Introduction to Risk Parity and Budgeting


Book Description

Although portfolio management didn't change much during the 40 years after the seminal works of Markowitz and Sharpe, the development of risk budgeting techniques marked an important milestone in the deepening of the relationship between risk and asset management. Risk parity then became a popular financial model of investment after the global fina




Advanced REIT Portfolio Optimization


Book Description

This book provides an investor-friendly presentation of the premises and applications of the quantitative finance models governing investment in one asset class of publicly traded stocks, specifically real estate investment trusts (REITs). The models provide highly advanced analytics for REIT investment, including: portfolio optimization using both historic and predictive return estimation; model backtesting; a complete spectrum of risk assessment and management tools with an emphasis on early warning systems, risk budgeting, estimating tail risk, and factor analysis; derivative valuation; and incorporating ESG ratings into REIT investment. These quantitative finance models are presented in a unified framework consistent with dynamic asset pricing (rational finance). Given its scope and practical orientation, this book will appeal to investors interested in portfolio optimization and innovative tools for investment risk assessment.




Handbook of Portfolio Construction


Book Description

Portfolio construction is fundamental to the investment management process. In the 1950s, Harry Markowitz demonstrated the benefits of efficient diversification by formulating a mathematical program for generating the "efficient frontier" to summarize optimal trade-offs between expected return and risk. The Markowitz framework continues to be used as a basis for both practical portfolio construction and emerging research in financial economics. Such concepts as the Capital Asset Pricing Model (CAPM) and the Arbitrage Pricing Theory (APT), for example, provide the foundation for setting benchmarks, for predicting returns and risk, and for performance measurement. This volume showcases original essays by some of today’s most prominent academics and practitioners in the field on the contemporary application of Markowitz techniques. Covering a wide spectrum of topics, including portfolio selection, data mining tests, and multi-factor risk models, the book presents a comprehensive approach to portfolio construction tools, models, frameworks, and analyses, with both practical and theoretical implications.




Risk-Based Approaches to Asset Allocation


Book Description

This book focuses on the concepts and applications of risk-based asset allocation. Markowitz’s traditional approach to asset allocation suffers from serious drawbacks when implemented. These mainly arise from the estimation risk associated with the necessary input the most critical being expected returns. With the financial crisis, there has been an increasing interest in asset allocation approaches that don’t need expected returns as input, known as risk-based approaches. The book provides an analysis of the different solutions that fit this description: the equal-weighting approach, the global minimum-variance approach, the most diversified portfolio approach and the risk parity approach. In addition to a theoretical discussion of these, it presents practical applications in different investment environments. Three different evaluation dimensions are considered to put these approaches to the test: financial efficiency, diversification and portfolio stability.




Machine Learning for Asset Management


Book Description

This new edited volume consists of a collection of original articles written by leading financial economists and industry experts in the area of machine learning for asset management. The chapters introduce the reader to some of the latest research developments in the area of equity, multi-asset and factor investing. Each chapter deals with new methods for return and risk forecasting, stock selection, portfolio construction, performance attribution and transaction costs modeling. This volume will be of great help to portfolio managers, asset owners and consultants, as well as academics and students who want to improve their knowledge of machine learning in asset management.







Modern Investment Management


Book Description

Dieser Band füllt eine echte Marktlücke. "Goldman Sach's Modern Investment" gibt eine Einführung in moderne Investment Management Verfahren, wie sie von Goldman Sachs Asset Management verwendet werden, um erstklassige Investitionsrenditen zu erzielen. Erläutert werden u.a. die moderne Portfoliotheorie (Portfoliodiversifikation zur Risikostreuung), Capital Asset Pricing (Verfahren zur Ermittlung des Risiko-Rendite-Austauschverhältnisses von Finanzanlagen, bei dem der unterschiedliche Risikogehalt von Finanztiteln berücksichtigt wird) sowie eine Reihe aktueller Themen wie z.B. strategische Portfoliostrukturierung, Risikobudgetierung und aktives Portfolio Management. Hier erhalten Sie die Mittel an die Hand, um die Goldman Sachs Asset Management Methode für sich selbst umzusetzen. Das von Fischer Black und Bob Litterman gemeinsam entwickelte Black-Litterman Asset Allocation Model gehört zu den angesehensten und meist verwendeten Modellen zur Portfoliostrukturierung. Litterman und seine Asset Management Group sind oft die treibende Kraft, wenn es um Portfoliostrukturierung und Investmententscheidungen der 100 international größten Pensionsfonds geht.




Strategic Asset Allocation


Book Description

Academic finance has had a remarkable impact on many financial services. Yet long-term investors have received curiously little guidance from academic financial economists. Mean-variance analysis, developed almost fifty years ago, has provided a basic paradigm for portfolio choice. This approach usefully emphasizes the ability of diversification to reduce risk, but it ignores several critically important factors. Most notably, the analysis is static; it assumes that investors care only about risks to wealth one period ahead. However, many investors—-both individuals and institutions such as charitable foundations or universities—-seek to finance a stream of consumption over a long lifetime. In addition, mean-variance analysis treats financial wealth in isolation from income. Long-term investors typically receive a stream of income and use it, along with financial wealth, to support their consumption. At the theoretical level, it is well understood that the solution to a long-term portfolio choice problem can be very different from the solution to a short-term problem. Long-term investors care about intertemporal shocks to investment opportunities and labor income as well as shocks to wealth itself, and they may use financial assets to hedge their intertemporal risks. This should be important in practice because there is a great deal of empirical evidence that investment opportunities—-both interest rates and risk premia on bonds and stocks—-vary through time. Yet this insight has had little influence on investment practice because it is hard to solve for optimal portfolios in intertemporal models. This book seeks to develop the intertemporal approach into an empirical paradigm that can compete with the standard mean-variance analysis. The book shows that long-term inflation-indexed bonds are the riskless asset for long-term investors, it explains the conditions under which stocks are safer assets for long-term than for short-term investors, and it shows how labor income influences portfolio choice. These results shed new light on the rules of thumb used by financial planners. The book explains recent advances in both analytical and numerical methods, and shows how they can be used to understand the portfolio choice problems of long-term investors.




Beyond Diversification: What Every Investor Needs to Know About Asset Allocation


Book Description

Generate solid, long-term profits with a portfolio allocated for your investing needs Asset allocation is the key to investing performance. Unfortunately, no single approach works perfectly—developing the right balance requires a clear-eyed look at the many models available to you, various investing methodologies, and your or your client’s level of risk tolerance. And that’s where this important guide comes in. Written by a leading allocation expert from T. Rowe Price, Beyond Diversification provides the knowledge, insights, and approaches you need to make the best allocation decisions for your goals. This deep dive into the how’s and why’s of asset allocation is organized by the three decisive components of a successfully allocated portfolio: Return Forecasting discusses the desired return investors seek. Risk Forecasting covers the level of risk investors are prepared to assume to achieve that return. Portfolio Construction calibrates the stock-bond mix that balances the risks and returns. With examples from T. Rowe Price’s asset allocation team showing you how the process works in the real world, Beyond Diversification provides everything you need to find the asset combination that will deliver the results you seek. You’ll learn how to choose the right tradeoffs, build the most effective asset allocation combination for your needs, and dramatically increase your odds of success for the long run.




Financial Risk Modelling and Portfolio Optimization with R


Book Description

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.