Part One


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Part One

  1. 1. Part One OUR DATA DRIVEN APPROACH TO INVESTING In Part One, we trace recent developments leading up to the Information Age stock market and provide a general over- view of our data driven approach to investing. In addition, we outline the key elements of our stock selection strategy and trading tactics.
  2. 2. Chapter 1: The Stock Market in the Information Age | 3 Chapter 1 THE STOCK MARKET IN THE INFORMATION AGE Widely held beliefs concerning the underlying mechanisms thought to govern stock price movements have undergone considerable change in recent years. It Pays To Be Skillful According to the conventional wis- For almost a half century, the view of the market taught at business schools dom, one’s expected return from and held by a large percentage of investment professionals has been that the stocks is purely a function of the stock market is “efficient,” i.e., that no one can consistently outperform the risk one is willing to assume. One’s risk-adjusted market return. prowess in selecting or trading stocks should make no difference in one’s returns. Efficient Market Theory is multi-faceted, controversial and, in our view, pa- tently absurd. But through sheer idiocy or self-de- structive intent, one could choose Efficient Market Theory forms the basis for an analytical construct known strategies that are guaranteed to lose money (by regularly placing market as portfolio optimization, which assumes that no stock is inherently a better orders to buy and sell thinly-traded investment than any other stock. Though it is acknowledged that some stocks stocks, for example). And it’s safe to are riskier bets than others, it is also assumed that the potential for reward say that, at any given time, there are is always exactly commensurate with risk. According to this line of thought, plenty of misguided, if not self-de- the only way to maximize a portfolio’s risk-adjusted return is by maximizing structive, participants in the stock its diversification. market. So, if some of their strate- gies are doomed, isn’t it reasonable to expect that other, more sensible, The practical application of this theory entails buying stocks in all sectors, strategies are likely to do better than however overvalued they might appear to be, in order to maximize diversifica- an average that includes the results tion. The wisdom of this approach went effectively unchallenged for decades. of the financially suicidal? Shouldn’t an investor who makes Then, in the 1990’s, along came the craze, when the market ascribed fewer mistakes than the average astronomical valuations to companies that, in many cases, had never pro- investor be likely to beat market duced a product or a dollar of earnings. We were told that mankind had averages? entered a new era driven by technological innovations that would change (cont’d) every aspect of life as we know it, including the behavior of stock markets.
  3. 3. 4 | DATA DRIVEN INVESTING– PROFESSIONAL EDITION Revenue figures, hard assets, earnings, and cash flow became less relevant to Some games are so rigged (e.g., rou- lette or slots) as to have a negative valuation than the creativity of a hot young company’s business model or the expected value for all who play (ex- iconoclasm inherent in its paradigm. cept the house). The stock market does not fit this description since, Many industry veterans saw this for the speculative bubble that it was, but as over the long-term, gains for the av- the market reached new high after new high, more and more of these older, erage stock have been excellent. It is wiser professionals succumbed to the sirens of the brave new information an “inherently profitable game,” in that the expected value for a typical era. Unfortunately for many, this period happened to coincide with the en- passive participant (such as an owner trance into the market by vast numbers of new investors, individuals invest- of an S&P 500 index fund) is greater ing through their 401k accounts who wanted a piece of the action. No one than zero - in the long-term, anyway. wanted to be left behind in one of the biggest run-ups in market history. Any inherently profitable game that can be consistently lost by the True believers in Efficient Market Theory were compelled to mindlessly buy actively incompetent should afford into the speculative frenzy by the dictates of their imperative to diversify as advantages to the actively skillful broadly as possible. Indeed, any portfolio not sporting a healthy slug of richly- which are not available to the pas- priced tech stocks was, according to the prevailing wisdom, poorly diversified. sive. In a 35-number roulette game with a 36:1 payoff (an inherently Upon the collapse of the market, investors began to return to tra- profitable game), over the long run all players are likely to win about as ditional notions of valuation, only to be assaulted by a barrage of financial often as the player who always bets reporting frauds and revelations of dishonest brokerage analyst recommenda- on the same number (i.e., the pas- tions. These scandals profoundly affected investors’ ability to evaluate stocks. sive player), however whimsical their Unable to believe the reported earnings for prior periods, and facing the pros- strategies for selecting numbers to pect that analysts (or management) might be lying about prospects for future bet upon might be. earnings, investors feel hard-pressed to make informed judgments concerning Long-term stock market returns which stocks to own. for any given investor, on the other hand, are likely to approximate: Thus, we have seen perceptions shift from faith in an “efficient market” to be- a) the average market return lief in the “new era of mankind” market and then, sadly, to the current widely PLUS or MINUS held view that the market is rigged in favor of insiders. b) a return component attribut- able to skill (or its lack) No doubt conventional thinking about the equity markets will continue to MINUS evolve. Whatever the prevailing wisdom turns out to be in the next phase, we c) market impact costs (driven by continue to believe that investors can prosper in the stock market by aligning amount of assets managed) MINUS their strategies with the market’s predictable response to certain key factors. d) brokerage commissions. We mentioned two such factors in the introduction to this book: Federal This reality is clearly at odds with the Reserve policy and the Presidential Election Cycle. These two factors have notion of an efficient stock market. influenced stock prices in highly predictable ways over many years, through times of chaos, crisis, and uncertainty, as well as during periods of order and prosperity. We identified these key factors – and measured their effects on different investment styles – by analyzing more than five decades of historical market
  4. 4. Chapter 1: The Stock Market in the Information Age | 5 data, and we tested their practical worth in over three years of real world application. Until recently, it would not have been possible for an individual or small firm to engage in this kind of analysis. Nor would it have been possible for us to develop Data Driven Investing– Professional Edition, with its emphasis on quantitative stock selection strategies, quick reaction to breaking news, and fast, cheap on-line trading. Information Age technologies are facilitating a fundamental realignment of opportunity away from big institutions and in favor of individuals and in- dependent investment advisors. The Internet provides a convenient way to gather information on stocks and monitor news sources. Computing tech- nology enables individuals to perform the kinds of analysis that formerly took teams of research assistants. And on-line, discount brokerage firms enable anyone with Internet access to enter trades for as little as $7. Of course, the advantages provided by the Information Age stock market mean little to those who lack the expertise to exploit them. Data Driven Investing– Professional Edition is dedicated to the proposition that individual investors and small firms can beat the market by learning and applying strategies that have worked consistently over long periods in the past, and by utilizing information technologies to stay informed and achieve better control over their trading.
  6. 6. Chapter 2: Data Driven Investing | 7 Chapter 2 DATA DRIVEN INVESTING We believe that, in any field of endeavor, success is a function of the wisdom of one’s decision rules and the discipline with which those rules are applied. The Data Driven Philosophy Nowhere is this more true than in the field of investing. The data driven approach is a pretty good approach to life in general. If Very broadly speaking, our rules for investing are: you study what has worked well in the past and consistently apply this Rule #1: Select stocks to own (and to avoid) based ONLY upon strategies knowledge to whatever you are do- that have worked consistently over long periods in the past. ing, your chances of success will probably be better than they other- Rule #2: Employ trading tactics based on well-established patterns of in- wise would have been – especially if vestor behavior. you are prepared to use this knowl- edge on a moment’s notice when an Rule #3: Develop pre-determined action plans so that the response to new opportunity arises. data is swift, automatic, and appropriate. Closely monitor news Good luck, it is said, occurs when sources for stories and react as quickly as possible to news of ma- preparation meets opportunity. terial events. Preparation is all about the analysis Rule #4: Stay with the program. Don’t deviate from rules 1-3, no matter of past data and the development of contingency plans. Exploitation how tempting the opportunity seems at the time. of an opportunity requires the rec- ognition of similarities between the We call our approach Data Driven Investing™ because the strategies we opportunity and the contingency for derive from our analysis of historical data interact continuously with real- which a plan has been devised, in ad- time data to drive our investment process. dition to the ability to react swiftly and decisively. You can’t expect to exploit oppor- tunities if you don’t have plans for finding and reacting to them.
  7. 7. 8 | DATA DRIVEN INVESTING– PROFESSIONAL EDITION Key Elements of Our Approach to Investing Data Driven Investing– Professional Edition consists of a number of elements which, in organizing this book, have been grouped into: · Strategies for selecting stocks; and, · Trading tactics We will cover strategies for selecting stocks in Part Two. Trading tactics will be presented in Part Three. Our strategies and tactics combine to form a three step process. How We Develop The first step is to identify the types of stocks that are likely to achieve superi- Screening Criteria or returns. We accomplish this by analyzing decades of historical market data to determine the quantitative characteristics of stocks that have consistently Data driven investing should not be performed well in each of the various monetary and political climates. confused with what is commonly referred to as “technical analysis.” We do not study short-term pat- The next step is to run quantitative screens to identify stocks possessing these terns in stock charts to predict the characteristics. There are thousands of publicly traded companies from which movements of individual stocks or to choose. Running screens allows us to better focus our attention on a “watch the market as a whole. Instead, we list” of suitable candidates. examine how fundamental forces that move equity markets – such as The third step is to employ time-tested tactics to trade stocks in response to Federal Reserve monetary policy – affect traditional methods of picking breaking news. The trading tactics that determine how and when we place stocks (e.g., ratios of price to earn- our orders are derived both from analysis of historical data and experience ings, price to book value, etc.), in or- gained while risking real money. der to develop the quantitative stock screening criteria that serve as the Success in the market requires more than just picking the right stocks. The first level of our selection process. timing, pricing, and type of orders we enter can significantly affect perfor- mance. Successful trading also depends on the discipline and consistency with which we apply our tactics. While we speak of this as a three step, sequential process, in practice all three tasks may be performed more or less continuously. We constantly seek to develop and maintain a watch list of the most desirable stocks to own, and we apply our tactics to enter trades whenever breaking news creates an op- portunity to buy or sell a watch list stock.
  8. 8. Chapter 2: Data Driven Investing | 9 Strategies for Selecting Stocks It Pays To Be In Style Our approach to selecting stocks involves: The Fed Effect on stock prices affects different classes of stocks in differ- · Reacting to Federal Reserve Policy: Federal Reserve Bank monetary ent ways. While the Fed was lower- policy exerts a profound and predictable influence on the behavior of ing rates in 2001-2002, the overall stock and commodity prices. The Fed Policy Cycle, alternating between market fell, contrary to conventional expansive and restrictive phases, determines the kinds of stocks we buy expectations, but carefully selected and sell. value stocks still did quite well. · Buying High Relative Strength Stocks: The relative strength measure compares a given stock’s return over a defined period of time to the re- turns of all other stocks in a given group. For example, a stock with a 12- month relative strength of 90 has outperformed 90% of the stocks in its The Politics Behind The group during the past 12 months. Stocks with high relative strength tend Election Cycle Effect to outperform market indices most of the time. One notable exception One theory attempting to explain is “tax season” (late December through early February), when low relative the Election Cycle Effect suggests strength stocks are usually the best choice.* that presidential administrations · Buying Nanocap Stocks: Other things being equal, we focus on stocks tend to save initiatives favorable for stocks until later in their terms, in whose market capitalization is under $100 million, thereby profiting an effort to concentrate the market’s from the well-established pattern – supported by decades of market data gains during re-election campaigns. – that the smaller the market value of a company, the better its stock price The Bush administration’s activities performance is likely to be. immediately following the 2002 mid-term elections suggest this pos- · Reacting to the Election Cycle: The four-year Presidential Election Cy- sibility. cle exerts a strong, predictable influence on stock market behavior. Our Harvey Pitt, the colossally un- data clearly indicate that overall market performance improves in the popular SEC Chairman, and Paul years leading up to an election. Furthermore, the Election Cycle Effect, O’Neill, considered by many a failed interacting with the Fed Effect, affects the performance of different in- Secretary of the Treasury, resigned vestment styles in different ways. shortly after the mid-term elections. About the same time, the adminis- · Buying Stocks with Minimal Analyst Coverage: In general, companies tration’s proposal to eliminate the that receive little or no coverage by brokerage analysts present better op- double-taxation of dividends and portunities, because analyst coverage tends to drive stock prices higher capital gains was floated. The market than they would otherwise be. Wall Street coverage reduces the potential responded with big gains in 2003, despite temporary setbacks caused for profiting from market inefficiencies and increases the likelihood of by the Iraq war. trading losses. (The absence of analyst coverage contributes to the supe- rior performance of nanocaps. Few stocks with market caps under $100 million are well covered by analysts.) However, we nearly always avoid very large companies with minimal analyst coverage. Brokerage analysts tend to avoid covering large cap companies with problems, rather than issue neutral or negative reports on them. * Source: Stock Traders Almanac 2002, page 112.
  9. 9. 10 | DATA DRIVEN INVESTING– PROFESSIONAL EDITION Neglected Large Caps · Profiting From Deficiencies in GAAP Accounting Rules: We take ad- vantage of differences between a company’s true economic condition and Bill Matson writes: performance, and its condition and performance as reported according to GAAP accounting principles. “When I was a retail broker in Mer- rill Lynch’s San Francisco office, one · Profiting from Fundamental Analysis: We employ fundamental analy- Silicon Valley CFO offered to open sis to evaluate news stories within the context of the subject firms’ indus- a large corporate account with me try attractiveness, competitive position, financial resources, and manage- if I could get Merrill to cover his company. ment quality. This helps us assess the impact of new developments on critical earnings and cash flow trends. “Merrill’s industry analyst told me that, even though the company Trading Tactics was large enough to merit coverage, he didn’t want anything to do with The key elements of the tactics with which we trade stocks can be it. Shortly thereafter, the company’s summarized as: stock nosedived. This illustrates a major reason some large companies don’t get their share of coverage · Understanding and Applying the Psychology of Investing: When buy- (i.e., they are accidents waiting to ing or selling shares, we remain acutely aware that we are interacting with happen).” real people, who are motivated by the same psychological underpinnings that drive us all. Prejudices, preferences, fears, and illusions impair inves- When a large company is in such tors’ ability to make rational decisions and delay their reactions to new bad shape that analysts shun it, you should too. information, leading to predictable patterns of behavior which can be ex- ploited to our profit. (This is consistent with data pre- sented in the September/October · Reacting to News Stories and Significant Price Changes: We react 1997 Financial Analysts Journal ar- swiftly and surely to news stories and significant price changes affecting ticle entitled “Is There a Neglected- the companies on our watch list. Usually, when a company meeting our Firm Effect?” by Craig Beard and selection criteria is the subject of a “good news” story, we try to be first in Richard Sias.) line to buy. When a company we own is the subject of a “bad news” story, we sell immediately in most cases. · Responding to Volume: Our trading decisions are informed by volume, meaning that our evaluation of events (such as price movements and Trading Illiquid Stocks news stories) is partly based on the volume of other investors’ trades en- tered in response. Market reactions confirmed by high volume are more Orders to buy or sell $1,000 worth credible and likely to be sustained than reactions accompanied by low of stock can cause multi-million dol- volume. lar changes in a thinly-traded com- pany’s market cap, but significant · Profiting from the Impatience of Others: On thinly-traded stocks with price changes accompanied by light wide bid-ask spreads, we enter standing orders to buy and sell shares at volume are almost always temporary. the edges of the spread. We call this tactic shopkeeper trading, because Knowing that the price will probably gravitate back to where it was before by maintaining an “inventory” of open orders, we supply convenience can provide valuable trading insight. (i.e., liquidity) similar to the way the owner of a retail store provides a quick, convenient way to make purchases. We earn the spread whenever impatient traders enter market orders to buy or sell (except in the rare
  10. 10. Chapter 2: Data Driven Investing | 11 instances when these traders have correctly anticipated a significant price trend – then we lose). A Really Stupid Thing To Do · Profiting from Established Trading Patterns: We trade on the basis of Placing a market order to buy or sell short-term patterns established over many years. Examples include tax- a thinly-traded stock is usually a re- motivated year-end trading patterns (e.g., the “January Effect”), weekly ally stupid thing to do – but lots of people do it anyway. patterns that often lead to temporarily depressed Monday morning prices, and patterns in the trading of spinoff stocks.* Shopkeeper trades provide a way to profit from such stupidity. · Making Money from Losers: We buy put options or short sell in situ- ations where a falling stock price is highly predictable, such as when an overpriced stock is the subject of a very bad news story. When a company reports its first quarterly profit following an extended period of losses, we often buy the stock before the market can fully respond to the turn- around. · Staying Fully Invested: Except during conditions we call “Panic Years” (see Chapter 11), we typically remain fully invested in equities, augment- Why Spinoffs Bounce Back ing our exposure with margin borrowing. Whenever our portfolio runs out of buying power, we sell the worst performers and reinvest the pro- When a company spins off a busi- ceeds in stocks associated with good news stories. ness unit, it issues shares in the new- ly formed corporation to its existing · Hedging Against Catastrophe: We cross-hedge a portion of our hold- shareholders. ings in order to reduce our overall risk. We typically buy put options on The recipients of these shares often the NASDAQ 100 index (i.e., QQQ’s) or richly-priced growth stocks sell them shortly thereafter, prompt- during Fed-Election Cycle phases that favor value stocks, switching to ed by brokers who earn easy money puts on the Dow Jones Industrial Average (DIA’s) during phases that by telling clients to unload the stock favor growth stocks. and buy something “more in line with their financial plans.” Also, many institutional investors are Integrating Stock Selection Strategy and Trading Tactics forced to sell spinoff shares due to prohibitions against their investing To summarize our data driven approach to investing, we continuously refine in small cap stocks. our stock selection criteria by backtesting investment strategies against the backdrop of critical cycles, such as the Federal Reserve monetary and Presi- In general, share prices of spinoff companies bounce back after this dential Election Cycles. We periodically run quantitative screens to update a initial sell-off. watch list of stocks possessing the appropriate criteria, focusing primarily on nanocap stocks (defined as companies with market caps of between $10 mil- lion and $100 million). We carefully monitor news sources, especially the Internet, for news stories affecting the companies on our watch list. We also watch for significant price changes on these stocks (because significant price movements often presage news events). When a news story breaks or a significant price change occurs, we swiftly implement predetermined actions in response. * “Institutional Demand and Security Price Pressure: The Case of Corporate Spinoffs,” Financial Analysts Journal, Sept./Oct. 1993 by Brown and Brooke, and “Restructuring Through Spinoffs” Journal of Financial Economics, 1993, by Cusatis, Miles, and Woolridge.
  11. 11. 12 | DATA DRIVEN INVESTING– PROFESSIONAL EDITION We buy stocks on the watch list when good news stories break. When there is bad news or a significant price decline on heavy volume, we usually sell the affected stock immediately. We try to stay fully invested, including buying on margin, and cull our losing positions whenever we run out of purchasing power in order to free up funds for new purchases. We hedge against catastrophe with put options on major market indices.