Global Macro Trading E-Book

Greg Gliner

• Herausgeber: John Wiley & Sons
• Kategorie: Fachliteratur
• Serie: Bloomberg Professional
• Sprache: Englisch

Seitenzahl: 458

Veröffentlichungsjahr: 2014

Beschreibung

Brings global macro trading down to earth for individual and professional traders, investors and asset managers, as well being a useful reference handbook Global Macro Trading is an indispensable guide for traders and investors who want to trade Global Macro - it provides Trading Strategies and overviews of the four asset classes in Global Macro which include equities, currencies, fixed income and commodities. Greg Gliner, who has worked for some of the largest global macro hedge funds, shares ways in which an array of global macro participants seek to capitalize on this strategy, while also serving as a useful reference tool. Whether you are a retail investor, manage your own portfolio, or a finance professional, this book equips you with the knowledge and skills you need to capitalize in global macro. * Provides a comprehensive overview of global macro trading, which consists of portfolio construction, risk management, biases and essentials to query building * Equips the reader with introductions and tools for each of the four asset classes; equities, currencies, fixed income and commodities * Arms you with a range of powerful global-macro trading and investing strategies, that include introductions to discretionary and systematic macro * Introduces the role of central banking, importance of global macroeconomic data releases and demographics, as they relate to global macro trading

Leseprobe

Contents

Preface

Part One: An Overview of Global Macro

Chapter 1: Surveying the Global Macro Landscape

Types of Global Macro Strategies

Return Profile and Allocations

Hedge Funds and Global Macro

Summary

Chapter 2: Trading Process, Sizing Trades, and Monitoring Performance

Maintaining a Stringent Process

Objectivity and Bias

Taking Losses

Position Sizing

Unit Size

Volatility Adjusting Position Size

Risk/Reward

Correlation

Gap Risk

Position Sizing Sheet

Thematic Trade

Sharpe Ratio

Sortino Ratio

Drawdowns

Value at Risk (VaR)

Risk Utilization

Stress-Testing

Monitoring Performance

Trend Analysis

Bloomberg Shortcuts

Summary

Chapter 3: Back-Tests, Queries, and Analogs

Simple Back-Tests and Queries

An Example of Building a Query

Historical Correlations and Analogs

Summary

Chapter 4: The Building Blocks of Global Macro Trading: The Importance of Equities, Fixed Income, Foreign Exchange, and Commodities in Global Macro

The Four Product Groups

Assessing the Relationships between Assets

Summary

Chapter 5: Technical Analysis

Strengths and Weaknesses of Technical Analysis

Types of Charts

Volume and Open Interest

CFTC Positioning

Trend

Moving Averages

Bollinger Bands

Reversal Patterns

Head and Shoulders

Trend Lines

Triple Tops and Bottoms

Continuation Patterns

Triangles

Oscillators

Elliott Wave Theory

Parabolics

Seasonals

Cycles

Crowd Psychology and Contrarian Views

Chartered Market Technician (CMT)

Bloomberg Shortcuts

Summary

Chapter 6: Systematic Trading

A Brief Definition of Systematic Trading

Framework for Constructing a Systematic Model

Assets or Product Groups

Strategies

Factors

Risk Factors

Risk Premia

Risk Parity

Summary

Part Two: Global Macro Trading Foundation

Chapter 7: Foreign Exchange in Global Macro

The Role of the U.S. Dollar

Trading Currencies

Currency Regimes

Valuation Techniques for Foreign Exchange

Bloomberg Shortcuts

Summary

Chapter 8: Equities

Equity Indices Overview

Equity Derivatives

Valuation Techniques for Equities

Bloomberg Shortcuts

Summary

Chapter 9: Fixed Income

Funding/Money Markets

London Interbank Offered Rate (LIBOR)

Interest Rate Swaps

Federal (Fed) Funds

Overnight Indexed Swaps (OIS)

Forward Rate Agreements (FRAs)

U.S. Fixed Income Futures

Sovereign Credit

Sovereign Curve

Curve Inversion

Credit Default Swaps (CDS)

Exchange Traded Funds (ETFs)

Bloomberg Shortcuts

Summary

Chapter 10: Commodities

Supply Drivers

Demand Drivers

Ending Stock

Contango and Backwardation

CRB Index

Return and Volatility

Energy

Natural Gas

Precious Metals

Industrial Metals

Agriculture

Bloomberg Shortcuts

Summary

Chapter 11: The Role of Central Banks in Global Macro

Monetary Policy Goals

Tools Used by Central Banks

The Impossible Trinity

Monetary Base

Money Supply

Reserves

Zero Lower Bound and the Liquidity Trap

Quantitative Easing

interpreting central bank communication

Central Banks

Bloomberg Shortcuts

Summary

Appendix: Fed Programs during the Financial Crisis

Chapter 12: Economic Data Releases and Demographics

Measuring Growth

Inflation

Employment and Population

Balance of Payments

Government Indicators

Consumption Indicators

Industry and Services Indicators

Demographics

Bloomberg Shortcuts

Summary

References

About the Author

Index

End User License Agreement

List of Illustrations

FIGURE 1.1 Global Macro versus S&P 500 from January 1995 to September 2013

FIGURE 1.2 (a) Performance of Global Macro during the Top Five Losing Quarters in SPX since January 1995 and (b) Performance of Global Macro during the Top Five Best Quarters in SPX since January 1995

FIGURE 1.3 Changes in Pension Funds’ Allocations to Different Hedge Fund Strategies from 2009 to 2012

FIGURE 2.1 Sample Normal Distribution

FIGURE 2.2 Euro Stoxx 50 Chart March 15, 2013 − March 18, 2013

FIGURE 2.3 10-Year Japanese Government Bond Yields

FIGURE 2.4 Nonlinear Risk Utilization

FIGURE 2.5 Baseball Hot Spots in the Strike Zone

FIGURE 3.1 British Pound Intraday Performance on July 5, 2012

FIGURE 3.2 FTSE Intraday Performance on July 5, 2012

FIGURE 3.3 Dow Jones Industrial Average Price Chart from July 2011 to December 2011

FIGURE 3.4 Analog Period Time Series

FIGURE 3.5 U.S. Dollar Index Historical Correlations to 180-Day Analog Period

FIGURE 3.6 Analog Period versus February 12, 2007 through October 20, 2008

FIGURE 4.1 Foreign Exchange Market Turnover by Currency Pairs

FIGURE 4.2 Canadian Dollar versus WTI Crude Oil

FIGURE 4.3 Japan Debt to GDP Ratio and 10-Year Japanese Government Bonds

FIGURE 4.4 Copper versus the Chilean Peso

FIGURE 4.5 Four Individual Assets from the Four Market Categories during the 2008 Financial Crisis

FIGURE 5.1 Line Chart of the S&P 500

FIGURE 5.2 Sample of a Single Bar on a Bar Chart

FIGURE 5.3 Bar Chart of the S&P 500

FIGURE 5.4 Sample Candlesticks

FIGURE 5.5 Candlestick Chart of the S&P 500

FIGURE 5.6 Major Japanese Candlestick Signals

FIGURE 5.7 Point and Figure Chart—First Steps

FIGURE 5.8 Point and Figure Chart

FIGURE 5.9 Arithmetic Scale and Logarithmic Scale

FIGURE 5.10 Dow Jones Industrial Average: (a) Regular Chart and (b) Lognormal Chart

FIGURE 5.11 Bar Chart and Volume of the S&P 500

FIGURE 5.12 Commitments of Traders Report

FIGURE 5.13 Gold CFTC Net Positioning of Noncommercial and Nonreportable Speculators

FIGURE 5.14 Nikkei Historical Price Chart with Trends

FIGURE 5.15 Bollinger Band Chart of the S&P 500

FIGURE 5.16 Sample Head and Shoulders Pattern

FIGURE 5.17 Sample Triple Bottom Pattern

FIGURE 5.18 Types of Triangles

FIGURE 5.19 Chart of Nasdaq in Broadening Top Formation

FIGURE 5.20 S&P 500 Bar Chart with MACD

FIGURE 5.21 S&P 500 Bar Chart with RSI

FIGURE 5.22 S&P 500 Bar Chart with Stochastics

FIGURE 5.23 Elliott Wave Basic Pattern

FIGURE 5.24 Zigzags in Elliott Wave

FIGURE 5.25 Flats in Elliott Wave

FIGURE 5.26 Corrective Wave (Horizontal) Triangles

FIGURE 5.27 Bull Market Truncation (Failure)

FIGURE 5.28 S&P 500 Chart with Fibonacci Retracements

FIGURE 5.29 Historical Price Chart of Silver, 1977–1980

FIGURE 5.30 Historical Price Chart of Gold, 1920–2012

FIGURE 5.31 Corn Seasonal Data, 1970–2010

FIGURE 5.32 Charts of Respective Markets when the Market Leader Had Their IPO

FIGURE 5.33 Chart of the S&P 500 during the October 1987 Crash

FIGURE 6.1 Construct and Framework of a Systematic Process

FIGURE 6.2 Efficient Frontier

FIGURE 6.3 Historical Total Return of Indexed Risk Parity—60% S&P 500/40% Barclays U.S. Aggregate Bond Index

FIGURE 7.1 Foreign Exchange Market Turnover by Currency as a Percent of Volume

FIGURE 7.2 Central Bank Holdings of Currencies

FIGURE 7.3 Currency Turnover by Market

FIGURE 7.4 Chinese Renminbi versus Chinese Renminbi 12-Month Nondeliverable Forward

FIGURE 7.5 Basket of Currencies in SDRs

FIGURE 7.6 Hong Kong Dollar Exchange Rate, 1935–2005

FIGURE 7.7 U.S. Dollar/Brazilian Real Price Chart

FIGURE 7.8 Brazilian Bovespa and Brazilian Real

FIGURE 7.9 Mexican Peso versus Mexico Five-Year CDS

FIGURE 7.10 Australian Dollar/Mexican Peso Cross versus Australia/Mexico Five-Year CDS Spread

FIGURE 7.11 British Pound versus Three-Month British Pound Risk Reversals

FIGURE 7.12 Canadian Dollar versus WTI Crude

FIGURE 7.13 2012 Country Debt to GDP

FIGURE 7.14 Big Mac Index

FIGURE 7.15 Australian Dollar/U.S. Dollar versus the RBA Rate/Fed Funds Effective Spread

FIGURE 7.16 Euro/U.S. Dollar versus Front Eurodollar/EURIBOR Spread

FIGURE 8.1 A Top-Down Approach

FIGURE 8.2 Absolute Price Chart of WTI Relative to Individual Energy Stocks

FIGURE 8.3 Equity Rotation in Sectors during Economic Cycles

FIGURE 8.4 VIX Annualized Average Daily Closing and Correlation to the S&P 500

FIGURE 8.5 Historical Chart of the VIX Index (Spot)

FIGURE 8.6 Payoff Structure of a Long Variance Swap Position

FIGURE 8.7 S&P 500 Historical Price/Book Value

FIGURE 8.8 S&P 500 Historical Dividend Yield

FIGURE 8.9 S&P 500 Historical Price/Earnings Ratio

FIGURE 8.10 S&P 500 Historical Free Cash Flow Yield

FIGURE 8.11 U.S. Historical Stock Market Capitalization as a Percentage of GDP

FIGURE 8.12 CRB Index Historical Year-over-Year Change

FIGURE 8.13 Five-Year CDX High Yield Index

FIGURE 8.14 Historical Chart of ISM Manufacturing PMI

FIGURE 8.15 Historical Price Chart of the Baltic Dry Index

FIGURE 8.16 Historical Chart of ARMS Index with 100-Day Smoothing

FIGURE 8.17 Conference Board Consumer Confidence Index

FIGURE 8.18 Australian Dollar Three-Month At-the-Money Volatility versus the VIX Index

FIGURE 9.1 Basic Fixed Income Universe: Overview

FIGURE 9.2 Inflation-Indexed Yield Analysis Bloomberg Screenshot

FIGURE 9.3 Historical Chart of LIBOR-OIS Spread

FIGURE 9.4 Market Pricing Factors on U.S. Fixed Income Yield Curve

FIGURE 9.5 Bloomberg Screenshot of U.S. Fixed Income Strip

FIGURE 9.6 Historical Chart of U.S. 2s/10s Flattener

FIGURE 9.7 Bear and Bull Flatteners

FIGURE 9.8 Portuguese Government Bonds Screenshot

FIGURE 9.9 Cash Flow during Life of CDS and Physical Settlement during Default

FIGURE 9.10 Recovery Rates on Defaulted Sovereign Bond Issuers

FIGURE 10.1 Supply and Demand with Ending Stock

FIGURE 10.2 Corn Futures Strip

FIGURE 10.3 CRB Index Historical Price Chart

FIGURE 10.4 Historical Chart of Crude Oil Prices

FIGURE 10.5 Global Crude Grades

FIGURE 10.6 Historical Price Chart of WTI Crude Front Contract

FIGURE 10.7 Historical Price Chart of Brent Crude Front Contract

FIGURE 10.8 Historical Price Chart of WTI–Brent Spread Front Contract

FIGURE 10.9 PADD Map

FIGURE 10.10 Map of Strait of Hormuz

FIGURE 10.11 Map of Strait of Malacca

FIGURE 10.12 Map of Mandab Strait

FIGURE 10.13 Druzhba Pipeline

FIGURE 10.14 Keystone and Keystone XL Proposal

FIGURE 10.15 WTI Cushing/New York Harbor RBOB and Heating Oil Crack Spread Historical Price Chart

FIGURE 10.16 Sample of 3:2:1 Crack Spread

FIGURE 10.17 Natural Gas Drilling

FIGURE 10.18 Historical Price Chart of Natural Gas Front Contract

FIGURE 10.19 Historical Price Chart of Gold

FIGURE 10.20 Historical Price Chart of Silver

FIGURE 10.21 Historical Price Chart of Platinum

FIGURE 10.22 Platinum/Gold Ratio

FIGURE 10.23 Historical Price Chart of Copper Front Contract (NYMEX)

FIGURE 10.24 Historical Price Chart of Aluminum (LME Forward)

FIGURE 10.25 Corn Planted Acres Map in United States

FIGURE 10.26 Corn Front Contract Historical Price Chart

FIGURE 10.27 U.S. Seasonal Drought Outlook

FIGURE 10.28 Corn Used for Ethanol Production, 1986–2011 (million bushels)

FIGURE 10.29 2011 Top Global Ethanol Producers by Country (in millions of gallons)

FIGURE 10.30 Corn Crop Calendar

FIGURE 10.31 Wheat Front Contract Historical Price Chart

FIGURE 10.32 Wheat Crop Calendar

FIGURE 10.33 Soybeans Front Contract Historical Price Chart

FIGURE 10.34 Soybeans Crop Calendar

FIGURE 10.35 Cotton Front Contract Historical Price Chart

FIGURE 10.36 Cotton Crop Calendar

FIGURE 10.37 Coffee Front Contract Historical Price Chart

FIGURE 10.38 Coffee Crop Calendar

FIGURE 10.39 Coffee Crop: High- and Low-Yielding Years

FIGURE 11.1 Example of Balance Sheet Transactions between Bank and Fed

FIGURE 11.2 Impossible Trinity

FIGURE 11.3 2011 Top 10 Countries by Total Reserves ($ in billions)

FIGURE 11.4 The Twelve Federal Reserve Districts

FIGURE 11.5 EMU: Three Steps

FIGURE 11.6 Chart of Italian Sovereign Curve before LTRO Announcement after LTRO I and II

FIGURE 11.7 Lending Capacity of EFSF/ESM and Timetable

FIGURE 11.8 SMP Total Weekly Purchases

FIGURE 11.9 European TARGET2 by Country

FIGURE 11.10 Greece Debt/GDP and Real GDP Growth

FIGURE 11.11 SNB Reserves

FIGURE 11.12 Swiss CPI 1978 to 1983

FIGURE 11.13 Dollar Liquidity Swaps, More Than 30 Days

FIGURE 12.1 Real GDP Growth: Average Annual Percent Change 2003–2012

FIGURE 12.2 CPI Year-over-Year: Average Annual Percentage Change, 2003–2012

FIGURE 12.3 Global Unemployment Rates: Annual Average, 2003–2012

FIGURE 12.4 U.S. Payrolls and U.S. Real GDP Change

FIGURE 12.5 Current Account as a Percent of GDP: Annual Average Change, 2003–2012

FIGURE 12.6 Budget Surplus/Deficit as a Percent of GDP: Annual Average Percent, 2003 to 2012

FIGURE 12.7 2012 Country’s Debt-to-GDP

FIGURE 12.8 Country’s 2012 Gross Domestic Savings as a Percentage of GDP

FIGURE 12.9 Effective Retirement Age for Men, 2002–2007

FIGURE 12.10 Social Benefit by Function as a Percentage of GDP, EU-27

FIGURE 12.11 Age Demography Change from 1970 to 2012

FIGURE 12.12 Demographic Implications on Savings and Current Account

List of Tables

TABLE 2.1 Sample Stress Test Days/Periods

TABLE 2.2 Sample of Returns by Asset Class, Duration, and Sharpe Ratio

TABLE 2.3 Trend Types

TABLE 2.4 Sample of Annual Trend Breakdown

TABLE 3.1 Bank of England—Quantitative Easing

TABLE 3.2 BoE Quantitative Easing—Query Output of Expected Returns

TABLE 4.1 The Four Product Groups

TABLE 6.1 Examples of Factors and Risk premia

TABLE 6.2 Correlation of Asset Returns 1958 to 2011

TABLE 7.1 Exchange Rate Regimes for the Hong Kong Dollar

TABLE 7.2 Table of Recent Interventions

TABLE 7.3 G7 Historical and Forecasted Current Account Surplus/Deficit

TABLE 7.4 Australia International Merchandise Exports, Top Five Countries from 2010 to 2011 (A$ in millions)

TABLE 7.5 GDP per Capita by Country and Region

TABLE 7.6 Carry-to-Risk Ratios on Carry Currencies

TABLE 8.1 Equity Indices by Region

TABLE 8.2 ETFs by Category

TABLE 9.1 30-Day Fed Funds Futures Specifications

TABLE 9.2 Five-Year CDS

TABLE 9.3 European Country with Respective Reference Entity

TABLE 9.4 Sample of Sovereign Defaults from 1998 to 2006

TABLE 9.5 Sample of Various Fixed Income ETFs

TABLE 10.1 Commodity Risks and Returns, 1970–2006: Annualized Monthly Returns (Continuously Compounded)

TABLE 10.2 Global Top 10 Oil Producers and Consumers

TABLE 10.3 Global Top 10 Oil Exporters and Importers

TABLE 10.4 OPEC Production and Quota Table

TABLE 10.5 Global Top 10 Natural Gas Producers and Consumers

TABLE 10.6 Central Banks Gold as a Percent of Reserves

TABLE 10.7 Global Gold Supply and Demand Table

TABLE 10.8 Global Silver Supply and Demand Table

TABLE 10.9 Global Silver Mine Production

TABLE 10.10 Global Platinum Supply and Demand Table

TABLE 10.11 Global Top 10 Copper Producers and Consumers

TABLE 10.12 Global Top 10 Aluminum Exporters and Importers

TABLE 10.13 Global Top 10 Corn Producers and Consumers

TABLE 10.14 Global Top 10 Corn Exporters and Importers

TABLE 10.15 Global Top 10 Wheat Producers and Consumers

TABLE 10.16 Global Top 10 Wheat Exporters and Importers

TABLE 10.17 Global Top 10 Soybean Producers and Consumers

TABLE 10.18 Global Top Soybean Exporters and Importers

TABLE 10.19 Global Top 10 Cotton Producers and Consumers

TABLE 10.20 Global Top 10 Cotton Exporters and Importers

TABLE 10.21 Global Top 10 Coffee Producers and Consumers

TABLE 10.22 Global Top 10 Coffee Exporters and Importers

TABLE 11.1 Types of Money

TABLE 11.2 Fed Quantitative Easing Program and Operation Twist

TABLE 11.3 Bank of England Quantitative Easing Program

TABLE 11.4 Effects of Past Large-Scale Asset Purchases on Interest Rates

TABLE 11.5 The Maastricht Convergence Criteria

TABLE 11.6 Euro Area NCBs’ Contribution to the ECB’s Capital

TABLE 11.7 European Debt/GDP

TABLE 11.8 OECD Household, Corporate, and Government Debt as a Percentage of Nominal GDP

TABLE 12.1 ISM Manufacturing at a Glance, September 2013

TABLE 12.2 Age Demography by Country

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Guide

Cover

Table of Contents

Begin Reading

Since 1996, Bloomberg Press has published books for financial professionals on investing, economics, and policy affecting investors. Titles are written by leading practitioners and authorities, and have been translated into more than 20 languages.

The Bloomberg Financial Series provides both core reference knowledge and actionable information for financial professionals. The books are written by experts familiar with the work flows, challenges, and demands of investment professionals who trade the markets, manage money, and analyze investments in their capacity of growing and protecting wealth, hedging risk, and generating revenue.

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GLOBAL MACRO TRADING

Profiting in a New World Economy

Greg Gliner

Cover image: © iStockphoto/Andrey Prokhorov

Cover design: C. Wallace

Copyright © 2014 by Greg Gliner. All rights reserved.

Published by John Wiley & Sons, Inc., Hoboken, New Jersey.

Published simultaneously in Canada.

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Library of Congress Cataloging-in-Publication Data

Gliner, Greg.

Global macro trading : profiting in a new world economy / Greg Gliner.

pages cm—(Bloomberg financial ; 567)

Includes bibliographical references and index.

ISBN 978-1-118-36242-6 (hardback)—ISBN 978-1-118-42038-6 (ePDF)—ISBN 978-1-118-41714-0 (ePub) 1. International trade. 2. Investments. 3. Macroeconomics. I. Title.

HF1379.G556 2014

332.64'2—dc23

2014013497

To My Family

Preface

Global Macro has been one of the most intriguing and most often-covered trading strategies, and it has also been responsible for creating some of the most legendary hedge fund managers. Conversely, it is also one of the most difficult strategies and possibly the least understood. After working as a Portfolio Manager in London I joined Tudor Investment Corporation as an Analyst, and I recall often feeling frustrated that there was no primer or reliable reference guide I could go to in times of need. Luckily, I was surrounded by extremely talented and brilliant people who gave me so much of their time. As I progressed, I found that more and more friends who worked for other hedge fund strategies had a lot of questions about Global Macro. It dawned on me that there existed a need for an introduction to the strategy of Global Macro and an explanation of how it is applied. The combination of my early frustrations and then becoming aware of this need is what compelled me to write a book on Global Macro Trading that could serve as both an introduction and a handy reference tool.

Global Macro Trading is separated into Part I and Part II. Part I provides a broad overview of Global Macro while Part II offers a deeper look into the foundation for Global Macro Trading. Part I spans Chapters 1 to 6 and Part II spans Chapters 7 to12. Additionally, you’ll find Bloomberg Cheat Sheets at the end of certain chapters to help navigate ways to use Bloomberg for that specific chapter and topic.

Part I

Chapter 1 examines the landscape of Global Macro as an asset class. It provides an overview of the strategy and returns and discusses why managers allocate to the strategy. Chapter 2 provides a detailed explanation of the trading process, as well as how to size trades and evaluate performance. It includes information on different types of bias, stress testing, risk utilization, and other risk management tools. Then, in Chapter 3, we tackle the construction of basic backtests and queries and analogs and provide the reader with framework to make trading evaluations. Chapter 4 starts to look at the four product groups, which serve as the building blocks for Global Macro. Part II will cover these in greater detail. Chapter 5 provides detail on technical analysis, including different types of charts, trends, moving averages and various oscillators such as Elliott waves, Fibonacci numbers, parabolics, seasonals, cycles, and crowd psychology. Chapter 6 explores the basic construction of systematic models and trading, as well as some commonly used strategies.

Part II

Chapters 7 through 10 explore the individual product groups: foreign exchange, equities, fixed income, and commodities. Chapter 7 looks at foreign exchange, and Chapter 8 examines equities. These chapters aim to provide the reader with some background, as well as some ways to value the respective asset classes on a macro level. Chapter 9 delves into the different aspects of fixed income. Chapter 10 examines commodities and separates them into energy, precious metals, agriculture, and industrial metals. It also serves as a reference tool about the main producers and consumers, as well as crop calendars. Chapter 11 explores central banking and takes an in-depth look at the Fed, ECB, and some of the recent programs following the financial crisis, as well as the importance of the main central banks in Global Macro Trading. Finally, Chapter 12 looks at important data releases followed by every macro trader, which is also meant for use as a reference tool.

The thorough information provided in Global Macro Trading enables readers to navigate Global Macro markets with confidence. After reading this book, you will understand the basic concepts behind the asset class and ways to trade it. You will also have a reference guide that will serve as a valuable tool in navigating the various regimes and market conditions. This information will empower the reader with a confident and competent understanding of Global Macro.

Acknowledgments

I would like to thank Dave Abner, who I met when I started as an analyst at BNP Paribas. He ran their ETF business during my time at BNP, and we kept in touch through the years. Dave has served as both a personal and professional role model for me. He is the author of The ETF Handbook and Visual Guide to ETFs and is the best-selling author for ETF books. When I ran the idea of writing a book on Global Macro Trading by him, he was more supportive than I ever could have imagined. He helped by connecting me to Wiley and boosted my confidence throughout the entire process, especially at points when my morale was low or I was plagued by self-doubt. He was my mentor throughout the entire process, and I am truly grateful to him and greatly admire his craft. He is the best in the ETF market and one of the greatest people I have the privilege of knowing.

I would like to thank Amit Hampel, who brought me on to join his team at Tudor Investment Corporation. Amit was the greatest mentor and boss I could have asked for. A large part of this book can be credited to the foundation I built while working for Amit. He was always one of the first in the office, and his unrelenting persistence and aim for perfection still resonate with me today. To this day, every time I have an investment idea, I ask myself how Amit would respond to it. I am honored to have worked for him and to call him a friend, an older brother, and a mentor.

I have been fortunate to work beside some of the most brilliant and morally sound associates I could have found in any profession. I would like to thank everyone I worked beside in my professional career. I want to thank former and current colleagues for making me a better person and for being my friends. I want to thank Mark Mitten, Todor Georgiev, Brian Martin, Donn Davis, Frank Leitner, Pat O’Brien, Beau Cummins, and Amit Hampel for being my mentors over the years.

Given the broad coverage of this book, I am grateful that I was able to call on some close friends and former colleagues who were instrumental in getting me to the finish line. I am very lucky to have had feedback from these incredibly knowledgeable industry participants: Dave Abner, Namik Immelback, Josh Smith, Frank Leitner, Kobi Platt, Charley Powers, Ray Fischer, Jay Hammarstedt, and Brett Steenbarger.

The expertise of the dedicated team at Wiley has been invaluable to me throughout the entire process. I want to thank Pamela Van Giessen, who helped me find this opportunity. Additionally, Evan Burton, Emilie Herman, Judy Howarth, Tula Batanchiev, and Steve Kyritz, who helped me take this book from conception to fruition, and I would like to thank Wiley as a whole for making this book a reality. Also, I would like to thank Mary Barbour, who I worked with as my editor for countless hours. I am grateful for all her care and attention; she is an extraordinary professional and I am grateful for her contribution.

Last, I want to thank my family for always being there for me. What they have achieved in the face of their many struggles served as my drive when I wanted to give up. I am so lucky to have parents who sacrificed so much to give me the life they never had. I love them and truly admire the example they set for me—I am so grateful to have inherited such high moral standards and to have had their support and encouragement throughout my entire life.

Part OneAn Overview of Global Macro

Chapter 1Surveying the Global Macro Landscape

Global macro, short for global macroeconomics, is the strategy of using economic theory, educated guesses about the macroeconomic environment, and geopolitical events to make large-scale investments around the world. It’s one of the most important strategies for any global investor, no matter if they are retail or institutional, because global events have a substantial influence on the performance of any type of investment.

Global macro is often considered the most flexible and opportunistic hedge fund strategy, due to the scope of traded products and the number of markets it covers. Its aim is to preserve capital, using stringent risk management to limit drawdowns. Profits are made through trades in equities, currency, fixed income, and commodities. These trades can occur anywhere in the world, hence the term “global macro.”

This chapter introduces the basic types of global macro strategies, historical returns of the strategy, and the various reasons why institutions choose to allocate to global macro.

Types of Global Macro Strategies

Like any hedge fund strategy, global macro can be categorized into substrategies. The four basic approaches of global macro are discretionary, systematic, high frequency, and commodity trading advisors (CTAs).

Discretionary and systematic macro strategies both have the potential to be extremely profitable and are powerful methods of analyzing markets and determining investments. These are the two most often used global macro strategies but, because the four are often used together, it’s important to understand how all of them work.

Discretionary

Discretionary macro trading, as the name implies, relies on a trader’s experience, intelligence, and knowledge to take subjective and often risky bets on various global markets in order to capture alpha and the best possible risk-adjusted return. With knowledge gleaned from studying global data, releases, economic data, and central bank action, among countless other factors, an investor can frame a top-down approach. This allows for a unique analysis of the risks and opportunities offered by industries, sectors, countries, and the macroeconomic situation at large.

Discretionary strategy requires serious organization and processing skills, since it involves such a large amount of data. The ability to analyze data across many different markets aids the trader in assessing whether or not a particular market is fully incorporating all factors into global asset prices.

The discretionary macro strategy is nimble and can also produce alpha in significant risk off markets. One example of a trader using historical patterns to capture alpha this way is Paul Tudor Jones’s prediction of the Black Monday crash on October 19, 1987. Jones observed that the market behavior during that period could potentially experience a catastrophic crash. He expressed this view by going short and made an enormous return on Black Monday.

Global macro managers have the luxury of being able to trade a vast amount of markets and also to go against the trend, shorting the stock market while other hedge fund strategies and mutual funds remain long. Thus, discretionary traders have the potential to make a tremendous profit in a selloff, while equity managers tend to lose significant amounts of capital.

Discretionary macro traders may also determine trades based on direction and relative value. Directional trades are made in hopes of an asset moving in a particular direction. For example, if a manager is bullish he or she could go long copper and hope to capture returns on the move up.

Relative value trades aim to pair or group assets together to capture the relative value differential between those assets, and profit from a divergence or change in the price difference. Looking at the European crisis, if a discretionary macro trader believes that German yields will be less affected than Italian yields, the trader can short Italian five years and go long German Bobls. If matters worsen in Europe and Italy acquires more credit risk, it could see yields rise in relative terms.

Systematic

The second main type of global macro strategy is systematic macro. Systematic managers employ a top-down model that takes various economic indicators into account. By using large sets of quantitative data, systematic macro strategies seek to earn alpha by capturing these dislocations. Systematic macro funds typically employ many PhDs to “systemize” all these quantitative factors in order to produce a model of trading positions that removes the variable of human emotion. Systematic macro prides itself on its stringent process, strong back-tests, and the ability to operate solely on quantitative analysis, hence ensuring maximum returns (assuming that past risk-adjusted returns are predictive). Over long periods of time—several years or more—systematic funds can produce more consistent returns than discretionary strategies; however, in periods of high volatility, they tend to underperform discretionary macro, as they did in 2008. Holding periods for systematic macro can range from days to months, or longer.

Systematic macro hedge funds have significantly changed the landscape in Macro with the amount of capital they have attracted. AQR Capital Management, founded by Cliff Asness, and Bridgewater, founded by Ray Dalio, manage over $80 billion and $100 billion, respectively, and have revolutionized systematic trading. The ability to trade multiple liquid asset classes in systematic macro means that asset managers can oversee large amounts of assets at once. Since equities, fixed income, commodities, and foreign exchange are the most liquid markets, it allows these funds to grow assets to previously unseen levels. Additionally, since strategies are constantly back-tested and improved, large asset allocators such as pensions, sovereign wealth funds, and endowments that have large amounts of capital to allocate, find comfort in using a computer-driven process with predictable drawdowns. Many of these institutions have minimum allocations of greater than several hundred million dollars, so, in a way, size also attracts more capital.

It is worth noting that, while systematic macro is scalable and can take large allocations, it is wise to allocate to both discretionary and systematic macro in a fairly even manner. This will allow an asset allocator to gain the advantages of both strategies and hedge the disadvantages. Discretionary macro is negatively correlated during periods of stress and, since discretionary traders can get short in a nimble way, it can produce profit in economic situations where most people are losing money. Systematic macro, on the other hand, lets traders allocate safely and predictably with more assurance.

A good book on this topic is Expected Returns (John Wiley & Sons, 2011) by Antti Ilmanen of AQR Capital Management (formerly of Brevan Howard).

High Frequency Trading

A third type of global macro trading is high frequency trading. This is the process of using highly sophisticated computers and technology to trade very short-term (millisecond) dislocations that may exist in the market. High frequency trading in macro is not as large or scalable as discretionary and systematic macro. Holding periods can range from milliseconds up to a few hours depending on the strategy. In high frequency trading, processing speed is of the utmost importance to ensure that certain dislocations are captured.

Commodity Trading Advisors (CTAs)

According to the National Futures Association, a Commodity Trading Advisor (CTA) is an individual or organization that advises others as to the value or advisability of buying or selling futures contracts, options on futures, or retail off-exchange foreign exchange contracts. Since futures are traded on most global macro markets, CTAs are considered a global macro strategy. Many larger CTAs employ a model-driven approach that can be technical or fundamental. However, most CTAs utilize a highly automated trend-following strategy that is in some ways similar to systematic macro. The methodology on position sizing used by most CTAs, which we’ll also be using in this book, originated with the Turtle Traders.

As with other trend-following strategies, CTAs perform very well over longer periods of time—as long as several years. They are, however, subject to large drawdowns (peak-to-trough) as a result. Man AHL and Winton Capital Management, both based in London, are widely regarded as the premier CTAs, each managing approximately $20 billion.

Return Profile and Allocations

Global macro as a strategy is very attractive because of its return profile. The Barclays Global Macro Index has achieved annualized returns of 10 percent from 2002 to 2012 compared to the S&P 500, which has been 2 percent over the same period. Additionally, the Barclays Global Macro Index has experienced lower volatility on an annualized basis compared to the S&P 500 over the same time period. As a result, global macro as a strategy has a higher Sharpe ratio, with the attractive investment characteristics of higher returns and lower volatility relative to other hedge fund strategies. Figure 1.1 demonstrates the outperformance of the Dow Jones Credit Suisse Global Macro Hedge Fund Index versus the S&P 500.

FIGURE 1.1 Global Macro versus S&P 500 from January 1995 to September 2013

Source: Dow Jones, Credit Suisse, and Bloomberg.

Global macro has shown a low correlation to S&P 500 returns, particularly in periods of market stress. Since many macro traders short during bear markets, this allows global macro funds to make money even when the market drops precipitously (Figure 1.2). Having a low correlation to the S&P 500 and a negative correlation during market collapses is also a very attractive return profile, and one of the reasons money managers tend to like global macro. While global macro returns have come down from the 1980s, 1990s, and 2000s with fixed income yields at historical lows and an atmosphere of economic uncertainty, global macro has still seen profit in all markets, which is why it remains a popular hedge fund strategy.

FIGURE 1.2 (a) Performance of Global Macro during the Top Five Losing Quarters in SPX since January 1995 and (b) Performance of Global Macro during the Top Five Best Quarters in SPX since January 1995

Source: Dow Jones, Credit Suisse, and Bloomberg.

As a result of the attractive uncorrelated return profile of global macro, investors have allocated to the strategy. Another attractive aspect of global macro is that it is one of the most, if not the most, liquid strategies in the hedge fund universe, considering that the assets traded are the most liquid to begin with. As a result of the very desirable return profiles and liquidity, global macro is the most popular hedge fund allocation by pension funds, as shown in Figure 1.3.

FIGURE 1.3 Changes in Pension Funds’ Allocations to Different Hedge Fund Strategies from 2009 to 2012

Source: Barclays Prime Services.

Hedge Funds and Global Macro

Some of the most famous hedge fund managers have emerged from global macro. In 1992, George Soros earned his fame on Black Wednesday, where he accurately predicted the devaluation of the British pound, making over $1 billion dollars in one day and earning himself the title of “The man who broke the Bank of England.” As mentioned previously, Paul Tudor Jones also successfully shorted the stock market prior to the October 19, 1987, crash, characterizing the week preceding the crash as one of the most exciting weeks of his life.

Louis Bacon, Stanley Druckenmiller, Bruce Kovner, Colm O’Shea, and Julian Robertson all earned their fame as discretionary macro traders able to profit in both bull and bear markets using the disciplined approach, stringent process, and analytic insight that are characteristic of global macro trading.

Summary

The goal of this chapter is to provide the reader with a brief introduction to the concept of global macro, the four basic strategies it encompasses, and why global macro is important to the macroeconomic situation at large.

Chapter 2Trading Process, Sizing Trades, and Monitoring Performance

Regardless of what hedge fund strategy you are trading, there are implicit risks involved. The first rule in any kind of investing is to understand how much you stand to lose, rather than how much you stand to gain. Having a stringent trading process that fully accounts for risk is critical to a trader’s long-term success. Like the old adage about pilots says: “There are old and bold fighter pilots, but rarely both.” The inescapable fact is that any time a global macro trader puts a trade on, things can go wrong. Some of these risks can be stress-tested while others are unpredictable, but a global macro trader should be as educated as possible on potential outcomes of any given trade.

This chapter will examine some of the tools one can use in the trading process, as well as some implicit human biases that make us more prone to potentially catastrophic risks. No process is perfect and each trader must find the one he or she likes best. With that said, just as humans evolve over time, one’s trading process should also evolve. This chapter will also outline some of the initial methods one can use to monitor and improve performance.

Understanding the different types of trading strategies and learning to monitor one’s own performance serves many important functions. Whether one is trading discretionary macro, systematic macro, or high frequency, having a process in place is the key to success. The greatest traders of all time used a variety of different strategies, but what they all had in common was a stringent process and the ability to take losses and recover.

Maintaining a Stringent Process

The biggest advantage of systematic and high frequency strategies is that once the systems and algorithms are in place, the variables of human emotion and psychology are removed. Trading discretionary macro, on the other hand, requires having a stringent process to ensure that we avoid our human impulses as much as possible. As mentioned before, all of these strategies can lead to profit, but it’s important for a trader to choose (and stick with) the strategy that feels most comfortable. For example, many people are skeptical of technical analysis; however, technicians can’t live without it since it gives them the discipline to know when to get in and out of positions. There is no right or wrong strategy when it comes to trading; it’s just important to figure out which one is the best for you and make sure your process is consistent.

A process should always evolve and improve. No one system or person is perfect and since the world of trading is constantly evolving, one’s process must as well. Evaluating one’s performance in a nonbiased and numeric fashion is an important part of driving process improvement. Oftentimes particular strategies may be making money while other strategies are not—so it’s statistically probable that there is opportunity for process improvement.

For example, many fixed income traders who systematically trade the 2s/10s yield curve might want to adjust the way they trade flatteners and steepeners since, in many countries, there is a zero lower bound (ZLB) and the two-year likely won’t react as much as it used to in years prior. This means that going further out in the yield curve will likely be a more effective move. If you aren’t continuously evaluating and updating your process, you might miss out on simple moves like this that can help your profits.

One of the best ways to maintain a consistent process is to log all of your trades in a journal or spreadsheet along with your thesis, conviction level, and the outcome of the trade. This will be an invaluable reference for you when it comes to future trades and will help you develop objectivity by finding patterns across both profitable trades and losing trades.

Objectivity and Bias

Gut feeling in discretionary trading is a lovely gift, but the fact remains that having objective procedural indicators relies far more on process than instincts. This section looks at the following types of bias:

Confirmation bias

Availability bias

Anchoring bias

Building indicators is not a scientific process. Ask 100 traders how they do it and you might get 100 different answers. But building a system, or combination, of important indicators can give some traders the discipline they require to stay true to their process. A big part of building a process is the understanding that we, as humans, are subject to biases that can impair our judgment; no one is immune. Making a checklist of questions and revisiting them often can help alleviate bias in one’s decision making.

Confirmation Bias

Confirmation bias means favoring information that supports one’s own argument, or favoring information that already has popular support. This tends to be the most common type of bias, as it is heavily aligned with human instinct.

Have you ever been to a social gathering where you were tempted to order fish, but when everyone else ordered a steak you followed suit? We all fall subject to confirmation bias in both trivial and significant ways.

If a trade moves against you, do you seek advice from others in the same position as you?

Do you think it is likely that bears consult with other bears? If they have a conversation with a bull, how open would they be to changing their minds? Hedge fund traders tend to seek confirmation from peers who hold the same positions that they do in order to reaffirm their instincts. How useful do you think this is?

One way to deal with this bias is to create a map of different trading scenarios and regimes. Some traders have an incredible ability to make money in bear markets but lose in bull markets, while others are great momentum traders but lose money when the market is choppy and mean reverts. If you can identify the trade you’re likely to have on, you can get a different perspective by seeking the advice of a trader who has had success in situations where you have lost money.

How mutually independent is the information you use for developing an argument for your trade?

It helps to log the reasons for your trade in your trade journal and then mark the points that are positive (+) and negative (−) for your argument. Examine these objectively and beware of how you may be skewing the facts to support your existing beliefs. The goal here is to try to outwit yourself by seeing the intentions behind your trade as objectively as possible, avoiding common pitfalls that can sometimes act in opposition to your process.

Availability Bias

Availability bias means overestimating the probability that something will occur, based on it being a vivid or memorable event rather than its relative likelihood. A great example is the fear of flying in an airplane. Many people have a fear of flying but have no problem driving a car. The fact is that the probability of dying in a plane crash is at least 2,000 times less likely than dying in a car crash, but because the fear of flying is one that is often discussed (i.e., it is “available”), people overestimate the chances that it will happen.

Imagine that your original thesis has been proven completely wrong, but the first data point you encounter after that fact is in support of your trade. How much weight should you give to this data as your new reason for keeping the trade?

This is a very important question and one without a clear answer. The best solution is to learn from past successes and mistakes by consulting your trade journal and analyzing your rationale for putting your trades on. This way you can get more familiar with the biases you tend to exhibit. Each time you feel a certain trade could be subject to this type of bias, you can revisit your journal where you outlined your original thesis for making a specific trade. You can track the outcome of prior trades and then objectively ask yourself whether it makes sense to stick with your original thesis or if you are overlooking some key information.

Anchoring Bias

Anchoring bias means prematurely establishing an estimated value for what the final value should be. The problem with anchoring bias is the inability to adjust that estimated value.

Are you married to a fair value price, level, or trade? Anchoring bias happens to all traders but it is probably most common among single stock investors. Single stock investors tend to do intensive fundamental analysis and arrive at a “fair value,” which can be defined as book value and free cash flow yield, for instance. The problem is when they become too attached, or married, to their thesis, it makes it difficult for them to assess a trade objectively. Legendary trader Jesse Livermore is known for his statement that “losers average losers.”

Tversky and Kahneman conducted a study to determine if two groups could guess the percentage of African countries that were part of the United Nations. Group One was asked if the population was more or less than 10 percent. Group Two was asked if it was more or less than 65 percent. The power of suggestion skewed the biases in different ways, resulting in the first group answering 25 percent and the second group answering 45 percent (Tversky and Kahneman 1974).

It is important to remember that no one is immune to these biases. If you have in your mind an idea of what price the asset should be trading at, be sure to question it lest you act with false confidence. The best thing one can do to fight anchoring bias is to seek out those who oppose your view and allow yourself to play devil’s advocate. If, for instance, you think the euro should go to parity, find analysts who think the euro is undervalued and force yourself to understand why they would think so. Even if you continue to defend your position afterward, you will have a much stronger argument as a result.

Remedies

Fortunately, there are remedies for these biases. Keeping a stringent process will help you counteract any influence they might have on you. As discussed, keeping a journal that logs your trades, along with their rationales and outcomes, will be a great reference point to help you with trades going forward. Playing devil’s advocate, performing extensive research on opposing views, and asking evenhanded questions can also help you avoid falling prey to these judgment biases.

Taking Losses

The ability to take losses is one of the most important attributes a trader can have. In Reminiscences of a Stock Operator, Jesse Livermore says, “A loss never bothers me after I take it. I forget it overnight. But being wrong—not taking the loss—that is what does damage to the pocketbook and to the soul.”

Human psychology has us wired to take profits early and hang on to losing trades too long, which stems from Prospect Theory. But this strategy dooms us to lose money since it doesn’t take into account the erratic behavior of market products. While this is a difficult instinct to overcome, we must acknowledge this fundamental human flaw and fight this urge as best we can. If a trade is losing, we need to cut it and take the loss—and if a trade is winning, let it run; traders actually need to do the exact opposite of what their instincts and psyche would have them do.

The first rule in investing is capital preservation; that is, limiting losses. Cutting losing trades and riding winning trades are the foundations of this rule. In Market Wizards, Paul Tudor Jones says, “I am always thinking about losing money as opposed to making money. The first thing I do is try to figure out what can go wrong.” Every trader will have winning trades and losing trades. The ability to acknowledge when one is wrong and move on is of the utmost importance. Peter Lynch of Fidelity once said, “If you are right half the time you have a terrific score.” Learning how to quickly cut a losing trade is more valuable (and realistic) than only making winning trades. Staying humble and being aware of the human tendency to err can save one a lot of money.