Portfolio Management in Practice, Volume 1 E-Book

• Herausgeber: John Wiley & Sons
• Kategorie: Fachliteratur
• Serie: The CFA Institute Series
• Sprache: Englisch

Seitenzahl: 551

Veröffentlichungsjahr: 2020

Beschreibung

The companion workbook to the Investment Management volume in the CFA Institute's Portfolio Management in Practice series provides students and professionals with essential practice regarding key concepts in the portfolio management process. Filled with stimulating exercises, this text is designed to help learners explore the multifaceted topic of investment management in a meaningful and productive way. The Investment Management Workbook is structured to further readers' hands-on experience with a variety of learning outcomes, summary overview sections, challenging practice questions, and solutions. Featuring the latest tools and information to help users become confident and knowledgeable investors, this workbook includes sections on professionalism in the industry, fintech, hedge fund strategies, and more. With the workbook, readers will learn to: * Form capital market expectations * Understand the principles of the asset allocation process * Determine comprehensive investment strategies within each asset class * Integrate considerations specific to high net worth individuals or institutions into the selection of strategies * Execute and evaluate chosen strategies and investment managers Well suited for individuals who learn on their own, this companion resource delivers an example-driven method for practicing the tools and techniques covered in the primary Investment Management volume, incorporating world-class exercises based on actual scenarios faced by finance professionals every day.

Leseprobe

CFA Institute is the premier association for investment professionals around the world, with over 170,000 members more than 160 countries. Since 1963 the organization has developed and administered the renowned Chartered Financial Analyst Program. With a rich history of leading the investment profession, CFA Institute has set the highest standards in ethics, education, and professional excellence within the global investment community, and is the foremost authority on investment profession conduct and practice.

Each book in the CFA Institute Investment Series is geared toward industry practitioners along with graduate-level finance students and covers the most important topics in the industry. The authors of these cutting-edge books are themselves industry professionals and academics and bring their wealth of knowledge and expertise to this series.

PORTFOLIO MANAGEMENT IN PRACTICE WORKBOOK

Volume IInvestment Management

Cover image: © r.nagy/Shutterstock

Cover design: Wiley

Copyright © 2004, 2007, 2015, 2021 by CFA Institute. 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, [phone], fax [phone], 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, [phone], fax [phone], or online at http://www.wiley.com/go/permissions.

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 for technical support, please contact our Customer Care Department within the United States at [phone], outside the United States at [phone], or fax [phone].

Wiley publishes in a variety of print and electronic formats and by print-on-demand. Some material included with standard print versions of this book may not be included in e-books or in print-on-demand. If this book refers to media such as a CD or DVD that is not included in the version you purchased, you may download this material at http://booksupport.wiley.com. For more information about Wiley products, visit www.wiley.com.

ISBN 978-1-119-74375-0

ISBN 978-1-119-74363-7 (ePDF)

ISBN 978-1-119-74373-6 (ePub)

Contents

Cover

Title Page

Copyright

PART I: LEARNING OBJECTIVES, SUMMARY OVERVIEW, AND PROBLEMS

CHAPTER 1: PROFESSIONALISM IN THE INVESTMENT MANAGEMENT

LEARNING OUTCOMES

SUMMARY

PRACTICE PROBLEMS

CHAPTER 2: FINTECH IN INVESTMENT MANAGEMENT

LEARNING OUTCOMES

SUMMARY

PRACTICE PROBLEMS

CHAPTER 3: CAPITAL MARKET EXPECTATIONS, PART 1: FRAMEWORK AND MACRO CONSIDERATIONS

LEARNING OUTCOMES

SUMMARY

PRACTICE PROBLEM

CHAPTER 4: CAPITAL MARKET EXPECTATIONS, PART 2: FORECASTING ASSET CLASS RETURNS

LEARNING OUTCOMES

SUMMARY

PRACTICE PROBLEMS

CHAPTER 5: OVERVIEW OF ASSET ALLOCATION

LEARNING OUTCOMES

SUMMARY

PRACTICE PROBLEMS

CHAPTER 6: PRINCIPLES OF ASSET ALLOCATION

LEARNING OUTCOMES

SUMMARY

PRACTICE PROBLEMS

CHAPTER 7: ASSET ALLOCATION WITH REAL-WORLD CONSTRAINTS

LEARNING OUTCOMES

SUMMARY

PRACTICE PROBLEMS

CHAPTER 8: CURRENCY MANAGEMENT: AN INTRODUCTION

LEARNING OUTCOMES

SUMMARY

PRACTICE PROBLEMS

CHAPTER 9: OVERVIEW OF FIXED-INCOME PORTFOLIO MANAGEMENT

LEARNING OUTCOMES

SUMMARY

PRACTICE PROBLEMS

CHAPTER 10: LIABILITY-DRIVEN AND INDEX-BASED STRATEGIES

LEARNING OUTCOMES

SUMMARY

PRACTICE PROBLEMS

CHAPTER 11: OVERVIEW OF EQUITY PORTFOLIO MANAGEMENT

LEARNING OUTCOMES

SUMMARY

PRACTICE PROBLEMS

CHAPTER 12: PASSIVE EQUITY INVESTING

LEARNING OUTCOMES

SUMMARY

PRACTICE PROBLEMS

CHAPTER 13: ACTIVE EQUITY INVESTING: STRATEGIES

LEARNING OUTCOMES

SUMMARY

PRACTICE PROBLEMS

CHAPTER 14: HEDGE FUND STRATEGIES

LEARNING OUTCOMES

SUMMARY

PRACTICE PROBLEMS

CHAPTER 15: OVERVIEW OF PRIVATE WEALTH MANAGEMENT

LEARNING OUTCOMES

SUMMARY

PRACTICE PROBLEMS

CHAPTER 16: TOPICS IN PRIVATE WEALTH MANAGEMENT

LEARNING OUTCOMES

SUMMARY

PRACTICE PROBLEMS

CHAPTER 17: PORTFOLIO MANAGEMENT FOR INSTITUTIONAL INVESTORS

LEARNING OUTCOMES

SUMMARY

PRACTICE PROBLEMS

CHAPTER 18: TRADE STRATEGY AND EXECUTION

LEARNING OUTCOMES

SUMMARY

PRACTICE PROBLEMS

CHAPTER 19: PORTFOLIO PERFORMANCE EVALUATION

LEARNING OUTCOMES

SUMMARY

PRACTICE PROBLEMS

CHAPTER 20: INVESTMENT MANAGER SELECTION

LEARNING OUTCOMES

SUMMARY

PRACTICE PROBLEMS

PART II: SOLUTIONS

CHAPTER 1: PROFESSIONALISM IN THE INVESTMENT MANAGEMENT

SOLUTIONS

CHAPTER 2: FINTECH IN INVESTMENT MANAGEMENT

SOLUTIONS

CHAPTER 3: CAPITAL MARKET EXPECTATIONS, PART I: FRAMEWORK AND MACRO CONSIDERATIONS

SOLUTIONS

CHAPTER 4: CAPITAL MARKET EXPECTATIONS, PART II: FORECASTING ASSET CLASS RETURNS

SOLUTIONS

CHAPTER 5: OVERVIEW OF ASSET ALLOCATION

SOLUTIONS

CHAPTER 6: PRINCIPLES OF ASSET ALLOCATION

SOLUTIONS

CHAPTER 7: ASSET ALLOCATION WITH REAL-WORLD CONSTRAINTS

SOLUTIONS

CHAPTER 8: CURRENCY MANAGEMENT: AN INTRODUCTION

SOLUTIONS

CHAPTER 9: OVERVIEW OF FIXED-INCOME PORTFOLIO MANAGEMENT

SOLUTIONS

CHAPTER 10: LIABILITY-DRIVEN AND INDEX-BASED STRATEGIES

SOLUTIONS

CHAPTER 11: OVERVIEW OF EQUITY PORTFOLIO MANAGEMENT

SOLUTIONS

CHAPTER 12: PASSIVE EQUITY INVESTING

SOLUTIONS

CHAPTER 13: ACTIVE EQUITY INVESTING: STRATEGIES

SOLUTIONS

CHAPTER 14: HEDGE FUND STRATEGIES

SOLUTIONS

CHAPTER 15: OVERVIEW OF PRIVATE WEALTH MANAGEMENT

SOLUTIONS

CHAPTER 16: TOPICS IN PRIVATE WEALTH MANAGEMENT

SOLUTIONS

CHAPTER 17: PORTFOLIO MANAGEMENT FOR INSTITUTIONAL INVESTORS

SOLUTIONS

CHAPTER 18: TRADE STRATEGY AND EXECUTION

SOLUTIONS

CHAPTER 19: PORTFOLIO PERFORMANCE EVALUATION

SOLUTIONS

CHAPTER 20: INVESTMENT MANAGER SELECTION

SOLUTIONS

ABOUT THE CFA PROGRAM

END USER LICENSE AGREEMENT

Guide

Table of Contents

Begin Reading

Pages

i

ii

iii

iv

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

61

62

63

64

65

66

67

68

69

70

71

72

73

74

75

76

77

78

79

80

81

82

83

84

85

86

87

88

89

90

91

92

93

94

95

96

97

98

99

100

101

102

103

104

105

106

107

108

109

110

111

112

113

114

115

116

117

118

119

120

121

122

123

124

125

126

127

128

129

130

131

132

133

134

135

136

137

138

139

140

141

142

143

144

145

146

147

148

149

150

151

152

153

154

155

156

157

158

159

160

161

162

163

164

165

166

167

168

169

170

171

172

173

174

175

176

177

178

179

180

181

182

183

184

185

186

187

188

189

190

191

192

193

194

195

196

197

198

199

200

201

202

203

204

205

206

207

208

209

210

211

212

213

214

215

216

217

218

219

220

221

222

223

224

225

226

227

228

229

230

231

232

233

234

235

236

237

238

239

240

241

242

243

244

245

246

247

248

249

250

251

252

253

254

255

256

257

258

259

260

261

262

263

264

265

266

267

268

269

270

271

272

273

274

275

276

277

278

279

280

281

282

283

284

285

286

287

288

289

290

291

292

293

294

295

296

297

298

299

300

301

302

303

304

305

306

307

308

309

310

311

312

313

314

315

316

317

318

319

320

321

322

323

324

325

326

327

328

329

330

331

332

333

334

PART I

LEARNING OBJECTIVES, SUMMARY OVERVIEW, AND PROBLEMS

CHAPTER 1

PROFESSIONALISM IN THE INVESTMENT MANAGEMENT

LEARNING OUTCOMES

The candidate should be able to:

describe how professions establish trust;

explain professionalism in investment management;

describe expectations of investment professionals;

describe a framework for ethical decision-making.

SUMMARY

A profession is an occupational group that has specific education, expert knowledge, and a framework of practice and behavior that underpins community trust, respect, and recognition.

The requirement to uphold high ethical standards is one clear difference between professions and craft guilds or trade bodies.

A primary goal of professions is to establish trust among clients and among society in general.

Common characteristics of professions include normalization of practitioner behavior, service to society, client focus, high entry standards, a body of expert knowledge, encouragement and facilitation of continuing education, monitoring of professional conduct, collegiality, recognized overseeing bodies, and encouragement of member engagement.

The investment profession has become increasingly global, driven by the opening of capital markets, coordination of regulation across borders, and the emergence of technology.

Investment professionals are trusted to draw on a body of formal knowledge and apply that knowledge with care and judgement. In comparison to clients, investment professionals are also expected to have superior financial expertise, technical knowledge, and knowledge of the applicable laws and regulations.

As a professional body, CFA Institute gathers knowledge from practicing investment professionals, develops high quality curricula, conducts rigorous examinations, contributes to new research in finance, and ensures practitioner involvement in developing its codes and values.

Legal standards are often rule based. Ethical conduct goes beyond legal standards, balancing self-interest with the direct and indirect consequences of behavior on others.

Investment professionals are likely to encounter dilemmas, including those with ethical implications. Professionals should consider carefully how to determine the facts of the issue and assess the implications.

A framework for ethical decision making can help people look at and evaluate a decision from different perspectives, enabling them to identify important issues, make wise decisions, and limit unintended consequences.

Regulation has helped raise professional standards by making them a requirement for practice, although sometimes at the expense of autonomy and flexibility.

Perhaps the greatest challenge for the investment management profession comes from technology. Rapid advances in computing power, data storage and internet connectivity are changing the definition of professional expertise and how it is applied to serve investors.

PRACTICE PROBLEMS

High ethical standards are distinguishing features of which of the following bodies?

Craft guilds

Trade bodies

Professional bodies

Fiduciary duty is a standard

most likely

to be upheld by members of a(n):

employer.

profession.

not-for-profit body.

To maintain trust, the investment management profession must be interdependent with:

regulators.

employers.

investment firms.

When an ethical dilemma occurs, an investment professional should

most likely

first raise the issue with a:

mentor outside the firm.

professional body’s hotline.

senior individual in the firm.

CHAPTER 2

FINTECH IN INVESTMENT MANAGEMENT

LEARNING OUTCOMES

The candidate should be able to:

describe “fintech;”

describe Big Data, artificial intelligence, and machine learning;

describe fintech applications to investment management;

describe financial applications of distributed ledger technology.

SUMMARY

The term “fintech” refers to technological innovation in the design and delivery of financial services and products.

Areas of fintech development include the analysis of large datasets, analytical techniques, automated trading, automated advice, and financial record keeping.

Big Data is characterized by the three Vs—volume, velocity, and variety—and includes both traditional and non-traditional (or alternative) datasets.

Among the main sources of alternative data are data generated by individuals, business processes, and sensors.

Artificial intelligence computer systems are capable of performing tasks that traditionally required human intelligence at levels comparable (or superior) to those of human beings.

Machine learning seeks to extract knowledge from large amounts of data by “learning” from known examples and then generating structure or predictions. Simply put, ML algorithms aim to “find the pattern, apply the pattern.” Main types of ML include supervised learning, unsupervised learning, and deep learning.

Natural language processing is an application of text analytics that uses insight into the structure of human language to analyze and interpret text- and voice-based data.

Robo-advisory services are providing automated advisory services to increasing numbers of retail investors. Services include asset allocation, portfolio optimization, trade execution, rebalancing, and tax strategies.

Big Data and ML techniques may provide insights into real-time and changing market circumstances to help identify weakening or adverse trends in advance, allowing for improved risk management and investment decision-making.

Algorithmic traders use automated trading programs to determine when, where, and how to trade an order on the basis of pre-specified rules and market conditions. Benefits include speed of executions, lower trading costs, and anonymity.

Blockchain and distributed ledger technology (DLT) may offer a new way to store, record, and track financial assets on a secure, distributed basis. Applications include cryptocurrencies and tokenization. Additionally, DLT may bring efficiencies to post-trade and compliance processes through automation, smart contracts, and identity verification.

PRACTICE PROBLEMS

A correct description of fintech is that it:

is driven by rapid growth in data and related technological advances.

increases the need for intermediaries.

is at its most advanced state using systems that follow specified rules and instructions.

A characteristic of Big Data is that:

one of its traditional sources is business processes.

it involves formats with diverse types of structures.

real-time communication of it is uncommon due to vast content.

In the use of machine learning (ML):

some techniques are termed “black box” due to data biases.

human judgment is not needed because algorithms continuously learn from data.

training data can be learned too precisely, resulting in inaccurate predictions when used with different datasets.

Text Analytics is appropriate for application to:

economic trend analysis.

large, structured datasets.

public but not private information.

In providing investment services, robo-advisers are

most likely

to:

rely on their cost effectiveness to pursue active strategies.

offer fairly conservative advice as easily accessible guidance.

be free from regulation when acting as fully-automated wealth managers.

Which of the following statements on fintech’s use of data as part of risk analysis is correct?

Stress testing requires precise inputs and excludes qualitative data.

Machine learning ensures that traditional and alternative data are fully segregated.

For real-time risk monitoring, data may be aggregated for reporting and used as model inputs.

A factor associated with the widespread adoption of algorithmic trading is increased:

market efficiency.

average trade sizes.

trading destinations.

A benefit of distributed ledger technology (DLT) favoring its use by the investment industry is its:

scalability of underlying systems.

ease of integration with existing systems.

streamlining of current post-trade processes.

What is a distributed ledger technology (DLT) application suited for physical assets?

Tokenization

Cryptocurrencies

Permissioned networks

CHAPTER 3

CAPITAL MARKET EXPECTATIONS, PART 1: FRAMEWORK AND MACRO CONSIDERATIONS

LEARNING OUTCOMES

The candidate should be able to:

discuss the role of, and a framework for, capital market expectations in the portfolio management process;

discuss challenges in developing capital market forecasts;

explain how exogenous shocks may affect economic growth trends;

discuss the application of economic growth trend analysis to the formulation of capital market expectations;

compare major approaches to economic forecasting;

discuss how business cycles affect short- and long-term expectations;

explain the relationship of inflation to the business cycle and the implications of inflation for cash, bonds, equity, and real estate returns;

discuss the effects of monetary and fiscal policy on business cycles;

interpret the shape of the yield curve as an economic predictor and discuss the relationship between the yield curve and fiscal and monetary policy;

identify and interpret macroeconomic, interest rate, and exchange rate linkages between economies.

SUMMARY

This is the first of two chapters on how investment professionals should address the setting of capital market expectations. The chapter began with a general framework for developing capital market expectations followed by a review of various challenges and pitfalls that analysts may encounter in the forecasting process. The remainder of the chapter focused on the use of macroeconomic analysis in setting expectations. The following are the main points covered in the chapter:

Capital market expectations are essential inputs for strategic as well as tactical asset allocation.

The ultimate objective is a set of projections with which to make informed investment decisions, specifically asset allocation decisions.

Undue emphasis should not be placed on the accuracy of projections for individual asset classes. Internal consistency across asset classes (cross-sectional consistency) and over various time horizons (intertemporal consistency) are far more important objectives.

The process of capital market expectations setting involves the following steps:

Specify the set of expectations that are needed, including the time horizon(s) to which they apply.

Research the historical record.

Specify the method(s) and/or model(s) that will be used and their information requirements.

Determine the best sources for information needs.

Interpret the current investment environment using the selected data and methods, applying experience and judgment.

Provide the set of expectations and document the conclusions.

Monitor outcomes, compare to forecasts, and provide feedback.

Among the challenges in setting capital market expectations are:

limitations of economic data

including lack of timeliness as well as changing definitions and calculations;

data measurement errors and biases

including transcription errors, survivorship bias, and appraisal (smoothed) data;

limitations of historical estimates

including lack of precision, nonstationarity, asynchronous observations, and distributional considerations such as fat tails and skewness;

ex post

risk as a biased risk measure

such as when historical returns reflect expectations of a low-probability catastrophe that did not occur or capture a low-probability event that did happen to occur;

bias in methods

including data-mining and time-period biases;

failure to account for conditioning information

;

misinterpretation of correlations

;

psychological biases

including anchoring, status quo, confirmation, overconfidence, prudence, and availability biases.

model uncertainty

.

Losing sight of the connection between investment outcomes and the economy is a fundamental, and potentially costly, mistake in setting capital market expectations.

Some growth trend changes are driven by slowly evolving and easily observable factors that are easy to forecast. Trend changes arising from exogenous shocks are impossible to forecast and difficult to identify, assess, and quantify until the change is well established.

Among the most important sources of shocks are policy changes, new products and technologies, geopolitics, natural disasters, natural resources/critical inputs, and financial crises.

An economy’s aggregate trend growth rate reflects growth in labor inputs and growth in labor productivity. Extrapolating past trends in these components can provide a reasonable initial estimate of the future growth trend, which can be adjusted based on observable information. Less developed economies may require more significant adjustments because they are likely to be undergoing more rapid structural changes.

The average level of real (nominal) default-free bond yields is linked to the trend rate of real (nominal) growth. The trend rate of growth provides an important anchor for estimating bond returns over horizons long enough for this reversion to prevail over cyclical and short-term forces.

The trend growth rate provides an anchor for long-run equity appreciation. In the very long run, the aggregate value of equity must grow at a rate very close to the rate of GDP growth.

There are three main approaches to economic forecasting:

Econometric models

: structural and reduced-form statistical models of key variables generate quantitative estimates, impose discipline on forecasts, may be robust enough to approximate reality, and can readily forecast the impact of exogenous variables or shocks. However, they tend to be complex, time-consuming to formulate, and potentially mis-specified, and they rarely forecast turning points well.

Indicators

: variables that lead, lag, or coincide with turns in the economy. This approach is the simplest, requiring only a limited number of published statistics. It can generate false signals, however, and is vulnerable to revisions that may overfit past data at the expense of the reliability of out-of-sample forecasts.

Checklist(s)

: subjective integration of information deemed relevant by the analyst. This approach is the most flexible but also the most subjective. It readily adapts to a changing environment, but ongoing collection and assessment of information make it time-consuming and also limit the depth and consistency of the analysis.

The business cycle is the result of many intermediate frequency cycles that jointly generate most of the variation in aggregate economic activity. This explains why historical business cycles have varied in both duration and intensity and why it is difficult to project turning points in real time.

The business cycle reflects decisions that (a) are made based on imperfect information and/or analysis with the expectation of future benefits, (b) require significant current resources and/or time to implement, and (c) are difficult and/or costly to reverse. Such decisions are, broadly defined, investment decisions.

A typical business cycle has a number of phases. We split the cycle into five phases with the following capital market implications:

Initial Recovery.

Short-term interest rates and bond yields are low. Bond yields are likely to bottom. Stock markets may rise strongly. Cyclical/riskier assets such as small stocks, high-yield bonds, and emerging market securities perform well.

Early Expansion.

Short rates are moving up. Longer-maturity bond yields are stable or rising slightly. Stocks are trending up.

Late Expansion.

Interest rates rise, and the yield curve flattens. Stock markets often rise but may be volatile. Cyclical assets may underperform while inflation hedges outperform.

Slowdown.

Short-term interest rates are at or nearing a peak. Government bond yields peak and may then decline sharply. The yield curve may invert. Credit spreads widen, especially for weaker credits. Stocks may fall. Interest-sensitive stocks and “quality” stocks with stable earnings perform best.

Contraction.

Interest rates and bond yields drop. The yield curve steepens. The stock market drops initially but usually starts to rise well before the recovery emerges. Credit spreads widen and remain elevated until clear signs of a cycle trough emerge.

At least three factors complicate translation of business cycle information into capital market expectations and profitable investment decisions. First, the phases of the cycle vary in length and amplitude. Second, it is not always easy to distinguish between cyclical forces and secular forces acting on the economy and the markets. Third, how, when, and by how much the markets respond to the business cycle is as uncertain as the cycle itself—perhaps more so.

Business cycle information is likely to be most reliable/valuable in setting capital market expectations over horizons within the range of likely expansion and contraction phases. Transitory developments cloud shorter-term forecasts, whereas significantly longer horizons likely cover portions of multiple cycle phases. Information about the current cyclical state of the economy has no predictive value over very long horizons.

Monetary policy is often used as a mechanism for intervention in the business cycle. This mechanism is inherent in the mandates of most central banks to maintain price stability and/or growth consistent with potential.

Monetary policy aims to be countercyclical, but the ability to fine-tune the economy is limited and policy measures may exacerbate rather than moderate the business cycle. This risk is greatest at the top of the cycle when the central bank may overestimate the economy’s momentum and/or underestimate the potency of restrictive policies.

Fiscal policy—government spending and taxation—can be used to counteract cyclical fluctuations in the economy. Aside from extreme situations, however, fiscal policy typically addresses objectives other than regulating short-term growth. So-called automatic stabilizers do play an important role in mitigating cyclical fluctuations.

The Taylor rule is a useful tool for assessing a central bank’s stance and for predicting how that stance is likely to evolve.

The expectation that central banks could not implement negative policy rates proved to be unfounded in the aftermath of the 2007–2009 global financial crisis. Because major central banks combined negative policy rates with other extraordinary measures (notably quantitative easing), however, the effectiveness of the negative rate policy is unclear. The effectiveness of quantitative easing is also unclear.

Negative interest rates, and the environment that gives rise to them, make the task of setting capital market expectations even more complex. Among the issues that arise are the following:

It is difficult to justify negative rates as a “risk-free rate” to which risk premiums can be added to establish long-term “equilibrium” asset class returns.

Historical data and quantitative models are even less likely to be reliable.

Market relationships (e.g., the yield curve) are likely to be distorted by other concurrent policy measures.

The mix of monetary and fiscal policies has its most apparent effect on the average level of interest rates and inflation. Persistently loose (tight) fiscal policy increases (reduces) the average level of real interest rates. Persistently loose (tight) monetary policy increases (reduces) the average levels of actual and expected inflation. The impact on nominal rates is ambiguous if one policy is persistently tight and the other persistently loose.

Changes in the slope of the yield curve are driven primarily by the evolution of short rate expectations, which are driven mainly by the business cycle and policies. The slope of the curve may also be affected by debt management.

The slope of the yield curve is useful as a predictor of economic growth and as an indicator of where the economy is in the business cycle.

Macroeconomic linkages between countries are expressed through their respective current and capital accounts.

There are four primary mechanisms by which the current and capital accounts are kept in balance: changes in income (GDP), relative prices, interest rates and asset prices, and exchange rates.

In the short run, interest rates, exchange rates, and financial asset prices must adjust to keep the capital account in balance with the more slowly evolving current account. The current account, in conjunction with real output and the relative prices of goods and services, tends to reflect secular trends and the pace of the business cycle.

Interest rates and currency exchange rates are inextricably linked. This relationship is evident in the fact that a country cannot simultaneously allow unfettered capital flows, maintain a fixed exchange rate, and pursue an independent monetary policy.

Two countries will share a default-free yield curve if (and only if) there is perfect capital mobility and the exchange rate is credibly fixed

forever

. It is the lack of credibly fixed exchange rates that allows (default-free) yield curves, and hence bond returns, to be less than perfectly correlated across markets.

With floating exchange rates, the link between interest rates and exchange rates is primarily expectational. To equalize risk-adjusted expected returns across markets, interest rates must be higher (lower) in a currency that is expected to depreciate (appreciate). This dynamic can lead to the exchange rate “overshooting” in one direction to generate the expectation of movement in the opposite direction.

An investor cares about the real return that he or she expects to earn

in his or her own

currency

. In terms of a foreign asset, what matters is the

nominal

return and the change in the exchange rate.

Although real interest rates around the world need not be equal, they are linked through the requirement that global savings must always equal global investment. Hence, they will tend to move together.

PRACTICE PROBLEMS

The following information relates to Questions 1–8

Neshie Wakuluk is an investment strategist who develops capital market expectations for an investment firm that invests across asset classes and global markets. Wakuluk started her career when the global markets were experiencing significant volatility and poor returns; as a result, she is now careful to base her conclusions on objective evidence and analytical procedures to mitigate any potential biases.

Wakuluk’s approach to economic forecasting utilizes a structural model in conjunction with a diffusion index to determine the current phase of a country’s business cycle. This approach has produced successful predictions in the past, thus Wakuluk has high confidence in the predictions. Wakuluk also determines whether any adjustments need to be made to her initial estimates of the respective aggregate economic growth trends based on historical rates of growth for Countries X and Y (both developed markets) and Country Z (a developing market). Exhibit 1 summarizes Wakuluk’s predictions:

EXHIBIT 1 Prediction for Current Phase of the Business Cycle

Country X

Country Y

Country Z

Initial Recovery

Contraction

Late Upswing

Wakuluk assumes short-term interest rates adjust with expected inflation and are procyclical. Wakuluk reviews the historical short-term interest rate trends for each country, which further confirms her predictions shown in Exhibit 1.

Wakuluk decides to focus on Country Y to determine the path of nominal interest rates, the potential economic response of Country Y’s economy to this path, and the timing for when Country Y’s economy may move into the next business cycle. Wakuluk makes the following observations:

Observation 1:

Monetary policy has been persistently loose for Country Y, while fiscal policies have been persistently tight.

Observation 2:

Country Y is expected to significantly increase transfer payments and introduce a more progressive tax regime.

Observation 3:

The current yield curve for Country Y suggests that the business cycle is in the slowdown phase, with bond yields starting to reflect contractionary conditions.

Wakuluk

most likely

seeks to mitigate which of the following biases in developing capital market forecasts?

Availability

Time period

Survivorship

Wakuluk’s approach to economic forecasting:

is flexible and limited in complexity.

can give a false sense of precision and provide false signals.

imposes no consistency of analysis across items or at different points in time.

Wakuluk is

most likely

to make significant adjustments to her estimate of the future growth trend for which of the following countries?

Country Y only

Country Z only

Countries Y and Z

Based on

Exhibit 1

and Wakuluk’s assumptions about short-term rates and expected inflation, short-term rates in Country X are

most likely

to be:

low and bottoming.

approaching a peak.

above average and rising.

Based on

Exhibit 1

, what capital market effect is Country Z

most likely

to experience in the short-term?

Cyclical assets attract investors.

Monetary policy becomes restrictive.

The yield curve steepens substantially.

Based on Observation 1, fiscal and monetary policies in Country Y will

most likely

lead to:

low nominal rates.

high nominal rates.

either high or low nominal rates.

Based on Observation 2, what impact will the policy changes have on the trend rate of growth for Country Y?

Negative

Neutral

Positive

Based on Observation 3, Wakuluk

most likely

expects Country Y’s yield curve in the near term to:

invert.

flatten.

steepen.

The following information relates to Questions 9–10

Jennifer Wuyan is an investment strategist responsible for developing long-term capital market expectations for an investment firm that invests in domestic equities. She presents a report to the firm’s investment committee describing the statistical model used to formulate capital market expectations, which is based on a dividend discount method. In the report, she notes that in developing the model, she researched the historical data seeking to identify the relevant variables and determined the best source of data for the model. She also notes her interpretation of the current economic and market environment.

Explain

what additional step(s) Wuyan should have taken in the process of setting capital market expectations.

Wuyan reports that after repeatedly searching the most recent 10 years of data, she eventually identified variables that had a statistically significant relationship with equity returns. Wuyan used these variables to forecast equity returns. She documented, in a separate section of the report, a high correlation between nominal GDP and equity returns. Based on this noted high correlation, Wuyan concludes that nominal GDP predicts equity returns. Based on her statistical results, Wuyan expects equities to underperform over the next 12 months and recommends that the firm underweight equities.

Commenting on the report, John Tommanson, an investment adviser for the firm, suggests extending the starting point of the historical data back another 20 years to obtain more robust statistical results. Doing so would enable the analysis to include different economic and central bank policy environments. Tommanson is reluctant to underweight equities for his clients, citing the strong performance of equities over the last quarter, and believes the most recent quarterly data should be weighted more heavily in setting capital market expectations.

Discuss

how

each

of the following forecasting challenges evident in Wuyan’s report and in Tommanson’s comments affects the setting of capital market expectations:

Status quo bias

Data-mining bias

Risk of regime change

Misinterpretation of correlation

Discuss how each of the following forecasting challenges evident in Wuyan’s report and in Tommanson’s comments affects the setting of capital market expectations:

Status quo bias

Data-mining bias

Risk of regime change

Misinterpretation of correlation

The following information relates to Questions 11–13

Jan Cambo is chief market strategist at a US asset management firm. While preparing a report for the upcoming investment committee meeting, Cambo updates her long-term forecast for US equity returns. As an input into her forecasting model, she uses the following long-term annualized forecasts from the firm’s chief economist:

Labor input will grow 0.5%.

Labor productivity will grow 1.3%.

Inflation will be 2.2%.

Dividend yield will be 2.8%.

Based on these forecasts, Cambo predicts a long-term 9.0% annual equity return in the US market. Her forecast assumes no change in the share of profits in the economy, and she expects some contribution to equity returns from a change in the price-to-earnings ratio (P/E).

Calculate

the implied contribution to Cambo’s US equity return forecast from the expected change in the P/E.

At the investment committee meeting, the firm’s chief economist predicts that the economy will enter the late expansion phase of the business cycle in the next 12 months.

Discuss

, based on the chief economist’s prediction, the implications for the following:

Bond yields

Equity returns

Short-term interest rates

Discuss, based on the chief economist’s prediction, the implications for the following:

Bond yields

Equity returns

Short-term interest rates

Cambo compares her business cycle forecasting approach to the approach used by the chief economist. Cambo bases her equity market forecast on a time-series model using a composite index of leading indicators as the key input, whereas the chief economist uses a detailed econometric model to generate his economic forecasts.

Discuss

strengths and weaknesses of the economic forecasting approaches used by Cambo and the chief economist.

Discuss strengths and weaknesses of the economic forecasting approaches used by Cambo and the chief economist.

Cambo’s Forecasting Approach

Chief Economist’s Forecasting Approach

Strengths

Weaknesses

The following information relates to Questions 14–16

Robert Hadpret is the chief economist at Agree Partners, an asset management firm located in the developed country of Eastland. He has prepared an economic report on Eastland for the firm’s asset allocation committee. Hadpret notes that the composite index of leading economic indicators has declined for three consecutive months and that the yield curve has inverted. Private sector borrowing is also projected to decline. Based on these recent events, Hadpret predicts an economic contraction and forecasts lower inflation and possibly deflation over the next 12 months.

Helen Smitherman, a portfolio manager at Agree, considers Hadpret’s economic forecast when determining the tactical allocation for the firm’s Balanced Fund (the fund). Smitherman notes that the fund has considerable exposure to real estate, shares of asset-intensive and commodity-producing firms, and high-quality debt. The fund’s cash holdings are at cyclical lows.

Discuss

the implications of Hadpret’s inflation forecast on the expected returns of the fund’s holdings of:

cash.

bonds.

equities.

real estate.

Discuss the implications of Hadpret’s inflation forecast on the expected returns of the fund’s holdings of:

Cash

Bonds

Equities

Real Estate

In response to the projected cyclical decline in the Eastland economy and in private sector borrowing over the next year, Hadpret expects a change in the monetary and fiscal policy mix. He forecasts that the Eastland central bank will ease monetary policy. On the fiscal side, Hadpret expects the Eastland government to enact a substantial tax cut. As a result, Hadpret forecasts large government deficits that will be financed by the issuance of long-term government securities.

Discuss

the relationship between the shape of the yield curve and the monetary and fiscal policy mix projected by Hadpret.

Currently, Eastland’s currency is fixed relative to the currency of the country of Northland, and Eastland maintains policies that allow unrestricted capital flows. Hadpret examines the relationship between interest rates and exchange rates. He considers three possible scenarios for the Eastland economy:

Scenario 1.

Shift in policy restricting capital flows

Scenario 2.

Shift in policy allowing the currency to float

Scenario 3.

Shift in investor belief toward a lack of full credibility that the exchange rate will be fixed forever

Discuss

how interest rate and exchange rate linkages between Eastland and Northland might change under

each

scenario.Note: Consider

each

scenario independently.

Discuss how interest rate and exchange rate linkages between Eastland and Northland might change under each scenario. (Note: Consider each scenario independently.)

Scenario 1

Scenario 2

Scenario 3

CHAPTER 4

CAPITAL MARKET EXPECTATIONS, PART 2: FORECASTING ASSET CLASS RETURNS

LEARNING OUTCOMES

The candidate should be able to:

discuss approaches to setting expectations for fixed-income returns;

discuss risks faced by investors in emerging market fixed-income securities and the country risk analysis techniques used to evaluate emerging market economies;

discuss approaches to setting expectations for equity investment market returns;

discuss risks faced by investors in emerging market equity securities;

explain how economic and competitive factors can affect expectations for real estate investment markets and sector returns;

discuss major approaches to forecasting exchange rates;

discuss methods of forecasting volatility;

recommend and justify changes in the component weights of a global investment portfolio based on trends and expected changes in macroeconomic factors.

SUMMARY

The following are the main points covered in the chapter.

The choice among forecasting techniques is effectively a choice of the information on which forecasts will be conditioned and how that information will be incorporated into the forecasts.

The formal forecasting tools most commonly used in forecasting capital market returns fall into three broad categories: statistical methods, discounted cash flow models, and risk premium models.

Sample statistics, especially the sample mean, are subject to substantial estimation error.

Shrinkage estimation combines two estimates (or sets of estimates) into a more precise estimate.

Time-series estimators, which explicitly incorporate dynamics, may summarize historical data well without providing insight into the underlying drivers of forecasts.

Discounted cash flow models are used to estimate the required return implied by an asset’s current price.

The risk premium approach expresses expected return as the sum of the risk-free rate of interest and one or more risk premiums.

There are three methods for modeling risk premiums: equilibrium models, such as the CAPM; factor models; and building blocks.

The DCF method is the only one that is precise enough to use in support of trades involving individual fixed-income securities.

There are three main methods for developing expected returns for fixed-income asset classes: DCF, building blocks, and inclusion in an equilibrium model.

As a forecast of bond return, YTM, the most commonly quoted metric, can be improved by incorporating the impact of yield changes on reinvestment of cash flows and valuation at the investment horizon.

The building blocks for fixed-income expected returns are the short-term default-free rate, the term premium, the credit premium, and the liquidity premium.

Term premiums are roughly proportional to duration, whereas credit premiums tend to be larger at the short end of the curve.

Both term premiums and credit premiums are positively related to the slope of the yield curve.

Credit spreads reflect both the credit premium (i.e., additional expected return) and expected losses due to default.

A baseline estimate of the liquidity premium can be based on the yield spread between the highest-quality issuer in a market (usually the sovereign) and the next highest-quality large issuer (often a government agency).

Emerging market debt exposes investors to heightened risk with respect to both ability to pay and willingness to pay, which can be associated with the economy and political/legal weaknesses, respectively.

The Grinold–Kroner model decomposes the expected return on equities into three components: (1) expected cash flow return, composed of the dividend yield minus the rate of change in shares outstanding; (2) expected return due to nominal earnings growth; and (3) expected repricing return, reflecting the rate of change in the P/E.

Forecasting the equity premium directly is just as difficult as projecting the absolute level of equity returns, so the building block approach provides little, if any, specific insight with which to improve equity return forecasts.

The Singer–Terhaar version of the international capital asset pricing model combines a global CAPM equilibrium that assumes full market integration with expected returns for each asset class based on complete segmentation.

Emerging market equities expose investors to the same underlying risks as emerging market debt does: more fragile economies, less stable political and policy frameworks, and weaker legal protections.

Emerging market investors need to pay particular attention to the ways in which the value of their ownership claims might be expropriated. Among the areas of concern are standards of corporate governance, accounting and disclosure standards, property rights laws, and checks and balances on governmental actions.

Historical return data for real estate is subject to substantial smoothing, which biases standard volatility estimates downward and distorts correlations with other asset classes. Meaningful analysis of real estate as an asset class requires explicit handling of this data issue.

Real estate is subject to boom–bust cycles that both drive and are driven by the business cycle.

The cap rate, defined as net operating income in the current period divided by the property value, is the standard valuation metric for commercial real estate.

A model similar to the Grinold–Kroner model can be applied to estimate the expected return on real estate:

There is a clear pattern of higher cap rates for riskier property types, lower-quality properties, and less attractive locations.

Real estate expected returns contain all the standard building block risk premiums:

Term premium: As a very long-lived asset with relatively stable cash flows, income-producing real estate has a high duration.

Credit premium: A fixed-term lease is like a corporate bond issued by the leaseholder and secured by the property.

Equity premium: Owners bear the risk of property value fluctuations, as well as risk associated with rent growth, lease renewal, and vacancies.

Liquidity premium: Real estate trades infrequently and is costly to transact.

Currency exchange rates are especially difficult to forecast because they are tied to governments, financial systems, legal systems, and geographies. Forecasting exchange rates requires identification and assessment of the forces that are likely to exert the most influence.

Provided they can be financed, trade flows do not usually exert a significant impact on exchange rates. International capital flows are typically larger and more volatile than trade-financing flows.

PPP is a poor predictor of exchange rate movements over short to intermediate horizons but is a better guide to currency movements over progressively longer multi-year horizons.

The extent to which the current account balance influences the exchange rate depends primarily on whether it is likely to be persistent and, if so, whether it can be sustained.

Capital seeks the highest risk-adjusted expected return. In a world of perfect capital mobility, in the long run, the exchange rate will be driven to the point at which the expected percentage change equals the “excess” risk-adjusted expected return on the portfolio of assets denominated in the domestic currency over that of the portfolio of assets denominated in the foreign currency. However, in the short run, there can be an exchange rate overshoot in the opposite direction as hot money chases higher returns.

Carry trades are profitable on average, which is contrary to the predictions of uncovered interest rate parity.

Each country/currency has a unique portfolio of assets that makes up part of the global “market portfolio.” Exchange rates provide an across-the-board mechanism for adjusting the relative sizes of these portfolios to match investors’ desire to hold them.

The portfolio balance perspective implies that exchange rates adjust in response to changes in the relative sizes and compositions of the aggregate portfolios denominated in each currency.

The sample variance–covariance matrix is an unbiased estimate of the true VCV structure; that is, it will be correct on average.

There are two main problems with using the sample VCV matrix as an estimate/forecast of the true VCV matrix: It cannot be used for large numbers of asset classes, and it is subject to substantial sampling error.

Linear factor models impose structure on the VCV matrix that allows them to handle very large numbers of asset classes. The drawback is that the VCV matrix is biased and inconsistent unless the assumed structure is true.

Shrinkage estimation of the VCV matrix is a weighted average of the sample VCV matrix and a target VCV matrix that reflects assumed “prior” knowledge of the true VCV structure.

Failure to adjust for the impact of smoothing in observed return data for real estate and other private assets will almost certainly lead to distorted portfolio analysis and hence poor asset allocation decisions.

Financial asset returns exhibit volatility clustering, evidenced by periods of high and low volatilities. ARCH models were developed to address these time-varying volatilities.

One of the simplest and most used ARCH models represents today’s variance as a linear combination of yesterday’s variance and a new “shock” to volatility. With appropriate parameter values, the model exhibits the volatility clustering characteristic of financial asset returns.

PRACTICE PROBLEMS

An investor is considering adding three new securities to her internationally focused, fixed-income portfolio. She considers the following non-callable securities:

1-year government bond

10-year government bond

10-year BBB rated corporate bond

She plans to invest equally in all three securities being analyzed or will invest in none of them at this time. She will only make the added investment provided that the expected spread/premium of the equally weighted investment is at least 1.5 percent (150bp) over the 1-year government bond. She has gathered the following information:

Risk-free interest rate (1-year, incorporating 2.6% inflation expectation)

3.8%

Term premium (10-year vs. 1-year government bond)

1%

10-year BBB credit premium (over 10-year government bond)

75bp

Estimated liquidity premium on 10-year corporate bonds

55bp

Using only the information given, address the following problems using the risk premium approach:

Calculate the expected return that an equal-weighted investment in the three securities could provide.

Calculate the expected total risk premium of the three securities and determine the investor’s probable course of action.

Jo Akumba’s portfolio is invested in a range of developed markets fixed-income securities. She asks her adviser about the possibility of diversifying her investments to include emerging and frontier markets government and corporate fixed-income securities. Her adviser makes the following comment regarding risk:

“All emerging and frontier fixed-income securities pose economic, political, and legal risk. Economic risks arise from the fact that emerging market countries have poor fiscal discipline, rely on foreign borrowing, have less diverse tax base, and significant dependence on specific industries. They are susceptible to capital flight. Their ability to pay is limited. In addition, weak property rights, weak enforcement of contract laws, and political instability pose hazards for emerging markets debt investors.”Discuss the statement made.

An Australian investor currently holds an A$240 million equity portfolio. He is considering rebalancing the portfolio based on an assessment of the risk and return prospects facing the Australian economy. Information relating to the Australian investment markets and the economy has been collected in the following table:

10-Year Historical

Current

Capital Market Expectations

Average government bond yield: 2.8%

10-year government bond yield: 2.3%

Average annual equity return: 4.6%

Year-over-year equity return: −9.4%

Average annual inflation rate: 2.3%

Year-over-year inflation rate: 2.1%

Expected annual inflation: 2.3%

Equity market P/E (beginning of period): 15×

Current equity market P/E: 14.5×

Expected equity market P/E: 14.0×

Average annual dividend income return: 2.6%

Expected annual income return: 2.4%

Average annual real earnings growth: 6.0%

Expected annual real earnings growth: 5.0%

Using the information in the table, address the following problems:

Calculate the historical Australian equity risk premium using the “equity-vs-bonds” premium method.

Calculate the expected annual equity return using the Grinold–Kroner model (assume no change in the number of shares outstanding).

Using your answer to Part B, calculate the expected annual equity risk premium.

An analyst is reviewing various asset alternatives and is presented with the following information relating to the broad equity market of Switzerland and various industries within the Swiss market that are of particular investment interest.

Expected risk premium for overall global investable market (GIM) portfolio

3.5%

Expected standard deviation for the GIM portfolio

8.5%

Expected standard deviation for Swiss Healthcare Industry equity investments

12.0%

Expected standard deviation for Swiss Watch Industry equity investments

6.0%

Expected standard deviation for Swiss Consumer Products Industry equity investments

7.5%

Assume that the Swiss market is perfectly integrated with the world markets.

Swiss Healthcare has a correlation of 0.7 with the GIM portfolio.

Swiss Watch has a correlation of 0.8 with the GIM portfolio.

Swiss Consumer Products has a correlation of 0.8 with the GIM portfolio.

Basing your answers only upon the data presented in the table above and using the international capital asset pricing model—in particular, the Singer–Terhaar approach—estimate the expected risk premium for the following:

Swiss Healthcare Industry

Swiss Watch Industry

Swiss Consumer Products Industry

Judge which industry is most attractive from a valuation perspective.

Identify risks faced by investors in emerging market equities over and above those that are faced by fixed-income investors in such markets.

Describe the main issues that arise when conducting historical analysis of real estate returns.

An analyst at a real estate investment management firm seeks to establish expectations for rate of return for properties in the industrial sector over the next year. She has obtained the following information:

Current industrial sector capitalization rate (“cap” rate)

5.7%

Expected cap rate at the end of the period

5.5%

NOI growth rate (real)

1%

Inflation expectation

1.5%

Estimate the expected return from the industrial sector properties based on the data provided.

A client has asked his adviser to explain the key considerations in forecasting exchange rates. The adviser’s firm uses two broad complementary approaches when setting expectations for exchange rate movements, namely focus on trade in goods and services and, secondly, focus on capital flows. Identify the main considerations that the adviser should explain to the client under the two approaches.

Looking independently at each of the economic observations below, indicate the country where an analyst would expect to see a strengthening currency for each observation.

Country X

Country Y

Expected inflation over next year

2.0%

3.0%

Short-term (1-month) government rate

Decrease

Increase

Expected (forward-looking) GDP growth over next year

2.0%

3.3%

New national laws have been passed that enable foreign direct investment in real estate/financial companies

Yes

No

Current account surplus (deficit)

8%

−1%

Fap is a small country whose currency is the Fip. Three years ago, the exchange rate was considered to be reflecting purchasing power parity (PPP). Since then, the country’s inflation has exceeded inflation in the other countries by about 5% per annum. The Fip exchange rate, however, remained broadly unchanged.

What would you have expected the Fip exchange rate to show if PPP prevailed?

Are Fips over-or undervalued, according to PPP?

The following information relates to Questions 11–18

Richard Martin is chief investment officer for the Trunch Foundation (the foundation), which has a large, globally diversified investment portfolio. Martin meets with the foundation’s fixed-income and real estate portfolio managers to review expected return forecasts and potential investments, as well as to consider short-term modifications to asset weights within the total fund strategic asset allocation.

Martin asks the real estate portfolio manager to discuss the performance characteristics of real estate. The real estate portfolio manager makes the following statements:

Statement 1: Adding traded REIT securities to an equity portfolio should substantially improve the portfolio’s diversification over the next year.

Statement 2: Traded REIT securities are more highly correlated with direct real estate and less highly correlated with equities over multi-year horizons.

Martin looks over the long-run valuation metrics the manager is using for commercial real estate, shown in Exhibit 1.

EXHIBIT 1 Commercial Real Estate Valuation Metrics

Cap Rate

GDP Growth Rate

4.70%

4.60%

The real estate team uses an in-house model for private real estate to estimate the true volatility of returns over time. The model assumes that the current observed return equals the weighted average of the current true return and the previous observed return. Because the true return is not observable, the model assumes a relationship between true returns and observable REIT index returns; therefore, it uses REIT index returns as proxies for both the unobservable current true return and the previous observed return.

Martin asks the fixed-income portfolio manager to review the foundation’s bond portfolios. The existing aggregate bond portfolio is broadly diversified in domestic and international developed markets. The first segment of the portfolio to be reviewed is the domestic sovereign portfolio. The bond manager notes that there is a market consensus that the domestic yield curve will likely experience a single 20 bp increase in the near term as a result of monetary tightening and then remain relatively flat and stable for the next three years. Martin then reviews duration and yield measures for the short-term domestic sovereign bond portfolio in Exhibit 2.

EXHIBIT 2 Short-Term Domestic Sovereign Bond Portfolio

Macaulay Duration

Modified Duration

Yield to Maturity

3.00

2.94

2.00%

The discussion turns to the international developed fixed-income market. The foundation invested in bonds issued by Country XYZ, a foreign developed country. XYZ’s sovereign yield curve is currently upward sloping, and the yield spread between 2-year and 10-year XYZ bonds is 100 bps.

The fixed-income portfolio manager tells Martin that he is interested in a domestic market corporate bond issued by Zeus Manufacturing Corporation (ZMC). ZMC has just been downgraded two steps by a major credit rating agency. In addition to expected monetary actions that will raise short-term rates, the yield spread between three-year sovereign bonds and the next highest-quality government agency bond widened by 10 bps.

Although the foundation’s fixed-income portfolios have focused primarily on developed markets, the portfolio manager presents data in Exhibit 3 on two emerging markets for Martin to consider. Both economies increased exports of their mineral resources over the last decade.

EXHIBIT 3 Emerging Market Data

Factor

Emerging Republic A

Emerging Republic B

Fiscal deficit/GDP

6.50%

8.20%

Debt/GDP

90.10%

104.20%

Current account deficit

5.20% of GDP

7.10% of GDP

Foreign exchange reserves

90.30% of short-term debt

70.10% of short-term debt

The fixed-income portfolio manager also presents information on a new investment opportunity in an international developed market. The team is considering the bonds of Xdelp, a large energy exploration and production company. Both the domestic and international markets are experiencing synchronized growth in GDP midway between the trough and the peak of the business cycle. The foreign country’s government has displayed a disciplined approach to maintaining stable monetary and fiscal policies and has experienced a rising current account surplus and an appreciating currency. It is expected that with the improvements in free cash flow and earnings, the credit rating of the Xdelp bonds will be upgraded. Martin refers to the foundation’s asset allocation policy in Exhibit 4 before making any changes to either the fixed-income or real estate portfolios.

EXHIBIT 4 Trunch Foundation Strategic Asset Allocation—Select Data

Asset Class

Minimum Weight

Maximum Weight

Actual Weight

Fixed income—Domestic

40.00%

80.00%

43.22%

Fixed income—International

5.00%

10.00%

6.17%

Fixed income—Emerging markets

0.00%

2.00%

0.00%

Alternatives—Real estate

2.00%

6.00%

3.34%

Which of the real estate portfolio manager’s statements is correct?

Only Statement 1

Only Statement 2

Both Statement 1 and Statement 2

Based only on

Exhibit 1

, the long-run expected return for commercial real estate:

is approximately double the cap rate.

incorporates a cap rate greater than the discount rate.

needs to include the cap rate’s anticipated rate of change.

Based on the private real estate model developed to estimate return volatility, the true variance is

most likely

:

lower than the variance of the observed data.

approximately equal to the variance of the observed data.

greater than the variance of the observed data.

Based on

Exhibit 2

and the anticipated effects of the monetary policy change, the expected annual return over a three-year investment horizon will

most likely

be:

lower than 2.00%.

approximately equal to 2.00%.

greater than 2.00%.

Based on the building block approach to fixed-income returns, the dominant source of the yield spread for Country XYZ is

most likely

the:

term premium.

credit premium.

liquidity premium.

Using the building block approach, the required rate of return for the ZMC bond will

most likely

:

increase based on the change in the credit premium.

decrease based on the change in the default-free rate.

decrease based on the change in the liquidity premium.

Based only on