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An inside look at modern approaches to modeling equity portfolios Financial Modeling of the Equity Market is the most comprehensive, up-to-date guide to modeling equity portfolios. The book is intended for a wide range of quantitative analysts, practitioners, and students of finance. Without sacrificing mathematical rigor, it presents arguments in a concise and clear style with a wealth of real-world examples and practical simulations. This book presents all the major approaches to single-period return analysis, including modeling, estimation, and optimization issues. It covers both static and dynamic factor analysis, regime shifts, long-run modeling, and cointegration. Estimation issues, including dimensionality reduction, Bayesian estimates, the Black-Litterman model, and random coefficient models, are also covered in depth. Important advances in transaction cost measurement and modeling, robust optimization, and recent developments in optimization with higher moments are also discussed. Sergio M. Focardi (Paris, France) is a founding partner of the Paris-based consulting firm, The Intertek Group. He is a member of the editorial board of the Journal of Portfolio Management. He is also the author of numerous articles and books on financial modeling. Petter N. Kolm, PhD (New Haven, CT and New York, NY), is a graduate student in finance at the Yale School of Management and a financial consultant in New York City. Previously, he worked in the Quantitative Strategies Group of Goldman Sachs Asset Management, where he developed quantitative investment models and strategies.
Written by the Founder and CEO of the prestigious New York School of Finance, this book schools you in the fundamental tools for accurately assessing the soundness of a stock investment. Built around a full-length case study of Wal-Mart, it shows you how to perform an in-depth analysis of that company's financial standing, walking you through all the steps of developing a sophisticated financial model as done by professional Wall Street analysts. You will construct a full scale financial model and valuation step-by-step as you page through the book. When we ran this analysis in January of 2012, we estimated the stock was undervalued. Since the first run of the analysis, the stock has increased 35 percent. Re-evaluating Wal-Mart 9months later, we will step through the techniques utilized by Wall Street analysts to build models on and properly value business entities. Step-by-step financial modeling - taught using downloadable Wall Street models, you will construct the model step by step as you page through the book. Hot keys and explicit Excel instructions aid even the novice excel modeler. Model built complete with Income Statement, Cash Flow Statement, Balance Sheet, Balance Sheet Balancing Techniques, Depreciation Schedule (complete with accelerating depreciation and deferring taxes), working capital schedule, debt schedule, handling circular references, and automatic debt pay downs. Illustrative concepts including detailing model flows help aid in conceptual understanding. Concepts are reiterated and honed, perfect for a novice yet detailed enough for a professional. Model built direct from Wal-Mart public filings, searching through notes, performing research, and illustrating techniques to formulate projections. Includes in-depth coverage of valuation techniques commonly used by Wall Street professionals. Illustrative comparable company analyses - built the right way, direct from historical financials, calculating LTM (Last Twelve Month) data, calendarization, and properly smoothing EBITDA and Net Income. Precedent transactions analysis - detailing how to extract proper metrics from relevant proxy statements Discounted cash flow analysis - simplifying and illustrating how a DCF is utilized, how unlevered free cash flow is derived, and the meaning of weighted average cost of capital (WACC) Step-by-step we will come up with a valuation on Wal-Mart Chapter end questions, practice models, additional case studies and common interview questions (found in the companion website) help solidify the techniques honed in the book; ideal for universities or business students looking to break into the investment banking field.
the mathematics of financial modeling & investment management The Mathematics of Financial Modeling & Investment Management covers a wide range of technical topics in mathematics and finance-enabling the investment management practitioner, researcher, or student to fully understand the process of financial decision-making and its economic foundations. This comprehensive resource will introduce you to key mathematical techniques-matrix algebra, calculus, ordinary differential equations, probability theory, stochastic calculus, time series analysis, optimization-as well as show you how these techniques are successfully implemented in the world of modern finance. Special emphasis is placed on the new mathematical tools that allow a deeper understanding of financial econometrics and financial economics. Recent advances in financial econometrics, such as tools for estimating and representing the tails of the distributions, the analysis of correlation phenomena, and dimensionality reduction through factor analysis and cointegration are discussed in depth. Using a wealth of real-world examples, Focardi and Fabozzi simultaneously show both the mathematical techniques and the areas in finance where these techniques are applied. They also cover a variety of useful financial applications, such as: * Arbitrage pricing * Interest rate modeling * Derivative pricing * Credit risk modeling * Equity and bond portfolio management * Risk management * And much more Filled with in-depth insight and expert advice, The Mathematics of Financial Modeling & Investment Management clearly ties together financial theory and mathematical techniques.
The Oxford Guide to Financial Modeling is accompanied by a companion web site that serves as an interactive workbook designed specifically for the book. This site is simple to use yet exceedingly robust with regard to its technological efficiency and purposeful usability. It is designed to further enhance understanding of the use and applications of the models referred to in the book and it is accessible free of charge at www.thomasho.com. This on-line workbook and resource tool contains more than 95 downloadable Excel models. The models provide clear expositions of the mathematical formulations and can be used along with the book. The companion web site is rich with a plethora of research and analytic tools designed for "doing finance" on-line.
From the Author: This is not another boring, impossible to read, thousand-page textbook. On the contrary, this is an exciting journey into the world of Wall Street-style financial modeling. The motivation behind this book comes from my days as a new research analyst, trying to juggle the demands of 80-plus hour work weeks, FINRA exams, and client meetings, while attempting to learn the basics of modeling. At the time I sought outside educational resources only to find useless classes focused on spreadsheet tricks, or high-level theory-based books with little practical value. What I really needed was someone to sit down, and show me exactly how to build a model, using a real company as an example, from start to finish. Now, years after leaving the sell-side rat race, I have written the book that I sought when I was new to the street. The result is a clear, concise, easy to read guide on how to build a three-statement model. The book starts with an introduction to the industry and important background information for new analysts. Then, beginning with a blank spreadsheet, the text demonstrates exactly how to build a model using an actual company example. Throughout the chapters there are numerous images of the model which highlight key elements, as if I were pointing to a computer screen and explaining it directly to the reader. There are also more than 30 spreadsheets available for download to follow along with the text. After the model is built, I discuss effective ways to use it for forecasting and share valuation, and demonstrate how to maintain the model over time. I have also included insight from my experience in research, pitfalls to watch for, and frequently asked questions from my research team, to help add color to the subject matter. This book is a self-published, grassroots effort. You will not find a shiny professional cover or expert photographs inside. This book is less what you would expect from a traditional textbook, and closer to an informal conversation between me and the reader. Sometimes all you need is to talk to someone who has been there, and that is what you will get between these two covers. Ultimately the goal is to have my readers come away from their experience feeling empowered and excited to build an earnings model of their own. Regardless of whether or not you intend to start a career in equity research, if you would like to learn how to model earnings for a company, then this book is a good place to get started.
The past twenty years have seen an extraordinary growth in the use of quantitative methods in financial markets. Finance professionals now routinely use sophisticated statistical techniques in portfolio management, proprietary trading, risk management, financial consulting, and securities regulation. This graduate-level textbook is intended for PhD students, advanced MBA students, and industry professionals interested in the econometrics of financial modeling. The book covers the entire spectrum of empirical finance, including: the predictability of asset returns, tests of the Random Walk Hypothesis, the microstructure of securities markets, event analysis, the Capital Asset Pricing Model and the Arbitrage Pricing Theory, the term structure of interest rates, dynamic models of economic equilibrium, and nonlinear financial models such as ARCH, neural networks, statistical fractals, and chaos theory. Each chapter develops statistical techniques within the context of a particular financial application. This exciting new text contains a unique and accessible combination of theory and practice, bringing state-of-the-art statistical techniques to the forefront of financial applications. Each chapter also includes a discussion of recent empirical evidence, for example, the rejection of the Random Walk Hypothesis, as well as problems designed to help readers incorporate what they have read into their own applications.
Too often, finance courses stop short of making a connection between textbook finance and the problems of real-world business. "Financial Modeling" bridges this gap between theory and practice by providing a nuts-and-bolts guide to solving common financial problems with spreadsheets. The CD-ROM contains Excel* worksheets and solutions to end-of-chapter exercises. 634 illustrations.
An in-depth look at the nature of market making and exchanges From theory to practicalities, this is a comprehensive, up-to-date handbook and reference on how markets work and the nuances of trading. It includes a CD with an interactive trading simulation. Robert A. Schwartz, PhD (New York, NY), is Marvin M. Speiser Professor of Finance and University Distinguished Professor in the Zicklin School of Business, Baruch College, CUNY. Reto Francioni, PhD (Zurich, Switzerland), is President and Chairman of the Board of SWX, the Swiss Stock Exchange, and former co-CEO of Consors Discount Broker AG, Nuremberg.
The study of security market imperfections, namely the predictability of equity stock returns, is one of the fundamental research areas in financial modelling. These anomalies, which are not consistent with existing theories, concern the relation between stock returns and variables, such as firm size and earnings-to-price ratios, and seasonal effects, such as January and turn-of-the-month. This book provides the most complete and current account of work in the area. Leading academics and investment researchers have combined to produce a comprehensive coverage of the subject, including both cross-sectional and time series analyses, as well as discussing the measurement of risk and prediction models that have been used by institutional investors. The studies cover many worldwide markets including the US, Japan, Asia, and Europe. The book will be invaluable for courses in financial engineering, investment and portfolio management, and as a reference for investment professionals seeking an up-to-date source on return predictability.
This advanced undergraduate/graduate textbook teaches students in finance and economics how to use R to analyse financial data and implement financial models. It demonstrates how to take publically available data and manipulate, implement models and generate outputs typical for particular analyses. A wide spectrum of timely and practical issues in financial modelling are covered including return and risk measurement, portfolio management, option pricing and fixed income analysis. This new edition updates and expands upon the existing material providing updated examples and new chapters on equities, simulation and trading strategies, including machine learnings techniques. Select data sets are available online.