R is a free, open source programming language that's become a popular standard for financial and economic analysis. Quantitative Investment Portfolio Analytics In R is your guide to getting started with modeling portfolio risk and return in R. Even if you have no experience with the software, you'll be fluent in R at a basic level after reading this short primer. The chapters provide step-by-step instructions for tapping into R's powerful capabilities for portfolio analytics.
Reproducible Finance with R: Code Flows and Shiny Apps for Portfolio Analysis is a unique introduction to data science for investment management that explores the three major R/finance coding paradigms, emphasizes data visualization, and explains how to build a cohesive suite of functioning Shiny applications. The full source code, asset price data and live Shiny applications are available at reproduciblefinance.com. The ideal reader works in finance or wants to work in finance and has a desire to learn R code and Shiny through simple, yet practical real-world examples. The book begins with the first step in data science: importing and wrangling data, which in the investment context means importing asset prices, converting to returns, and constructing a portfolio. The next section covers risk and tackles descriptive statistics such as standard deviation, skewness, kurtosis, and their rolling histories. The third section focuses on portfolio theory, analyzing the Sharpe Ratio, CAPM, and Fama French models. The book concludes with applications for finding individual asset contribution to risk and for running Monte Carlo simulations. For each of these tasks, the three major coding paradigms are explored and the work is wrapped into interactive Shiny dashboards.
Financial Risk Modelling and Portfolio Optimization with R, 2nd Edition Bernhard Pfaff, Invesco Global Asset Allocation, Germany A must have text for risk modelling and portfolio optimization using R. This book introduces the latest techniques advocated for measuring financial market risk and portfolio optimization, and provides a plethora of R code examples that enable the reader to replicate the results featured throughout the book. This edition has been extensively revised to include new topics on risk surfaces and probabilistic utility optimization as well as an extended introduction to R language. Financial Risk Modelling and Portfolio Optimization with R: Demonstrates techniques in modelling financial risks and applying portfolio optimization techniques as well as recent advances in the field. Introduces stylized facts, loss function and risk measures, conditional and unconditional modelling of risk; extreme value theory, generalized hyperbolic distribution, volatility modelling and concepts for capturing dependencies. Explores portfolio risk concepts and optimization with risk constraints. Is accompanied by a supporting website featuring examples and case studies in R. Includes updated list of R packages for enabling the reader to replicate the results in the book. Graduate and postgraduate students in finance, economics, risk management as well as practitioners in finance and portfolio optimization will find this book beneficial. It also serves well as an accompanying text in computer-lab classes and is therefore suitable for self-study.
Portfolio risk forecasting has been and continues to be an active research field for both academics and practitioners. Almost all institutional investment management firms use quantitative models for their portfolio forecasting, and researchers have explored models' econometric foundations, relative performance, and implications for capital market behavior and asset pricing equilibrium. Portfolio Risk Analysis provides an insightful and thorough overview of financial risk modeling, with an emphasis on practical applications, empirical reality, and historical perspective. Beginning with mean-variance analysis and the capital asset pricing model, the authors give a comprehensive and detailed account of factor models, which are the key to successful risk analysis in every economic climate. Topics range from the relative merits of fundamental, statistical, and macroeconomic models, to GARCH and other time series models, to the properties of the VIX volatility index. The book covers both mainstream and alternative asset classes, and includes in-depth treatments of model integration and evaluation. Credit and liquidity risk and the uncertainty of extreme events are examined in an intuitive and rigorous way. An extensive literature review accompanies each topic. The authors complement basic modeling techniques with references to applications, empirical studies, and advanced mathematical texts. This book is essential for financial practitioners, researchers, scholars, and students who want to understand the nature of financial markets or work toward improving them.
Your complete guide to quantitative analysis in the investment industry Quantitative Investment Analysis, Third Edition is a newly revised and updated text that presents you with a blend of theory and practice materials to guide you through the use of statistics within the context of finance and investment. With equal focus on theoretical concepts and their practical applications, this approachable resource offers features, such as learning outcome statements, that are targeted at helping you understand, retain, and apply the information you have learned. Throughout the text's chapters, you explore a wide range of topics, such as the time value of money, discounted cash flow applications, common probability distributions, sampling and estimation, hypothesis testing, and correlation and regression. Applying quantitative analysis to the investment process is an important task for investment pros and students. A reference that provides even subject matter treatment, consistent mathematical notation, and continuity in topic coverage will make the learning process easier—and will bolster your success. Explore the materials you need to apply quantitative analysis to finance and investment data—even if you have no previous knowledge of this subject area Access updated content that offers insight into the latest topics relevant to the field Consider a wide range of subject areas within the text, including chapters on multiple regression, issues in regression analysis, time-series analysis, and portfolio concepts Leverage supplemental materials, including the companion Workbook and Instructor's Manual, sold separately Quantitative Investment Analysis, Third Edition is a fundamental resource that covers the wide range of quantitative methods you need to know in order to apply quantitative analysis to the investment process.
This book provides readers with a systematic approach to quantitative investments and bridges the gap between theory and practice, equipping students to more seamlessly enter the world of industry. A successful quantitative investment strategy requires an individual to possess a deep understanding of the financial markets, investment theories and econometric modelings, as well as the ability to program and analyze real-world data sets. In order to connect finance theories and practical industry experience, each chapter begins with a real-world finance case study. The rest of the chapter introduces fundamental insights and theories, and teaches readers to use statistical models and R programming to analyze real-world data, therefore grounding the learning process in application. Additionally, each chapter profiles significant figures in investment and quantitative studies, so that readers can more fully understand the history of the discipline. This volume will be particularly useful to advanced students and practitioners in finance and investments.
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
A detailed, multi-disciplinary approach to investment analytics Portfolio Construction and Analytics provides an up-to-date understanding of the analytic investment process for students and professionals alike. With complete and detailed coverage of portfolio analytics and modeling methods, this book is unique in its multi-disciplinary approach. Investment analytics involves the input of a variety of areas, and this guide provides the perspective of data management, modeling, software resources, and investment strategy to give you a truly comprehensive understanding of how today's firms approach the process. Real-world examples provide insight into analytics performed with vendor software, and references to analytics performed with open source software will prove useful to both students and practitioners. Portfolio analytics refers to all of the methods used to screen, model, track, and evaluate investments. Big data, regulatory change, and increasing risk is forcing a need for a more coherent approach to all aspects of investment analytics, and this book provides the strong foundation and critical skills you need. Master the fundamental modeling concepts and widely used analytics Learn the latest trends in risk metrics, modeling, and investment strategies Get up to speed on the vendor and open-source software most commonly used Gain a multi-angle perspective on portfolio analytics at today's firms Identifying investment opportunities, keeping portfolios aligned with investment objectives, and monitoring risk and performance are all major functions of an investment firm that relies heavily on analytics output. This reliance will only increase in the face of market changes and increased regulatory pressure, and practitioners need a deep understanding of the latest methods and models used to build a robust investment strategy. Portfolio Construction and Analytics is an invaluable resource for portfolio management in any capacity.
A must-read book on the quantitative value investment strategy Warren Buffett and Ed Thorp represent two spectrums of investing: one value driven, one quantitative. Where they align is in their belief that the market is beatable. This book seeks to take the best aspects of value investing and quantitative investing as disciplines and apply them to a completely unique approach to stock selection. Such an approach has several advantages over pure value or pure quantitative investing. This new investing strategy framed by the book is known as quantitative value, a superior, market-beating method to investing in stocks. Quantitative Value provides practical insights into an investment strategy that links the fundamental value investing philosophy of Warren Buffett with the quantitative value approach of Ed Thorp. It skillfully combines the best of Buffett and Ed Thorp—weaving their investment philosophies into a winning, market-beating investment strategy. First book to outline quantitative value strategies as they are practiced by actual market practitioners of the discipline Melds the probabilities and statistics used by quants such as Ed Thorp with the fundamental approaches to value investing as practiced by Warren Buffett and other leading value investors A companion Website contains supplementary material that allows you to learn in a hands-on fashion long after closing the book If you're looking to make the most of your time in today's markets, look no further than Quantitative Value.
This book provides a comprehensive treatment of the important aspects of investment theory, security analysis, and portfolio selection, with a quantitative emphasis not to be found in most other investment texts.The statistical analysis framework of markets and institutions in the book meets the need for advanced undergraduates and graduate students in quantitative disciplines, who wish to apply their craft to the world of investments. In addition, entrepreneurs will find the volume to be especially useful. It also contains a clearly detailed explanation of many recent developments in portfolio and capital market theory as well as a thorough procedural discussion of security analysis. Professionals preparing for the CPA, CFA, and or CFP examinations will also benefit from a close scrutiny of the many problems following each chapter.The level of difficulty progresses through the textbook with more advanced treatment appearing in the latter sections of each chapter, and the last chapters of the volume.
