Asset Management Book Reviews

Asset Management by Frank J. Fabozzi, Francesco A. Fabozzi, Marcos Lopez de Prado & Stoyan V. Stoyanov Book Summary

Long gone are the times when investors could make decisions based on intuition. Modern asset management draws on a wide-range of fields beyond financial theory: economics, financial accounting, econometrics/statistics, management science, operations research (optimization and Monte Carlo simulation), and more recently, data science (Big Data, machine learning, and artificial intelligence). The challenge in writing an institutional asset management book is that when tools from these different fields are applied in an investment strategy or an analytical framework for valuing securities, it is assumed that the reader is familiar with the fundamentals of these fields. Attempting to explain strategies and analytical concepts while also providing a primer on the tools from other fields is not the most effective way of describing the asset management process. Moreover, while an increasing number of investment models have been proposed in the asset management literature, there are challenges and issues in implementing these models. This book provides a description of the tools used in asset management as well as a more in-depth explanation of specialized topics and issues covered in the companion book, Fundamentals of Institutional Asset Management. The topics covered include the asset management business and its challenges, the basics of financial accounting, securitization technology, analytical tools (financial econometrics, Monte Carlo simulation, optimization models, and machine learning), alternative risk measures for asset allocation, securities finance, implementing quantitative research, quantitative equity strategies, transaction costs, multifactor models applied to equity and bond portfolio management, and backtesting methodologies. This pedagogic approach exposes the reader to the set of interdisciplinary tools that modern asset managers require in order to extract profits from data and processes.Contents: Asset Management CompaniesFundamentals of Financial StatementsSecuritization and the Creation of Residential Mortgage-Related SecuritiesFinancial Econometrics Tools for Asset ManagementMonte Carlo Applications to Asset ManagementOptimization Models for Asset ManagementMachine Learning and Its Applications to Asset ManagementRisk Measures and Asset Allocation ProblemsSecurities Lending and Its Alternatives in the Equity MarketRepurchase Agreements for Financing Positions and Shorting in the Bond MarketImplementable Quantitative ResearchQuantitative Equity StrategiesChallenges in Implementing Equity Factor Investing StrategiesTransaction and Trading CostsManaging a Common Stock Portfolio with a Multifactor Risk Model Using Fundamental FactorManaging a Bond Portfolio Using a Multifactor Risk ModelBacktesting Investment StrategiesMonte Carlo Backtesting Method
Readership: Suitable for professional portfolio managers, security analysts as well as students focusing on investment management courses.Asset Management;Financial Accounting;Securitization;Financial Econometrics;Monte Carlo Simulation;Optimization Models;Machine Learning;Risk Meausres;Securities Lending;Securities Finance;Repurchasing Agreements;Quantitative Equity Strategies0Key Features:Background tools are covered such as financial accounting, financial econometrics, Monte Carlo simulation, and optimizationTopics not usually covered in books on asset management are covered such as securitization technology, machine learning, alternative risk measures, backtesting methodologies, transaction costs, and securities financePractical implementation issues associated with quantitative investingApplications of factor models to both equity and bond portfolio management

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Asset Management (Frank J. Fabozzi, Francesco A. Fabozzi, Marcos Lopez de Prado & Stoyan V. Stoyanov) Book Reviews 2024

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