CHAPTER 6

THE TOP-DOWN METHOD

So if you’re bullish on Financials, how much of your portfolio should you put in Financials stocks? Twenty-five percent? Fifty? One hundred percent? This question concerns portfolio management. Most investors concern themselves only with individual companies (“I like Bank of America, so I’ll buy some”) without considering how they fit into their overall portfolio. But this is no way to manage your money.

In this part of the book, we show you how to analyze Financials companies like a top-down portfolio manager. This includes a full description of the top-down method, how to use benchmarks and how the top-down method applies to the Financials sector. We then explore security analysis in Chapter 7, where we provide a framework for analyzing any company and discuss many of the important questions to ask when analyzing Financials companies. Finally, in Chapter 8, we conclude by giving a few examples of specific investing strategies for the Financials sector.

INVESTING IS A SCIENCE

Too many investors today think investing has “rules”—that all one must do to succeed in investing for the long run is find the right set of investing rules. But that simply doesn’t work. Why? All well-known and widely discussed information is already reflected in stock prices. This is a basic tenet of market theory commonly referred to as “market efficiency.” So if you see a headline about a stock you follow, there’s no use trading on that information—it’s already priced in. You missed the move.

If everything known is already discounted in prices, the only way to consistently beat the market is to know something others don’t. Think about it: There are many intelligent investors and longtime professionals who fail to beat the market year after year, most with the same access to information as anyone, if not more. Why?

Most view investing as a craft. They think, “If I learn the craft of value investing and all its rules, then I can be a successful investor using that method.” But that simply can’t work because by definition, all the conventional ways of thinking about value investing will already be widely known and thus priced in. In fact, most investment styles are very well-known and already widely practiced. There are undoubtedly millions of investors out there much like you, looking at the same metrics and information you are. So there isn’t much power in them. Even the investing techniques themselves are widely known—taught to millions in universities and practiced by hundreds of thousands of professionals globally. There’s no edge.

Moreover, it’s been demonstrated investment styles move in and out of favor over time—no one style or category is inherently better than another in the long run. You may think “value” investing works wonders to beat markets, but the fact is growth stocks will trounce value at times.

The key to beating stock markets lies in being dynamic—never adhering for all time to a single investment idea—and gleaning information the market hasn’t yet priced in. In other words, you cannot adhere to a single set of “rules” and hope to outperform markets over time.

So how can you beat the markets? By thinking of investing as a science.

Einstein’s Brain and the Stock Market

If he weren’t so busy becoming the most renowned scientist of the twentieth century, Albert Einstein would have made a killing on Wall Street—but not because he had such a high IQ. Granted, he was immensely intelligent, but a high IQ alone does not make a market guru. (If it did, MIT professors would be making millions managing money instead of teaching.) Instead, it’s the style of his thought and the method of his work that matter.

In the little we know about Einstein’s investment track record, he didn’t do very well. He lost most of his Nobel Prize money in bad bond ventures.1 Heck, Sir Isaac Newton may have given us the three laws of motion, but even his talents didn’t extend to investing. He lost his shirt in the South Sea Bubble of the early 1700s, explaining later, “I can calculate the movement of the stars, but not the madness of men.”

So why believe Einstein would have been a great portfolio manager if he put his mind to it? In short, Einstein was a true and highly creative scientist. He didn’t take the acknowledged rules of physics as such—he used prior knowledge, logic and creativity, combined with the rigors of verifiable, testable scientific method to create an entirely new view of the cosmos. In other words, he was dynamic and gleaned knowledge others didn’t have. Investors should do the same. (Not to worry, you won’t need advanced calculus to do it.)

Einstein’s unique character gave him an edge—he truly had a mind made to beat markets. Scientists have studied his work, his speeches, his letters, even his brain (literally) to find the secret of his intellect. In all, his approach to information processing and idea generation, his willingness to go against the grain of the establishment and his relentless pursuit of answers to questions no one else was asking ultimately made him a genius.

Most biographers and his contemporaries agree one of Einstein’s foremost gifts was his ability to discern “the big picture.” Unlike many scientists who could easily drown themselves in data minutiae, Einstein had an ability to see above the fray. Another way to say this is he could take the same information everyone else at his time was looking at and interpret it differently, yet correctly. He accomplished this using his talent for extracting the most important data from what he studied and linking them together in innovative ways no one else could.

Einstein called this “combinatory play.” Similar to a child experimenting with a new Lego set, Einstein would combine and recombine seemingly unrelated ideas, concepts and images to produce new, original discoveries. In the end, almost all new ideas are merely the combination of existing ones in one form or another. Take E = mc2: Einstein was not the first to discover the concepts of energy, mass or the speed of light. Rather, he combined these concepts in a novel way and, in the process, altered the way in which we view the universe.2

Einstein’s combinatory play is a terrific metaphor for stock investing. To be a successful market strategist, you must be able to extract the most important data from all of the “noise” permeating today’s markets and generate conclusions the market hasn’t yet appreciated. Central to this task is your ability to link data together in unique ways and produce new insights and themes for your portfolio in the process.

Einstein learned science basics just like his peers. But once he had those mastered, he directed his brain to challenging prior assumptions and inventing entirely different lenses to look through.

This is why this book isn’t intended to give you a “silver bullet” for picking the right Financials stocks. The fact is the “right” Financials stocks will be different in different times and situations. You don’t have to be Einstein, you just should think differently—and like a scientist—if you want to beat markets.

THE TOP-DOWN METHOD

Overwhelmingly, investment professionals today do what can broadly be labeled “bottom-up” investing. Their emphasis is on stock selection. A typical bottom-up investor researches an assortment of companies and attempts to pick those with the greatest likelihood of outperforming the market based on individual merits. The selected securities are cobbled together to form a portfolio, and factors like country and economic sector exposure are purely residuals of security selection, not planned decisions.

“Top-down” investing reverses the order. A top-down investor first analyzes big-picture factors like economics, politics and sentiment to forecast which investment categories are most likely to outperform the market. Only then does a top-down investor begin looking at individual securities. Top-down investing is inevitably more concerned with a portfolio’s aggregate exposure to investment categories than with any individual security. Thus, top-down is an inherently dynamic mode of investment because investment strategies are based on the prevailing market and economic environment (which changes often).

There’s significant debate in the investment community as to which approach is superior. This book’s goal is not to reject bottom-up investing—there are indeed investors who’ve successfully utilized bottom-up approaches. Rather, the goal is to introduce a comprehensive and flexible methodology any investor could use to build a portfolio designed to beat the global stock market in any investment environment. It’s a framework for gleaning new insights and making good on information not already reflected in stock prices.

Before we describe the method, let’s explore several key reasons a top-down approach is advantageous:

• Scalability: A bottom-up process is akin to looking for needles in a haystack. A top-down process is akin to seeking the haystacks with the highest concentration of needles. Globally, there are nearly 25,000 publicly traded stocks. Even the largest institutions with the greatest research resources cannot hope to adequately examine all these companies. Smaller institutions and individual investors must prioritize where to focus their limited resources. Unlike a bottom-up process, a top-down process makes this gargantuan task manageable by determining, upfront, what slices of the market to examine at the security level.
• Enhanced stock selection: Well-designed top-down processes generate insights that can greatly enhance stock selection. Macroeconomic or political analysis, for instance, can help determine what types of strategic attributes will face headwinds or tailwinds (see Chapter 7 for a full explanation).
• Risk control: Bottom-up processes are highly subject to unintended risk concentrations. Top-down processes are inherently better suited to manage risk exposures throughout the investment process.
• Macro overview: Top-down processes are more conducive to avoiding macro-driven calamities like the bursting of the Japan bubble in the 1990s, the Technology bubble in 2000 or the 2000 to 2002 bear market. No matter how good an individual company may be, it is still beholden to sector, regional and broad market factors. In fact, there is evidence “macro” factors can largely determine a stock’s performance regardless of individual merit.

Top-Down Means Thinking 70-20-10

A top-down investment process also helps focus on what’s most important to investment results: asset allocation and sub-asset allocation decisions. Many investors focus most of their attention on security-level portfolio decisions, like picking individual stocks they think will perform well. However, studies have shown over 90% of return variability is derived from asset allocation decisions, not market timing or stock selection.3

Our research shows about 70% of return variability is derived from asset allocation, 20% from sub-asset allocation (such as country, sector, size and style) and 10% from security selection. While security selection can make a significant difference over time, higher-level portfolio decisions dominate investment results more often than not.

The balance of this chapter defines the various steps in the top-down method, specifically as they relate to making country, sector and style decisions. This same basic framework can be applied to portfolios to make allocations within sectors. At the end of the chapter, we detail how this framework can be applied to the Financials sector.

Benchmarks

A key part of the top-down model is using benchmarks. A benchmark is typically a broad-based index of securities such as the S&P 500, MSCI World or Russell 2000. Benchmarks are indispensable road maps for structuring a portfolio, monitoring risk and judging performance over time.

Tactically, a portfolio should be structured to maximize the probability of consistently beating the benchmark. This is inherently different from maximizing returns. Unlike aiming to achieve some fixed rate of return each year, which will cause disappointment relative to peers when capital markets are very strong and is potentially unrealistic when the capital markets are very weak, a properly benchmarked portfolio provides a realistic guide for dealing with uncertain market conditions.

Portfolio construction begins by evaluating the characteristics of the chosen benchmark: sector weights, country weights and market cap and valuations. Then an expected risk and return is assigned to each of these segments (based on portfolio drivers), and the most attractive areas are overweighted, while the least attractive are underweighted. Table 6.1 shows MSCI World benchmark sector characteristics as of December 31, 2011, as an example, Table 6.2 shows country characteristics and Table 6.3 shows market cap and valuations.

Table 6.1 MSCI World Characteristics—Sectors

Source: Thomson Reuters; MSCI, Inc.4 MSCI World Index as of 12/31/11.

Table 6.2 MSCI World Characteristics—Countries

Source: Thomson Reuters; MSCI, Inc.,5 MSCI World Index as of 12/31/11.

Table 6.3 MSCI World Characteristics—Market Cap and Valuations

Notes: Market Cap in US Billions, P/E = price to earnings, P/B = price to book, P/CF = price to cash flow, P/S = price to sales.

Source: Thomson Reuters; MSCI, Inc.,6 MSCI World Index as of 12/31/11.

Based on benchmark characteristics, portfolio drivers are then used to determine country, sector and style decisions for the portfolio. For example, the Financials sector weight in the MSCI World Index is about 18%.7 Therefore, a portfolio managed against this benchmark would consider an 18% weight in Financials “neutral,” or market-weighted. If you believe Financials will perform better than the market in the foreseeable future, then you would “overweight” the sector, or carry a percentage of stocks in your portfolio greater than 18%. The reverse is true for an “underweight”—you’d hold less than 18% in Financials if you were pessimistic on the sector looking ahead.

Note that being pessimistic on Financials doesn’t necessarily mean holding zero stocks. It might only mean holding a lesser percentage of stocks in your portfolio than the benchmark. This is an important feature of benchmarking—it allows an investor to make strategic decisions on sectors and countries but maintains diversification, thus managing risk more appropriately.

For the Financials sector, we can use Financials-specific benchmarks like the S&P 500 Financials, MSCI World Financials or Russell 2000 Financials indexes. The components of these benchmarks can then be evaluated at a more detailed level, such as industry and sub-industry weights. (For example, we broke out MSCI World industry and sub-industry benchmark weights in Chapter 1.)

TOP-DOWN DECONSTRUCTED

The top-down method begins by first analyzing the macro environment. It asks the “big” questions like: Do you think stocks will go up or down in the next 12 months? Which countries or sectors should benefit most? Once you have decided on these high-level portfolio “drivers” (sometimes called “themes”), you can examine various macro portfolio drivers to make general overweight and underweight decisions for countries, sectors, industries and sub-industries versus your benchmark.

For instance, let’s say we’ve determined a macroeconomic driver that goes something like this: “In the next 12 months, I believe global economic growth will be slower than most expect.” That’s a very high-level statement with important implications for your portfolio. It means you’d want to search for stocks that would benefit most from weakening economic growth and activity.

The second step in top-down is applying quantitative screening criteria to narrow the choice set of stocks. Since, in our hypothetical example, we believe economic growth will be weak, we could take a neutral stance on Financials stocks and focus on more defensive industries within.

But which ones? Are you bullish on, say, Insurance Brokers? Government-focused office REITs? Fixed-income asset managers? Do you want exposure to the US or another region? Do you want small-cap Financials companies or large cap? And what about valuations? Are you looking for growth or value? (Size and growth versus value decisions are often referred to as “style” decisions.) These criteria and more can help you narrow the list of stocks you might buy.

The third and final step is performing fundamental analysis on individual stocks. Notice a great deal of thinking, analysis and work is done before you ever think about individual stocks. That’s the key to the top-down approach: It emphasizes high-level themes and funnels its way down to individual stocks, as illustrated in Figure 6.1.

Figure 6.1 Top-Down Deconstructed

Step 1: Analyze Portfolio Drivers and Country and Sector Selection

Let’s examine the first step in the top-down method more closely. In order to make top-down decisions, we develop and analyze what we call portfolio drivers (as mentioned previously). We segment these portfolio drivers in three general categories: economic, political and sentiment.

Portfolio drivers are what drive the performance of a broad category of stocks. Accurately identifying current and future drivers will help you find areas of the market most likely to outperform or underperform your benchmark (i.e., the broader stock market).

Table 6.4 shows examples of each type of portfolio driver. It’s important to note these drivers are by no means comprehensive, nor are they valid for all time periods. In fact, correctly identifying new portfolio drivers is essential to beating the market in the long term.

Table 6.4 Portfolio Drivers

Economic Drivers

Economic drivers are anything related to the macroeconomic environment. This could include monetary policy, interest rates, lending activity, yield curve analysis, relative GDP growth analysis and myriad others. What economic forces are likely to drive GDP growth throughout countries in the world? What is the outlook for interest rates, and how would that impact sectors? What is the outlook for loan growth or employment trends among countries?

Economic drivers pertain not only to the fundamental outlook of the economy (GDP growth, interest rates, inflation), but also to the stock market (valuations, M&A activity, share buybacks). As an investor, it’s your job to identify these drivers and determine how they’ll impact your overall portfolio and each of its segments.

The following is a sample list of economic drivers that could impact portfolio performance:

• US economic growth will be higher than consensus expectations.
• European Union interest rates will remain benign.
• Mergers, acquisitions and share buybacks will be strong.
• Emerging Markets growth will drive commodity demand.

Political Drivers

Political drivers can be country-specific, pertain to regions (European Union, Organisation for Economic Cooperation and Development [OECD]) or affect interaction between countries or regions (such as trade policies). These drivers are more concerned with categories such as taxation, government stability, fiscal policy and political turnover. Which countries are experiencing a change in government that could have a meaningful impact on their economies? Which sectors could be at risk from new taxation or legislation? Which countries are undergoing pro-growth reforms?

Political drivers will help determine the relative attractiveness of market segments and countries based on the outlook for the political environment. Be warned, however: Most investors suffer from “home country bias,” where they ascribe too much emphasis to the politics of their own country. Always keep in mind it’s a big, interconnected world out there, and geopolitical developments everywhere can have implications.

What are possible political drivers you can find? The following is a list of examples that can drive stocks up or down:

• Political party change in Japan driving pro-growth reforms.
• New tax policies in Germany stalling economic growth.
• Protests, government coups and conflict driving political instability in Thailand.

Sentiment Drivers

Sentiment drivers attempt to measure consensus thinking about investment categories. Ideally, drivers identify market opportunities where sentiment is different from reality. For example, let’s say you observe current broad market sentiment expects a US recession in the next year. But you disagree and believe GDP growth will be strong. This presents an excellent opportunity for excess returns. You can load up on stocks that will benefit from an economic boom and watch the prices rise as the rest of the market realizes it much later.

Since the market is a discounter of all known information, it’s important to try to identify what the market is pricing in. The interpretation of such investor drivers is typically counterintuitive (avoid what is overly popular and seek what is largely unpopular). Looking forward, which sectors are investors most bullish about and why? What countries or sectors are widely discussed in the media? What market segments have been bid up recently based on something other than fundamentals? If the market’s perception is different from fundamentals in the short term, stocks will eventually correct themselves to reflect reality in the long term.

A note of caution: Gauging market sentiment does not mean being a contrarian. Contrarians are investors who simply do the opposite of what most believe will happen. Instead, find places where sentiment (people’s beliefs) doesn’t match what you believe is reality and over- or underweight sections of your portfolio accordingly, relative to your benchmark. Examples of sentiment drivers include:

• Investors remain pessimistic about Financials despite improving fundamentals.
• Sentiment for the Chinese stock market approaching euphoria, stretching valuations.
• Professional investors universally forecast US small-cap stocks will outperform.

Step 2: Quantitative Factor Screening

Step two in the top-down method is screening for quantitative factors. This allows you to narrow the potential list of stocks once your portfolio drivers are in place.

There are thousands and thousands of stocks out there, so it’s vital to use a series of factors like market capitalization and valuations to narrow the field a bit. Securities passing this screen are then subjected to further quantitative analysis that eliminates companies with excessive risk profiles relative to their peer group, such as companies with excessive leverage or balance sheet risk and securities lacking sufficient liquidity for investment.

The rigidity of the quantitative screens is entirely up to you and will determine the number of companies on your prospect list. The more rigid the criteria, the fewer the companies that make the list. Broader criteria will increase the number of companies.

Examples

How can you perform such a screen? Here are two examples of quantitative factor screenings to show how broad or specific you can be. You might want to apply very strict criteria, or you may prefer to be broader.

Strict Criteria

• First, you decide you want to search for only Financials firms. By definition, that excludes all companies from the other nine sectors. Already, you’ve narrowed the field a lot!
• Now, let’s say based on your high-level drivers, you only want European Financials stocks. By excluding all other regions besides Europe, you’ve narrowed the field even more.
• Next, let’s decide to search only for Diversified Financials firms in the Financials sector.
• Perhaps you don’t believe very small stocks are preferable, so you limit market capitalization to $3 billion and above.
• Last, let’s set some parameters for valuation:
  • P/E (price to earnings) less than 14x
  • P/B (price to book) less than 2x
  • P/CF (price to cash-flow) less than 10x
  • P/S (price to sales) less than 3x

This rigorous process of selecting parameters will yield a small number of stocks to research, all based on your higher-level themes. But maybe you have reason to be less specific and want to do a broader screen because you think Financials in general is a good place to be. A broad screen might have only the following criteria:

• Financials sector
• Global (no country or region restrictions)
• Market caps above $1 billion

This selection process is much broader and obviously gives you a much longer list of stocks to choose from. Neither a strict nor broad screen is inherently better. It just depends on how well-formed and specific your higher-level themes are. Obviously, a stricter screen means less work for you in step three—actual stock selection.

Step 3: Stock Selection

After narrowing the prospect list, your final step is identifying individual securities possessing strategic attributes consistent with higher-level portfolio themes. (We’ll cover the stock selection process specifically in more detail in Chapter 8.) Your stock selection process should attempt to accomplish two goals:

In lieu of picking individual securities, there are other ways to exploit high-level themes in the top-down process. For instance, if you feel strongly about a particular sub-industry but don’t think you can add value through individual security analysis, it may be more prudent to buy a group of companies in the sub-industry or a category product like an exchange-traded fund (ETF). There is a growing variety of ETFs that track the domestic and global Financials sector and industries. This way, you can be sure to gain broad Financials exposure without much stock-specific risk. (For more information on ETFs, visit www.ishares.com, www.sectorspdr.com or www.masterdata.com.)

MANAGING AGAINST A FINANCIALS BENCHMARK

Now we can practice translating this specifically to your Financials allocation. Just as you analyze the components of your benchmark to determine country and sector components in a top-down strategy, you must analyze each sector’s components, as we did in Chapters 2–5. To demonstrate how, we’ll use the MSCI World Financials Sector Index as the benchmark. Table 6.5 shows the MSCI World Financials sub-industry weights as of December 31, 2011. We don’t know what the sample portfolio weights should be, but we know it should add up to 100%. Of course, if managing against a broader benchmark, your Financials sector weight may add up to more or less than the Financials weight in the benchmark, depending on over- or underweight decisions.

Table 6.5 MSCI World Financials Sub-Industry Weights Versus Sample Portfolio

Source: Thomson Reuters; MSCI, Inc.,8 MSCI World Index as of 12/31/11.

Keeping the sub-industry weights in mind will help mitigate benchmark risk. If you have a portfolio of stocks with the same sub-industry weights as the MSCI World Financials Index, you’re neutral—taking no benchmark risk. However, if you feel strongly about a sub-industry, like Insurance Brokers, and decide to purchase only those firms (one of the smallest weights in the sector), you’re taking huge benchmark risk. The same is true if you significantly underweight a sub-industry. All the same rules apply as when you do this from a broader portfolio perspective, as we did earlier in this chapter.

The benchmark’s sub-industry weights provide a jumping-off point in making further portfolio decisions. Once you make higher-level decisions on the sub-industries, you can make choices versus the benchmark by overweighting the sub-industries you feel likeliest to perform best and underweighting those likeliest to perform worst. Table 6.6 shows how you can make different portfolio bets against the benchmark by over- and underweighting sub-industries. Note: Portfolio A might be a portfolio of all Financials stocks, or it can simply represent a neutral Financials sector allocation in a larger portfolio.

Table 6.6 Portfolio A

Source: Thomson Reuters; MSCI, Inc.,9 MSCI World Index as of 12/31/11.

The “difference” column shows the relative difference between the benchmark and Portfolio A. In this example, Portfolio A is most overweight to Banks and most underweight to Insurance.

In other words, for this hypothetical example, Portfolio A’s owner expects Banks to outperform the sector and Insurance to underperform the sector. But in terms of benchmark risk, Portfolio A remains fairly close to the benchmark weights, so its relative risk is quite modest. This is extremely important: By managing against a benchmark, you can make strategic choices to beat the index and are well-diversified within the sector without concentrating too heavily in a specific area.

Table 6.7 is another example of relative portfolio weighting versus the benchmark. Portfolio B is significantly underweight to Diversified Financials with exposure concentrated in Banks. Because the sub-industry weights are so different from the benchmark, Portfolio B takes on substantially more relative risk than Portfolio A.

Table 6.7 Portfolio B

Source: Thomson Reuters; MSCI, Inc.,10 MSCI World Index as of 12/31/11.

Regardless of how your portfolio is positioned relative to the benchmark, it’s important to use benchmarks to identify where your relative risks are before investing. Knowing the benchmark weights and having opinions on the future performance of each sub-industry is a crucial step in building a portfolio designed to beat the benchmark. Should you make the correct overweight and underweight decisions, you’re likelier to beat the benchmark, regardless of the individual securities held within. But even if you’re wrong, you’ll have diversified enough not to lose your shirt.

Notes

1. Matthew Kalman, “Einstein Letters Reveal a Turmoil Beyond Science,” Boston Globe (July 11, 2006), www.boston.com/news/world/middleeast/articles/2006/07/11/einstein_letters_reveal_a_turmoil_beyond_science/ (accessed March 30, 2012).

2. Michael Michalko, “Combinatory Play,” Creative Thinking, www.creativethinking.net/DT10_CombinatoryPlay.htm?Entry=Good (accessed March 30, 2012).

3. Gary P. Brinson, Brian D. Singer, and Gilbert L. Beebower, “Determinants of Portfolio Performance II: An Update,” The Financial Analysts Journal 47 (1991), 3.

4. Source: MSCI. The MSCI information may only be used for your internal use, may not be reproduced or redisseminated in any form and may not be used to create any financial instruments or products or any indices. The MSCI information is provided on an “as is” basis and the user of this information assumes the entire risk of any use made of this information. MSCI, each of its affiliates and each other person involved in or related to compiling, computing or creating any MSCI information (collectively, the “MSCI Parties”) expressly disclaims all warranties (including, without limitation, any warranties of originality, accuracy, completeness, timeliness, non-infringement, merchantability and fitness for a particular purpose) with respect to this information. Without limiting any of the foregoing, in no event shall any MSCI Party have any liability for any direct, indirect, special, incidental, punitive, consequential (including, without limitation, lost profits) or any other damages.

5. Ibid.

6. See note 4.

7. Thomson Reuters, Financials weight in the MSCI World Index as of 04/30/2012.

8. See note 4.

9. Ibid.

10. Ibid.