Global asset allocation new methods and applications

Global Asset Allocation John Wiley & Sons Founded in 1807, John Wiley & Sons is the oldest independent publishing company in the United States With offices in North America, Europe, Australia, and Asia, Wiley is globally committed to developing and marketing print and electronic products and services for our customers’ professional and personal knowledge and understanding The Wiley Finance series contains books written specifically for finance and investment professionals as well as sophisticated individual investors and their financial advisors Book topics range from portfolio management to e-commerce, risk management, financial engineering, valuation and financial instrument analysis, as well as much more For a list of available titles, please visit our Web site at www.WileyFinance.com Global Asset Allocation New Methods and Applications HEINZ ZIMMERMANN WOLFGANG DROBETZ PETER OERTMANN John Wiley & Sons, Inc Copyright © 2003 by Heinz Zimmermann, Wolfgang Drobetz, and Peter Oertmann All rights reserved Published by John Wiley & Sons, Inc., Hoboken, New Jersey Published simultaneously in Canada No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400, fax 978-750-4470, or on the web at www.copyright.com Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, 201-748-6011, fax 201-748-6008, e-mail: permcoordinator@wiley.com Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose No warranty may be created or extended by sales representatives or written sales materials The advice and strategies contained herein may not be suitable for your situation You should consult with a professional where appropriate Neither the publisher nor author shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages For general information on our other products and services, or technical support, please contact our Customer Care Department within the United States at 800-762-2974, outside the United States at 317-572-3993 or fax 317-572-4002 Wiley also publishes its books in a variety of electronic formats Some content that appears in print may not be available in electronic books For more information about Wiley products, visit our Web site at www.wiley.com Library of Congress Cataloging-in-Publication Data: Zimmermann, Heinz Global asset allocation : new methods and applications / Heinz Zimmermann, Wolfgang Drobetz, Peter Oertmann p cm — (Wiley finance series) ISBN 0-471-26426-1 (cloth : alk paper) Asset allocation Investments, Foreign Globalization —Economic aspects I Drobetz, Wolfgang II Oertmann, Peter III Title IV Series HG4529.5.Z56 2003 332.67’3—dc21 2002009972 Printed in the United States of America 10 preface his book is about global asset allocation decisions The benefits of international asset allocation have been recognized for a long time H Grubel, H Levy, M Sarnat, and B Solnik demonstrated the benefits of international diversification more than 25 years ago, when only a small number of global investment opportunities were available This picture has drastically changed Most institutional investors, such as pension plans or insurance companies, invest a substantial part of their assets in foreign markets, sectors, and currencies, and mutual funds offer a wide range of global investment products at reasonable cost The globalization of the economy has progressed dramatically in this time period, which is particularly true for the internationalization of the financial system, including the banking sector Financial services have become a truly global business Many excellent books have been published on these topics over the past years, for example, Frankel (1994), Ledermann and Klein (1994), Giddy (1994), Jorion and Khoury (1995), Solnik (2000), Smith and Walter (2000), to mention just a few The distinguishing feature of this book is its attempt to incorporate recent methodological advances in the treatment of the various topics Much progress has been made in the statistical modeling of time-varying risk and return characteristics of financial markets These tools make it possible to shed new light on the time-varying relationship between volatility and the correlation between markets and sectors, and to investigate the implications for international asset allocation strategies This literature also suggests a “dynamic” view of the risk-return trade-off of financial assets: Risk premia are time-varying and predictable based on changing business conditions Numerous econometric research has tested the time-series and cross-sectional implications of conditional multifactor asset pricing models This research has major implications for the implementation of dynamic (tactical) asset allocation T v vi PREFACE strategies, as well as the measurement of investment performance Finally, a substantial part of the recent progress in the asset pricing literature relies on test strategies based on stochastic deflators This approach is extremely useful to investigate the degree to which markets are integrated or segmented in terms of the pricing of systematic risk across national borders, sectors, or entire asset classes This has important implications for asset allocation strategies, but also for corporate funding decisions This book focuses on the practical applications of these methodological advances for global asset pricing and portfolio decisions Original empirical work is presented throughout the book Most of the chapters were originally presented at two Global Asset Allocation Conferences organized by Peter Oertmann and Heinz Zimmermann in October 1999 and October 2000, respectively, in Zurich, Switzerland We are grateful to the Swiss Institute of Banking and Finance (s/bf) at the University of St Gallen for hosting the conferences The senior author of this book was then a director of the Institute The presented papers were evaluated by the organizers of the first conference, and a few were refereed by outside reviewers Earlier versions of Chapters and 10 were published in the Journal of Financial Markets and Portfolio Management, where a German version of Chapter was published also All chapters have been updated and revised from the papers originally presented While the three authors of this book bear full responsibility for the content of this volume, we gratefully acknowledge the contribution of David Rey, the author of Chapter 4, who did an excellent job in preparing the final version of the entire manuscript; and of Viola Markert, co-author of Chapter We also acknowledge the motivating comments and suggestions by the participants of the conferences, as well as by our students and colleagues We hope that this volume will stimulate further research in this area HEINZ ZIMMERMANN WOLFGANG DROBETZ PETER OERTMANN Basel and St Gallen, Switzerland October 2002 contents CHAPTER The Global Economy and Investment Management Executive Summary Motivation Globalization and Risk Globalization and Expected Returns Globalization and the Market Price of Risk Tactical Asset Allocation and Estimation Risk About This Book 2 4 CHAPTER International Asset Pricing, Portfolio Selection, and Currency Hedging: An Overview Executive Summary Introduction Valuation in an International Setting: Basic Facts Purchasing Power Relationships The Core Problem of International Asset Pricing Portfolio Selection and Asset Pricing I Utility-Based Asset Pricing Models—Overview The Basic International Capital Asset Pricing Model (IntCAPM) without Deviations from PPP Portfolio Separation and the IntCAPM in Real Terms The IntCAPM in Nominal Terms Portfolio Selection and Asset Pricing II Accounting for PPP Deviations and “Real” Exchange Rate Risk The Solnik-Sercu International Asset Pricing Model From Partial to General Equilibrium General Models Accounting for Domestic Inflation Currency Hedging Equilibrium Currency Hedging Universal Currency Hedging 10 12 13 13 14 15 16 18 18 19 27 30 36 37 38 vii viii CONTENTS Free Lunch and Full Currency Hedging Overlay Currency Hedges International Arbitrage Pricing Theory Pricing Condition with Currency Risk Adjustment The Solnik Pricing Condition Summing Up the Main Streams CHAPTER The Anatomy of Volatility and Stock Market Correlations Executive Summary Introduction Data and Descriptive Statistics An Asymmetrical Model of Volatility The Correlation Structure of International Stock Returns Correlation and Volatility Upmarket and Downmarket Correlations Business Cycles and Correlations Investment Implications Diversification in Upmarkets and Downmarkets Shortfall Risk Value-at-Risk Option Pricing Conclusion CHAPTER The Correlation Breakdown in International Stock Markets Executive Summary Motivation Analysis of the Stock Return Series Description of the Data Summary Statistics International Equity Market Correlations Time-Measured Observations Moving Estimation Windows Realized Correlation Constructed from Daily Data Is There a Time Trend? Event-Measured Observations Correlation Breakdown What Actually Is an (Extreme) Event on Financial Markets? 39 40 41 42 45 47 51 51 51 53 58 64 64 70 74 76 77 79 80 84 86 89 89 90 91 92 92 93 95 96 98 101 105 105 106 Contents Empirical Evidence: Based on Realized Correlations Empirical Evidence: Based on Monthly Return Data Implications for Asset Management Optimal Portfolios from Event-Varying Variance-Covariance Matrices Conclusion CHAPTER Global Economic Risk Profiles: Analyzing Value and Volatility Drivers in Global Markets Executive Summary Introduction Empirical Methodology The Return-Generating Process The Pricing Restriction Data Description Stock and Bond Market Returns Specification of Global Risk Factors GERP—A First Inspection of the Markets’ Risk Profiles Factor Profiles for Stock Markets Factor Profiles for Bond Markets Explanatory Power of the Factor Models Discriminating between Volatility and Value Drivers Testing the Pricing Potential of the Risk Factors: Wald Tests Potential Value Drivers for Stock Markets Potential Value Drivers for Bond Markets Choosing the Common Factors Assessing the Power of Value Drivers: Testing the Pricing Equation Conclusion Appendix CHAPTER Testing Market Integration: The Case of Switzerland and Germany Executive Summary Introduction Integration and Correlation ix 107 110 115 116 119 121 121 121 123 124 125 126 126 127 129 131 133 133 134 134 135 137 137 138 141 142 145 145 146 150 306 10 11 12 13 14 15 16 17 18 NOTES portfolio weights along the efficient frontier, there is a substantial short position only in the Canadian market Short positions in the emerging markets are modest See Ferson, Foerster and Keim (1993) for a derivation of these moment conditions on the basis of traditional beta pricing models There is one restriction on the coefficients in the C matrix for each test asset However, note that ex post there is always some discount factor that prices both MSCI and IFC markets (see Hansen & Jagannathan, 1991) In equilibrium, all market participants hold the tangency (market) portfolio The choice of this strategy is also convenient from a computational point of view, because a closed-form solution is available for this portfolio (see Merton, 1971) For example, see Rudolf and Zimmermann (1998a) For an application of a strategy that applies conditioning information to emerging markets data see Harvey (1994) See Stein (1955) for the original reference See Jorion (1986) for a derivation The general form of the Stein-estimator is well known from standard Bayesian analysis Estimation risk is measured as the average loss of an investor’s utility in repeated samples Technically spoken, the Stein-estimator is admissible relative to a quadratic loss function This implies that there is no alternative estimator with at least equal and sometimes lower estimation risk for any value of the true unknown mean return The summation of the components of a quadratic loss function allows increased risk to some individual components of the expected returns vector and less to others Contrary to this view, Drobetz and Wegmann (1999) show that mean reversion is consistent with rational asset pricing Of course, weights have to sum to one and, hence, there are some markets in the sample that have to be sold short from time to time It turns out that the high weights for Switzerland during the late 1980s imply negative weights for the Canadian stock market Notes 307 Chapter The Structure of Sector and Market Returns: Implications for International Diversification See Drummen and Zimmermann (1992), Heston and Rouwenhorst (1994, 1995), Furrer and Herger (1999), Beckers, Grinold, Rudd, and Stefek (1992), among others Detailed results are available from the authors upon request Notice, moreover, a small inconsistency in the calculation of the country and sector trends, which is caused by the successive inclusion of younger countries in the index universe (Poland or Turkey, for instance) Stocks of these countries constitute a new country index These countries are also included in the respective sector indices As constituents of the sector indices the stocks of “new” countries immediately enter the sector trend calculation As the constituents of the new country index, however, they enter the country trend calculation with a time lag of 12 months, since each new index needs to have a 12-month history before its correlation/volatility can be calculated and, hence, before it can be included in the average trend The same problem will arise in the calculation of the sector and country efficient frontiers in section The countries that are excluded are Luxembourg, Poland, China, Argentine, Brazil, Columbia, and Brazil As mentioned in the previous footnote, this partly distorts the comparability of country and sector performances: The countries cannot be included in the country portfolios, but they enter the return calculation of the sector indices However, the influence of these countries in the sector indices is negligible, because they only account for 1.77 percent of the market capitalization altogether These returns differ from the country and sector returns in Table 8.4, because the descriptive statistics are based on continuously compounded returns, whereas the portfolio calculations are based on simple returns Chapter 10 Integrating Tactical and Equilibrium Portfolio Management: Putting the Black-Litterman Model to Work See Chan, Karceski, and Lakonishok (1999) for a recent attempt to condition the covariance matrix on macroeconomic variables 308 NOTES Throughout the examples we assume a coefficient of relative risk aversion γ of 3 See Drobetz (2000) for a discussion and empirical results of spanning tests using volatility bounds for stochastic discount factors See Black and Littermann (1992), p 32 See Black and Litterman (1992), p 33 See Black and Litterman (1992), p 35 and the appendix, and Chapter in Lee (2000) See Lee (2000) for a more in-depth analysis See Pitts (1997b), p 13 See Lee (2000), p 176 and the Appendix in Black and Litterman (1992), p 42 10 For a discussion of Bayes’ Law see for example Hamilton (1994) 11 See point in the Appendix in Black and Litterman (1992) They suggest that the solution can be derived by the “mixed estimation” of Theil (1971) 12 The parameter τ is set equal to 0.3 Larger values of τ indicate less confidence in the equilibrium returns, which seems nonintuitive index Adler-Dumas multi-beta IntCAPM, 7, 33–34, 48 Allocation strategies, sector vs country, 199–228 basic issues (three), 201–202 correlations between stocks within countries vs within sectors, 227–228 efficient frontiers, 219–227 analyzing specific portfolios, 223–227 simple diversification strategies, 219–222 two-dimensional diversification strategies, 222–223 extreme market events, 216–219 crash of 1987, 216–217 crash of 1998, emerging markets, 217 Kuwait Invasion of 1990, 217 Russia Crisis 1998, 217 stock market downturn in 2000, 217, 228 overview/introduction, 199–202, 227–228 problem setup (two numerical examples), 202–208 range of efficient portfolios, 228 structure of the indices, 208–216 characteristics of the Datastream Index Family, 208–209 descriptive statistics of Datastream country indices, 210 descriptive statistics of Datastream sector indices, 212–213 statistical properties of the index returns, 209–214 temporal behavior of index volatilities and correlations, 214–216 volatility of sector and subsector returns, 228 Arbitrage pricing theory (APT), 8, 9, 41–47, 123 international (IntAPM), 41–47 pricing condition with currency risk adjustment, 41–45 Solnik pricing condition, 45–47 unconditional beta pricing model, 123 valuation framework and, 23 ARCH, 60 See also GARCH (Generalized Autoregressive Conditional Heteroscedasticity) model Asset pricing models See International asset pricing models (IntAPMs) Autocorrelations, 178 309 310 Beta pricing model (latent variable model), 149–150, 157–158 data description, 163–164 derivation of single latent variable model from the familiar beta pricing restriction, 169–171 empirical results, 166–168 Black-Litterman model (integrating tactical and equilibrium portfolio management), 261–285 annualized volatilities and market-capitalization weights, 284 correlation structure between Dow Jones STOXX sectors, 285 deficiencies of standard portfolio theory, 263–267 amount of required input data, 263–264 extreme portfolio weights, 264–266 mismatch in levels of information, 267 sensitivity of portfolio weights, 266 neutral views as starting point, 267–271 overview/introduction, 261–263, 283–284 process/steps, 271–277 combining certain views, 275–276 combining uncertain views, 276–277 expressing views, 273–275 long-term equilibrium, 272–273 simple example, 277–283 incorporating absolute view, 280–283 INDEX incorporating relative view, 277–280 views: absolute, 280–283 certain, 275–276 expressing, 273–275 neutral, 267–271 relative, 277–280 uncertain, 276–277 Business cycles, correlations and, 74–76 Capital Asset Pricing Model (CAPM), 7, 8, 13 Black-Litterman approach closely linked to, 268 Consumption (CCAPM), 153 integration testing and, 148 International (IntCAMP), 9, 30, 47 basic model without deviations from PPP, 14–15 in nominal terms, 16–18 in real terms, 15–16 Intertemporal (ICAPM), 13 multibeta/single-beta, value-growth spread testing of ad hoc modification, 230–231 high-minus-low (HML) bookto-market (BM) factor, 230 small-minus-big factor (SMB), 231 Clustering, volatility, 58, 61 Consumer price index (CPI), 11 Consumption-based IntCAPM, Stulz, 35–36 Consumption-based test of market integration, 152–157 data description, 161–163 empirical results, 164–166 Index Consumption Capital Asset Pricing Model (CCAPM), 153–154 Consumption tastes, national (heterogeneity of), 12–13 Correlation: of value premiums/value-growth spreads, 239–244 volatility and (see Volatility and stock market correlations) Correlation breakdown in international stock markets, 89–120 definition, 105–106 event-measured observations, 105–116 empirical evidence (based on monthly return data), 110–115 empirical evidence (based on realized correlations), 107–109 extreme events on financial markets, 106–107 implications for asset management, 115–116, 120 motivation, 90–91 optimal portfolios from eventvarying variance-covariance matrices, 89, 116–119 overview/introduction, 89–90, 119–120 risk management and, 89 stock return series analysis, 91–95 assumption (that continuously compounded stock market returns are multivariate normally distributed), 91, 119–120 data description, 92 311 international equity market correlations, 93–95 summary statistics, 92–93 time-measured observations, 95–104 moving estimation windows, 96–98 realized correlation constructed from daily data, 98–101 time trends, 101–104 Country: allocation strategies (see Allocation strategies, sector vs country) definition (in asset pricing theories), 13 Crash of 1987, 216–217 Crash of 1998, emerging markets, 217 Currency forward contracts, equilibrium expected return on, 29–30 Currency hedging, 7, 36–41 analysis of equilibrium conditions for, 36–41 equilibrium, 37 full (free lunch and), 39–40 overlay, 40–41 portfolio selection and, 20–24, 31–33 universal, 38–39 Currency risk: accounting for PPP deviations and “real” exchange rate risk, 18–19 integrative survey of models, pricing condition with adjustment for, 41–45 Datastream/Primark index family, 208–209 312 Diversification: emerging markets and, 183–187 factors risk profiles and, 130 international allocation strategies (see Allocation strategies, sector vs country) sectors/countries: analyzing specific portfolios, 223–227 simple strategies, 219–222 two-dimensional strategies, 222–223 in upmarkets and downmarkets, 77–78 Downmarkets: correlations, 70–74, 105–106 diversification in, 77–78 Efficient frontiers, 183, 184, 219–227 analyzing specific portfolios, 223–227 simple diversification strategies, 219–222 two-dimensional diversification strategies, 222–223 EGARCH, 61, 62, 63, 64 See also GARCH (Generalized Autoregressive Conditional Heteroscedasticity) model Emerging market investments, 173–198 data description, 176–183 analysis of distribution of stock market returns, 180 correlations between international stock returns, 179 countries, 175 summary statistics for emerging and developed stock market returns, 177 INDEX distributional characteristics of stock market returns, 173 diversification and, 183–187 mean-variance analysis revisited, 187–190 motivation, 174–176 overview/introduction, 173, 197–198 simulating portfolio strategies with/without shrinkage, 192–197 investment in IFC markets, 196–197 investment in MSCI markets, 196 simultaneous investment in MSCI and IFC markets, 194–196 Stein-estimator, 173, 190–192, 197 Equilibrium: condition for risk-free assets, 28 conditions for currency hedging, 36–41 expected return on currency forward contracts, 29–30 expected stock returns, 30 long-term (Black-Litterman approach), 272–273 from partial to general, 27–30 portfolio management (integrating with tactical) (see Black-Litterman model (integrating tactical and equilibrium portfolio management)) Equity home bias puzzle, 36, 116–117 Euler equation, 153 Exchange rate risk See Currency risk Index Expected returns, globalization and, 3–4 Extreme event on financial markets (defined), 106–107 Fat tails, 54 Fundamental analysis, factors risk profiles and, 130 G7 countries, and global risk factors, 127–129 GARCH (Generalized Autoregressive Conditional Heteroscedasticity) model, 58, 60–64, 148 ARCH, 60 EGARCH, 61, 62, 63, 64 GARCH-in-the-mean approach, 148 Generalized Method of Moments (GMM), 139, 140, 148, 156, 161, 181, 185 Global dividend yield (GLDIVY), 246–247 Global economic risk profiles (GERPs), 121–144 analysis, 129–134 explanatory power of the factor models, 133–134 factor profiles for bond markets, 133 factor profiles for stock markets, 131–133 statistics for predetermined global risk factors, 130 applications in portfolio management, 130–131 assessing power of value drivers: testing the pricing equation, 138–141 data description, 126–129 313 G7 countries, and global risk factors, 127–129 specification of global risk factors, 127–129 stock and bond market returns, 126–127 discriminating between volatility and value drivers, 134–138 choosing the common factors, 137 potential value drivers for bond markets, 137 potential value drivers for stock markets, 135–137 testing the pricing potential of the risk factors (Wald tests), 134–135, 138 diversification and, 130 empirical methodology, 123–126 pricing restriction, 125–126 return-generating process, 124–125 fundamental analysis and, 130 hedging and, 130 major findings: single-factor CAPM, 141 three-factor model, 141 overview/introduction, 121–123, 141–142 pricing potential, 130 regression of stock and bond markets excess returns on predetermined global risk factors, 143–144 Global economy and investment management, 1–6 globalization and expected returns, 3–4 globalization and market price of risk, globalization and risk, 2–3 314 Global economy and investment management (Continued) motivation, overview, Global efficient frontier, 183, 184 See also Efficient frontiers Global real interest rate (GLREAL), 245–246 Global risk factors: G7 countries and, 127–129 regression of stock and bond markets excess returns on, 143–144 specification of, 127–129 statistics for, 130 Global stock market volatility (GLVOLA), 245 Global term spread (TERMSP), 246 Hedging: currency (see Currency hedging) factors risk profiles and, 130 Heteroscedasticity, 59 Home bias puzzle, 36, 116–117 Inflation: general models accounting for domestic, 30–36 risk premiums, 34–35 Integration, testing for market (vs market segmentation), 145–171 asset-pricing theory perspective, 147 consumption-based test, 152–157 data description, 161–163 empirical results, 164–166 correlation and integration, 150–152 data description, 161–164 empirical results of the tests, 164–168 INDEX joint test of two hypotheses, 148 latent variable model (beta pricing model with an unobservable benchmark portfolio), 149–150, 157–158 data description, 163–164 derivation of single latent variable model from the familiar beta pricing restriction, 169–171 empirical results, 166–168 models (two) for, 149, 152–161 moving correlations of excess returns (Germany and Switzerland), 151 overview/introduction, 146–150, 168–169 stochastic discount factor (SDF), 149, 153 valuation perspective, 147 International arbitrage pricing theory (IntAPM), 8, 9, 41–47, 123 pricing condition with currency risk adjustment, 41–45 pricing restriction proposed by Solnik, 45–47 unconditional beta pricing model, 123 valuation framework and, 123 International asset pricing models (IntAPMs), 7–49 basic facts about valuation in international setting, 9–13 core problem (heterogeneity of national consumption tastes), 12–13 purchasing power relationships, 10–12 currency hedging, 36–41 315 Index vs domestic asset pricing models, and international arbitrage pricing theory, 41–47 overview/introduction, 7–9, 47–49 International asset pricing models and portfolio selection, 13–36 accounting for PPP deviations and “real” exchange rate risk, 18–19 general models accounting for domestic inflation, 30–36, 47–49 Adler-Dumas multi-beta IntCAPM, 33–34 home country bias, 36 inflation risk premiums, 34–35 portfolio selection and currency hedging in the general model, 31–33 Stulz consumption-based IntCAPM, 35–36 IntCAPM in nominal terms, 16–18 IntCAPM in real terms, 15–16 IntCAPM without deviations from PPP, 14–15 from partial to general equilibrium, 27–30 equilibrium condition for riskfree assets, 28 equilibrium expected return on currency forward contracts, 29–30 equilibrium expected stock returns, 30 Solnik-Sercu International Asset Pricing Model (SS-IAPM), 19–27, 47–48 portfolio selection and currency hedging, 20–24 pricing restriction, 24–27 utility-based asset pricing models (overview), 13–14, 48–49 International CAPM See Capital Asset Pricing Model (CAPM) International Finance Corporation (IFC) indices for emerging stock markets, 176 International setting: correlation (see Correlation) emerging markets (see Emerging market investments) liberalization and deregulation of capital markets, 1, market imperfections, 13 strategies (see Allocation strategies, sector vs country) valuation in (basic facts), 9–13 value-growth spreads (see Valuegrowth spreads, international (enigma of)) Intertemporal CAPM (ICAPM), 13 Inverse relative global wealth (INRELW), 245 Kuwait invasion (1990), 217 Latent variable model (beta pricing model with unobservable benchmark portfolio), 149–150, 157–158 data description, 163–164 derivation of single latent variable model from the familiar beta pricing restriction, 169–171 empirical results, 166–168 Log-portfolio, 21 Market price of risk, and globalization, Mean-variance approach, 186, 187–190, 192, 261 316 Modern portfolio theory See Portfolio theory, modern Moody’s U.S credit spread (CREDSP), 246 Morgan Stanley Capital Investment (MSCI) database, 176 Multibeta pricing models, 8, 49 Multivariate distribution of large returns for five largest stock markets, 106 Neutral views, 267–271 Option pricing, 84–86 Overlay currency hedges, 40–41 Portfolio management: applications of Global Economic Risk Profiles (GERPs), 130–131 diversification, 130 fundamental analysis, 130 hedging, 130 pricing potential, 130 tactical/equilibrium (integrating) (see Black-Litterman model (integrating tactical and equilibrium portfolio management)) Portfolio selection, and asset pricing, 13–36 accounting for PPP deviations and “real” exchange rate risk, 18–19 general models accounting for domestic inflation, 30–36 Adler-Dumas multi-beta IntCAPM, 33–34 home country bias, 36 inflation risk premiums, 34–35 INDEX portfolio selection and currency hedging in the general model, 31–33 Stulz consumption-based IntCAPM, 35–36 IntCAPM in nominal terms, 16–18 IntCAPM in real terms, 15–16 IntCAPM without deviations from PPP, 14–15 from partial to general equilibrium, 27–30 equilibrium condition for riskfree assets, 28 equilibrium expected return on currency forward contracts, 29–30 equilibrium expected stock returns, 30 Solnik-Sercu International Asset Pricing Model (SS-IAPM), 19–27 portfolio selection and currency hedging, 20–24 pricing restriction, 24–27 utility-based asset pricing models (overview), 13–14 Portfolio theory, modern, 262–267 amount of required input data, 263–264 Black-Litterman and, 262–263 (see also Black-Litterman model (integrating tactical and equilibrium portfolio management)) deficiencies of, 263–267 extreme portfolio weights, 264–266 mismatch in levels of information, 267 Index sensitivity of portfolio weights, 266 Pricing, arbitrage See Arbitrage pricing theory (APT) Pricing kernel, 153 Pricing potential, factors risk profiles and, 130 Purchasing power parity (PPP): absolute/relative, 10–12 concept of, 10–12 deviations, accounting for (and “real” exchange rate risk), 18–19 and international asset pricing, relationships, 10–12 Regression framework, instrumental, 244–247 estimation results of instrumental regressions, 247 variables: global dividend yield (GLDIVY), 246–247 global real interest rate (GLREAL), 245–246 global stock market volatility (GLVOLA), 245 global term spread (TERMSP), 246 inverse relative global wealth (INRELW), 245 Moody’s U.S credit spread (CREDSP), 246 Treasury-Eurodollar spread (TEDSPR), 246 U.S purchasing manager index (BUSCLI), 245 Regression of stock and bond markets excess returns on predetermined global risk factors, 143–144 317 Risk: currency, 7, 18–19, 41–45 globalization and, 1, 2–3, market price of (and globalization), shortfall, 79–80 Risk-free assets, equilibrium condition for, 28 Risk premiums through three main channels, Risk profiles, global economic (GERPs), 121–144 analysis, 129–134 explanatory power of the factor models, 133–134 factor profiles for bond markets, 133 factor profiles for stock markets, 131–133 statistics for predetermined global risk factors, 130 applications in portfolio management, 130–131 assessing power of value drivers: testing the pricing equation, 138–141 data description, 126–129 G7 countries, and global risk factors, 127–129 specification of global risk factors, 127–129 stock and bond market returns, 126–127 discriminating between volatility and value drivers, 134–138 choosing the common factors, 137 potential value drivers for bond markets, 137 potential value drivers for stock markets, 135–137 318 Risk profiles, global economic (GERPs) (Continued) testing the pricing potential of the risk factors (Wald tests), 134–135, 138 diversification and, 130 empirical methodology, 123–126 pricing restriction, 125–126 return-generating process, 124–125 fundamental analysis and, 130 hedging and, 130 major findings: single-factor CAPM, 141 three-factor model, 141 overview/introduction, 121–123, 141–142 pricing potential and, 130 regression of stock and bond markets excess returns on predetermined global risk factors, 143–144 Russian crisis (1998), 217 Sector allocation See Allocation strategies, sector vs country Semicorrelation analysis, 73, 105–106 Sharpe ratios, 193–197, 198 Shortfall risk, 79–80 Short selling, 189 Solnik-Sercu International Asset Pricing Model (SS-IAPM), 19–27, 30, 47–48 portfolio selection and currency hedging, 20–24 pricing restriction, 24–27 Spanning tests, 173, 184–186, 197 Stein-estimator, 173, 190–192, 197 Stochastic discount factor (SDF), 149, 153–154, 158 INDEX Stock market(s): extreme events, 216–219 five largest, 106 Stulz consumption-based IntCAPM, 35–36 Time trends (correlation and volatility), 101–104 Treasury-Eurodollar spread (TEDSPR), 246 United States purchasing manager index (BUSCLI), 245 Universal currency hedging, 38–39 Upmarket and downmarket correlations, 70–74, 105–106 Utility-based asset pricing models, 13–14, 48–49 Valuation in international setting (basic facts), 9–13 Value-at-risk (VaR), 80–84 Value drivers: analyzing value and volatility drivers in global markets (see Global economic risk profiles (GERPs)) assessing power of (testing the pricing equation), 138–141 for bond markets, 137 for stock markets, 135–137 vs volatility, 123, 134–138 Value-growth spreads, international (enigma of), 229–260 data description, 233–234 economics of, 244–253 empirical facts on, 234–244 international correlations of value premiums, 239–244 Index international correlations of year-to-year value-growth spreads, 242 long-horizon value premiums, 234–237 short-horizon value premiums, 237–239 statistics on value/growth stock returns, 235 statistics on year-to-year valuegrowth spreads, 238 year-to-year value-growth spreads, 236 exploration of phenomenon, 230–231 global forces driving value premiums, 248–250 global integration of value premiums, 250–253 insights from empirical analysis, 232–233 instrumental regression framework, 244–247 estimation results of, 247 global dividend yield (GLDIVY), 246–247 global real interest rate (GLREAL), 245–246 global stock market volatility (GLVOLA), 245 global term spread (TERMSP), 246 inverse relative global wealth (INRELW), 245 Moody’s U.S credit spread (CREDSP), 246 Treasury-Eurodollar spread (TEDSPR), 246 U.S purchasing manager index (BUSCLI), 245 variables (eight), 245–247 319 open questions for value investors, 231–232 overview/introduction, 230–233, 259–260 tactical style rotation strategies, 253–259 devising simple switching strategy, 253 performance of active valuegrowth strategies, 253–259 risk/return of tactical-style rotation vs passive-style investment, 254 Value investors, open questions for, 231–232 Value premiums: global forces driving, 248–250 global integration of, 250–253 international correlations of, 239–244 long-horizon, 234–237 short-horizon, 237–239 Variance-covariance matrices, 89, 116–119 Vector autoregressive model (VAR), 125 Volatility(ies): asymmetrical model of, 58–64 estimated news impact curves, 63 GARCH model, 58 returns and volatility forecast (Swiss case), 59 clustering, 58, 61 drivers vs value drivers, 123–124 Volatility and stock market correlations, 51–87, 89 See also Correlation arguments offered by investment professionals, 52 320 Volatility and stock market correlations (Continued) correlation structure of international stock returns, 64–76 business cycles and correlations, 74–76 correlation and volatility, 64–70 upmarket and downmarket correlations, 70–74 data and descriptive statistics, 53–58 descriptive statistics, 54 INDEX matrix of stock market correlations, 58 up- and down-volatilities, 57 findings of empirical regularities, 86–87 investment implications, 76–86 diversification in upmarkets and downmarkets, 77–78 option pricing, 84–86 shortfall risk, 79–80 value-at-risk (VaR), 80–84 overview/introduction, 51–53 Wald tests, 134–135, 138 ... Heinz Global asset allocation : new methods and applications / Heinz Zimmermann, Wolfgang Drobetz, Peter Oertmann p cm — (Wiley finance series) ISBN 0-471-26426-1 (cloth : alk paper) Asset allocation. .. Basel and St Gallen, Switzerland October 2002 contents CHAPTER The Global Economy and Investment Management Executive Summary Motivation Globalization and Risk Globalization and Expected Returns Globalization... Australia, and Asia, Wiley is globally committed to developing and marketing print and electronic products and services for our customers’ professional and personal knowledge and understanding The