000			03564nam a22002417a 4500
999			_c4531 _d4531
005			20230120144145.0
008			230120b ||||| |||| 00| 0 eng d
020			_a9780000990389
082			_a332.67253 _bFAB
100			_aFabozzi, Frank J. _9192
245			_aAsset management: _btools and issues
260			_bWorld Scientific Publishing Company Pvt. Ltd. _aNew Jersey _c2021
300			_axix, 493 p.
365			_aINR _b1650.00
504			_aContents: Asset Management Companies Fundamentals of Financial Statements Securitization and the Creation of Residential Mortgage-Related Securities Financial Econometrics Tools for Asset Management Monte Carlo Applications to Asset Management Optimization Models for Asset Management Machine Learning and Its Applications to Asset Management Risk Measures and Asset Allocation Problems Securities Lending and Its Alternatives in the Equity Market Repurchase Agreements for Financing Positions and Shorting in the Bond Market Implementable Quantitative Research Quantitative Equity Strategies Challenges in Implementing Equity Factor Investing Strategies Transaction and Trading Costs Managing a Common Stock Portfolio with a Multifactor Risk Model Using Fundamental Factor Managing a Bond Portfolio Using a Multifactor Risk Model Backtesting Investment Strategies Monte Carlo Backtesting Method
520			_aLong 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.
650			_aPortfolio management _9193
650			_aAsset allocation _97259
650			_aInstitutional investments--Management _911511
700			_aFabozzi, Francesco A. _911512
700			_aStoyanov, Stoyan V. _911513
942			_2ddc _cBK