In this part of the book, we show you how to analyze Materials 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 Materials sector. We then delve into security analysis in Chapter 8, where we provide a framework for analyzing any company, and discuss many of the important questions to ask when analyzing Materials companies. Finally, in Chapter 9, we conclude by giving a few examples of specific investing strategies for the Materials sector.

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.

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.”²

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.

Both his contemporaries and most biographers 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, most 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.³

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 Materials stocks. The fact is the “right” Materials 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.

“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 upon 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 that 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 why a top-down approach is advantageous:

Our research shows about 70 percent of return variability is derived from asset allocation, 20 percent from sub-asset allocation (such as country, sector, size, and style), and 10 percent 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 Materials sector.

Tactically, a portfolio should be structured to maximize the probability of consistently beating the benchmark. This is inherently different than 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 under-weighted. Table 7.1 shows MSCI World benchmark sector characteristics as of December 31, 2007 as an example, while shows country characteristics, and Table 7.3 shows market cap and valuations. Table 7.2

Based on benchmark characteristics, portfolio drivers are then used to determine country, sector, and style decisions for the portfolio. For example, in Table 7.1 the Financials sector weight of the MSCI World Index is about 23 percent. Therefore, a portfolio managed against this benchmark would consider a 23 percent 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 hold more than 23 percent of your portfolio in Financials stocks. The reverse is true for an “underweight”—you’d hold less than 23 percent in Financials if you were pessimistic on the sector looking ahead.

Note that being pessimistic on Financials doesn’t necessarily mean holding zero financial 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 Materials sector, we can use Materials-specific benchmarks like the S&P 500 Materials, MSCI World Materials, or Russell 2000 Materials 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 4.)

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

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 infrastructure construction will be high, it likely means we’re bullish on Metals & Mining stocks. But which ones? Are you bullish on, say, copper producers? Aluminum producers? Steel producers? Do you want producers with exposure to the US or another region? Do you want small cap Materials companies or large cap? And what about valuations? Are you looking for growth or value? (Size and growth/value categories 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 that 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 is illustrated in Figure 7.1.

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 7.4 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.

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 an example list of economic drivers that could impact portfolio performance:

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 on 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:

Since the market is a discounter of all known information, it’s important to try and 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 than 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:

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.

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 a reason to be less specific and want to do a broader screen because you think Materials in general is a good place to be.

This selection process is much broader and obviously gives you a much longer list of stocks to choose from. Doing either a strict or broad screen isn’t 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.

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 are a growing variety of ETFs that track the domestic and global Materials sector, industries, and even specific commodity prices. This way, you can be sure to gain broad Materials exposure without much stock-specific risk. (For more information on ETFs, visit www.ishares.com, www.sectorspdr.com, or www.masterdata.com.)

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 Materials Index, you’ re neutral—taking no benchmark risk. However, if you feel strongly about a sub-industry, like Paper Packaging and decide to only purchase those firms (one of the smallest weights in the sector), you ’re taking a 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 7.6 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 Materials stocks, or it can simply represent a neutral Materials sector allocation in a larger portfolio.

The “difference” column shows the relative difference between the benchmark and Portfolio A. In this example, Portfolio A is most overweight to Diversified Metals & Mining and Steel and most underweight to Diversified Chemicals and Construction Materials.

In other words, for this hypothetical example, Portfolio A’s owner expects Diversified Metals & Mining and Steel to outperform the sector and Diversified Chemicals and Construction Materials 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 7.7 is another example of relative portfolio weighting versus the benchmark. Portfolio B is significantly underweight to Diversified Metals & Mining and most overweight to Gold and Fertilizers & Agricultural Chemicals. Because the sub -industry weights are so different from the benchmark, Portfolio B takes on substantially more relative risk than Portfolio A.

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.