewed articles that help leveraged long-short investors and leverage-averse investors navigate today’s complex and unpredictable markets. Retaining all the content that made an instant classic of the first edition—including the authors’ innovative approach to disentangling the many factors that influence stock returns, unifying the investment process, and integrating long and short portfolio positions—this new edition addresses critical issues. Among them-- • What’s the best leverage level for long-short and leveraged long-only portfolios? • Which behavioral characteristics explain the recent financial meltdown and previous crises? • What is smart beta—and why should you think twice about using it? • How do option-pricing theory and arbitrage strategies lead to market instability? • Why are factor-based strategies on the rise? Equity Management provides the most comprehensive treatment of the subject to date. More than a mere compilation of articles, this collection provides a carefully structured view of modern quantitative investing. You’ll come away with levels of insight and understanding that will give you an edge in increasingly complex and unpredictable markets. Well-established as two of today’s most innovative thinkers, Jacobs and Levy take you to the next level of investing. Read Equity Management and design the perfect portfolio for your investing goals.
Quantitative equity management techniques are helping investors achieve more risk efficient and appropriate investment outcomes. Factor investing, vetted by decades of prior and current research, is growing quickly, particularly in in the form of smart-beta and ETF strategies. Dynamic factor-timing approaches, incorporating macroeconomic and investment conditions, are in the early stages but will likely thrive. A new generation of big data approaches are rendering quantitative equity analysis even more powerful and encompassing.
