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"TAIL RISKS" originate from the failure of mean reversion and the idealized bell curve of asset returns, which assumes that highly probable outcomes occur near the center of the curve and that unlikely occurrences, good and bad, happen rarely, if at all, at either "tail" of the curve. Ever since the global financial crisis, protecting investments against these severe tail events has become a priority for investors and money managers, but it is something Vineer Bhansali and his team at PIMCO have been doing for over a decade. In one of the first comprehensive and rigorous books ever written on tail risk hedging, he lays out a systematic approach to protecting portfolios from, and potentially benefiting from, rare yet severe market outcomes. Tail Risk Hedging is built on the author's practical experience applying macroeconomic forecasting and quantitative modeling techniques across asset markets. Using empirical data and charts, he explains the consequences of diversification failure in tail events and how to manage portfolios when this happens. He provides an easy-to-use, yet rigorous framework for protecting investment portfolios against tail risk and using tail hedging to play offense. Tail Risk Hedging explores how to: Generate profits from volatility and illiquidity during tail-risk events in equity and credit markets Buy attractively priced tail hedges that add value to a portfolio and quantify basis risk Interpret the psychology of investors in option pricing and portfolio construction Customize explicit hedges for retirement investments Hedge risk factors such as duration risk and inflation risk Managing tail risk is today's most significant development in risk management, and this thorough guide helps you access every aspect of it. With the time-tested and mathematically rigorous strategies described here, including pieces of computer code, you get access to insights to help mitigate portfolio losses in significant downturns, create explosive liquidity while unhedged participants are forced to sell, and create more aggressive yet tail-risk-focused portfolios. The book also gives you a unique, higher level view of how tail risk is related to investing in alternatives, and of derivatives such as zerocost collars and variance swaps. Volatility and tail risks are here to stay, and so should your clients' wealth when you use Tail Risk Hedging for managing portfolios. PRAISE FOR TAIL RISK HEDGING: "Managing, mitigating, and even exploiting the risk of bad times are the most important concerns in investments. Bhansali puts tail risk hedging and tail risk management under a microscope--pricing, implementation, and showing how we can fine-tune our risk exposures, which are all crucial ways in how we can better weather our bad times." -- ANDREW ANG, Ann F. Kaplan Professor of Business at Columbia University "This book is critical and accessible reading for fiduciaries, financial consultants and investors interested in both theoretical foundations and practical considerations for how to frame hedging downside risk in portfolios. It is a tremendous resource for anyone involved in asset allocation today." -- CHRISTOPHER C. GECZY, Ph.D., Academic Director, Wharton Wealth Management Initiative and Adj. Associate Professor of Finance, The Wharton School "Bhansali's book demonstrates how tail risk hedging can work, be concretely implemented, and lead to higher returns so that it is possible to have your cake and eat it too! A must read for the savvy investor." -- DIDIER SORNETTE, Professor on the Chair of Entrepreneurial Risks, ETH Zurich
Reshape your investing strategy for an increasingly uncertain world “An engrossing, fast-paced, terrific read for anyone interested in the financial imbalances due to too much reliance on math and too little respect for indeterminacy.” —Tyler Durden, ZeroHedge.com The world does not unfold according to a fixed set of rules. It is a dynamical system whose evolution looks like a bell curve with fat “tails.” The same is true of financial markets. However, every day we rely on the certainty and precision of mathematical strategies that assume the contrary to control and grow wealth in markets. Tail Risk Killers shows you how the rigidity of model-based thinking has led to the fragility of today’s global financial marketplace, and it explains how to use adaptive trading strategies to mitigate risk in impending market conditions. Risk management veteran Jeff McGinn pokes holes in prevalent assumptions about how financial markets act that tend to underestimate the likelihood of occurrence of extreme events. Through clear, conversational writing, real-world anecdotes, and easy-tofollow formulas, he provides a glimpse into the way tomorrow’s successful traders are viewing financial markets—with an eye for probability distributions. While illustrating how to protect your assets from tail risk, he shows you how to: Implement the six axioms for risk management Prepare for the unintended consequences of central banks suppressing tail risk Identify and avoid the dark risks hidden in today’s derivative-laden financial system Anticipate the fate of credit default swaps that may not face extinction McGinn argues that the intervention of central banks has robbed global markets of their opportunities to adapt, but this highly relevant book shows you that it is not too late to adapt your portfolio to survive the extreme events that happen more often than popular financial models suggest. Tail Risk Killers helps you discover useful information and processes beyond the focus of industry standards, helps you connect the dots of evolving trading strategies and time your next trade for maximum profitability.
This paper presents a simple heuristic measure of tail risk, which is applied to individual bank stress tests and to public debt. Stress testing can be seen as a first order test of the level of potential negative outcomes in response to tail shocks. However, the results of stress testing can be misleading in the presence of model error and the uncertainty attending parameters and their estimation. The heuristic can be seen as a second order stress test to detect nonlinearities in the tails that can lead to fragility, i.e., provide additional information on the robustness of stress tests. It also shows how the measure can be used to assess the robustness of public debt forecasts, an important issue in many countries. The heuristic measure outlined here can be used in a variety of situations to ascertain an ordinal ranking of fragility to tail risks.
The year 2008 was a watershed year as dramatic market movements exposed the flaws in the theory and practice of pension fund management. Solvency declined dramatically, hedge funds did not deliver, rebalancing policies detracted value and liquidity dried up tainting the allure of "alternative" investments. Static policies for dynamic markets are undoubtedly flawed and have to be changed with the support of appropriate liquid, transparent and low cost benchmarks; implicit bets need to be made explicit and managed; naive performance measures have to be improved; and the CAPM needs to be revamped dramatically. But this process can only start with investors taking the time to understand how various market factors influence assets or managers and then develop a set of rules so that as the factors evolve over time, the optimal portfolio evolves simultaneously. SMART (Systematic Management of Assets using a Rules-based Technique) management of assets and liabilities leads to improved solvency and a lowering of ALM risks. SMART is about introducing good process namely, only measured and monitored risks can be managed. This book presents a new design for pension fund management that allows CIOs to be smart about managing assets relative to liabilities and, at the same time, allows them to access alpha flexibly (and compensate managers only when they demonstrate skill), thereby improving solvency.
Financial Risk Forecasting is a complete introduction to practical quantitative risk management, with a focus on market risk. Derived from the authors teaching notes and years spent training practitioners in risk management techniques, it brings together the three key disciplines of finance, statistics and modeling (programming), to provide a thorough grounding in risk management techniques. Written by renowned risk expert Jon Danielsson, the book begins with an introduction to financial markets and market prices, volatility clusters, fat tails and nonlinear dependence. It then goes on to present volatility forecasting with both univatiate and multivatiate methods, discussing the various methods used by industry, with a special focus on the GARCH family of models. The evaluation of the quality of forecasts is discussed in detail. Next, the main concepts in risk and models to forecast risk are discussed, especially volatility, value-at-risk and expected shortfall. The focus is both on risk in basic assets such as stocks and foreign exchange, but also calculations of risk in bonds and options, with analytical methods such as delta-normal VaR and duration-normal VaR and Monte Carlo simulation. The book then moves on to the evaluation of risk models with methods like backtesting, followed by a discussion on stress testing. The book concludes by focussing on the forecasting of risk in very large and uncommon events with extreme value theory and considering the underlying assumptions behind almost every risk model in practical use – that risk is exogenous – and what happens when those assumptions are violated. Every method presented brings together theoretical discussion and derivation of key equations and a discussion of issues in practical implementation. Each method is implemented in both MATLAB and R, two of the most commonly used mathematical programming languages for risk forecasting with which the reader can implement the models illustrated in the book. The book includes four appendices. The first introduces basic concepts in statistics and financial time series referred to throughout the book. The second and third introduce R and MATLAB, providing a discussion of the basic implementation of the software packages. And the final looks at the concept of maximum likelihood, especially issues in implementation and testing. The book is accompanied by a website - www.financialriskforecasting.com – which features downloadable code as used in the book.
This book is a compilation of recent articles written by leading academics and practitioners in the area of risk-based and factor investing (RBFI). The articles are intended to introduce readers to some of the latest, cutting edge research encountered by academics and professionals dealing with RBFI solutions. Together the authors detail both alternative non-return based portfolio construction techniques and investing style risk premia strategies. Each chapter deals with new methods of building strategic and tactical risk-based portfolios, constructing and combining systematic factor strategies and assessing the related rules-based investment performances. This book can assist portfolio managers, asset owners, consultants, academics and students who wish to further their understanding of the science and art of risk-based and factor investing. - Contains up-to-date research from the areas of RBFI - Features contributions from leading academics and practitioners in this field - Features discussions of new methods of building strategic and tactical risk-based portfolios for practitioners, academics and students
It is widely acknowledged that many financial modelling techniques failed during the financial crisis, and in our post-crisis environment many techniques are being reconsidered. This single volume provides a guide to lessons learned for practitioners and a reference for academics. Including reviews of traditional approaches, real examples, and case studies, contributors consider portfolio theory; methods for valuing equities and equity derivatives, interest rate derivatives, and hybrid products; and techniques for calculating risks and implementing investment strategies. Describing new approaches without losing sight of their classical antecedents, this collection of original articles presents a timely perspective on our post-crisis paradigm. Highlights pre-crisis best classical practices, identifies post-crisis key issues, and examines emerging approaches to solving those issues Singles out key factors one must consider when valuing or calculating risks in the post-crisis environment Presents material in a homogenous, practical, clear, and not overly technical manner
Destined to become a market classic, Dynamic Hedging is the only practical reference in exotic options hedgingand arbitrage for professional traders and money managers Watch the professionals. From central banks to brokerages to multinationals, institutional investors are flocking to a new generation of exotic and complex options contracts and derivatives. But the promise of ever larger profits also creates the potential for catastrophic trading losses. Now more than ever, the key to trading derivatives lies in implementing preventive risk management techniques that plan for and avoid these appalling downturns. Unlike other books that offer risk management for corporate treasurers, Dynamic Hedging targets the real-world needs of professional traders and money managers. Written by a leading options trader and derivatives risk advisor to global banks and exchanges, this book provides a practical, real-world methodology for monitoring and managing all the risks associated with portfolio management. Nassim Nicholas Taleb is the founder of Empirica Capital LLC, a hedge fund operator, and a fellow at the Courant Institute of Mathematical Sciences of New York University. He has held a variety of senior derivative trading positions in New York and London and worked as an independent floor trader in Chicago. Dr. Taleb was inducted in February 2001 in the Derivatives Strategy Hall of Fame. He received an MBA from the Wharton School and a Ph.D. from University Paris-Dauphine.
In the aftermath of the recent financial crisis, the federal government has pursued significant regulatory reforms, including proposals to measure and monitor systemic risk. However, there is much debate about how this might be accomplished quantitatively and objectively—or whether this is even possible. A key issue is determining the appropriate trade-offs between risk and reward from a policy and social welfare perspective given the potential negative impact of crises. One of the first books to address the challenges of measuring statistical risk from a system-wide persepective, Quantifying Systemic Risk looks at the means of measuring systemic risk and explores alternative approaches. Among the topics discussed are the challenges of tying regulations to specific quantitative measures, the effects of learning and adaptation on the evolution of the market, and the distinction between the shocks that start a crisis and the mechanisms that enable it to grow.