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    Global Macro Trading: Profiting in a New World Economy
    Global Macro Trading: Profiting in a New World Economy
    Global Macro Trading: Profiting in a New World Economy
    Ebook595 pages5 hours

    Global Macro Trading: Profiting in a New World Economy

    By Greg Gliner

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    About this ebook

    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
    LanguageEnglish
    PublisherWiley
    Release dateMay 20, 2014
    ISBN9781118417140
    Global Macro Trading: Profiting in a New World Economy

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      Book preview

      Global Macro Trading - Greg Gliner

      Part One

      An Overview of Global Macro

      Chapter 1

      Surveying 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 2

      Trading 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.

      A stop-loss is a predetermined price to sell a long asset or buy back a short trade at a loss. The purpose of a stop-loss is to have a predetermined loss limit on any given trade. Putting in a stop-loss is, in a way, its own anchoring bias. However, there are procedural methods that try to ameliorate this bias. Sizing positions appropriately and accounting for historical volatility can help to mitigate anchoring bias and quantify a stop-loss. Technicians love using stop-losses because they signal when to get in and when to get out. A stop should be predetermined prior to the trade to avoid bias and, even though they face gap risk, using stops can limit downside risk. For bigger money managers and hedge funds, mental stops may be more appropriate so banks or dealers don’t sit on your orders and act in a way that may not be beneficial to you.

      Position Sizing

      Analyzing what to buy and sell dominates most of what portfolio managers and traders think about when they trade. Position sizing is often overlooked by many market participants, but is arguably more important than knowing what position to buy or sell. Remember, the first rule of investing isn’t to make money—it’s to preserve capital and avoid loss. While this may seem like an issue of semantics, utilizing position sizing ensures that you are always aware of your downside risk, that is, the amount you stand to lose.

      Position sizing aims to adjust each position for volatility. The importance of adjusting for volatility is that it equally normalizes all your positions such that if losses are incurred they are more predictable and statistically have the same probability of occurring, assuming that positions are weighted equally based on volatility. This allows traders to take positions in a broad range of markets and to have a measure by which to monitor risk.

      This concept of position sizing was developed by the Turtle Traders, whose work has influenced many managers and CTAs. The Turtles calculated the volatility of a particular asset, which they referred to as N, in which N is defined as the 20-day exponential moving average of the true range. The true range is defined as the maximum of the High on Day − Low on Day, High on Day − Previous Day’s Close, or Previous Day’s Close − Low. N ends up representing the 20-day average price move in the particular asset or volatility.

      Unit Size

      The Turtles have a specific methodology for calculating unit size but, for matters of simplicity, this book elects to take a slightly different approach to it. Let’s assume that the portfolio has $100,000,000 under management. One hundred basis points (1 percent) of the portfolio is equal to $1,000,000 and 25 basis points equals $250,000. We will assume that each unit size is equal to 25 basis points. What this means is that on any particular trade of one unit, the portfolio is willing to absorb 25 basis points

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