Class Overview

A description of the class and what I cover.

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Introduction
In this session, we look at what an investment philosophy is, why you need one to be a successful investor and how best to tailor a philosophy to fit you (in terms of risk aversion, time horizon and tax status).

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Understanding Risk I: The risk in bonds
In this session, we examine the risks of investing in bonds. Even if the payments on the bond are guaranteed (there is no default risk), you face interest rate risk after you buy the bond and we look at simple measures of interest rate risk exposure. We also look at the additional risk that comes from default, how best to measure that default risk and how much to demand as compensation for exposure to that risk.

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Understanding Risk II: The risk in stocks
When you invest in the equity of a private or publicly traded company, you get a claim on the residual cash flows of the company.  The risks you face can be categorized on three dimensions: price risk versus cash flow risk, total risk versus just downside risk and stand alone risk versus risk added to a portfolio. In this session, we look at the menu of choices that you have as an investor in how best to measure this risk, ranging from theory based models, where the risk is measured as a beta or betas to alternative models, where risk is captured in accounting ratios, proxies, market implied measures and margin of safety.

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Financial Statement Analysis
In investing, we are dependent upon accounting statements for raw data in assessing companies. In this session, we look at the three basic financial statements: the balance sheet, where we record what a company owns and owes at a point in time, the income statement, where we measure revenues, expenses and earnings during a period and the statement of cash flows, where we explain changes in cash balances by looking at operating, investing and financing cash flows. We look at how a financial perspective can vary from an accounting perspective in each of these statements.

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Valuation: The Basics
Can you invest in something without knowing its value? While many people do, it strikes us as imprudent. In this session, we look at the basics of valuation, by laying out the ingredients of an intrinsic valuation model: cash flows, discount rates and growth. In particular, we note the importance of being consistent in your assumptions and note that higher growth can add value or destroy value. In the last part of the session, we look at relative valuation, where we value an asset by looking at how the market is pricing similar assets, and note the importance of controlling for cash flows, growth and risk, when using multiples.

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Trading Costs and Taxes
When you trade, you incur costs and these costs can be a drag on your investment returns. In this session, we look past the brokerage costs of trading to bring in the larger costs: the bid-ask spread, the price impact and the opportunity cost of waiting. These costs not only vary across companies and time, but they can vary across strategies. In the last part of the session, we look at how much of an investor’s returns are consumed by taxes and note that more trading generally leads to larger tax liabilities.

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Market Efficiency I: Laying the Groundwork
Our beliefs about market efficiency and inefficiency determine how we invest. In this session, we look at what an efficient market is and note that market efficiency does not preclude market mistakes (price can be different from value) or investors beating the market (though they tend to be few and far between). We also look at the requirements for a market to be efficient: liquidity in markets and traders/investors who are trying to exploit the inefficiencies. Finally, we eke out the implications: markets are likely to be less efficient if trading costs and trading frictions are high and value-seeking investors are few and far between. While most markets are efficient for most people at most points in time, there are pockets of inefficiency that we can be exploited in investing.

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Market Efficiency II: Testing market beating schemes and strategies
As investors, we are easy prey for the sales pitches from firms trying to sell us the next “magic bullet” for investing success. In this session, we look at three ways to test whether these strategies that claim to beat the market work. In the first, an event study, we look at a news announcement (that we think affects stock prices) and collect the stock prices of the companies affected by this announcement. If these returns are higher than expected (after adjusting for risk and market performance), the event may be worth building an investment strategy around. In the second, the portfolio approach, we test to see whether companies that share a common characteristic (small market capitalization, low price to book ratio etc.) are better investments than the rest of the market. In the third approach, we use multiple regressions to eke out the variables that drive stock returns and try to make money of them.

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Random Walks and Momentum
If markets follow a random walk, the price change in the next period should not only be independent of past price changes and completely unpredictable. Rather than debate the theoretical underpinnings of the random walk hypothesis, we look at the evidence on whether price changes in consecutive time periods are correlated and come to wildly divergent conclusions, depending on the time period in question. With very short intervals (minutes or hours), there is little detectable correlation, with much of the observed correlation being caused by market microstructure effects (the bid ask spread and liquidity). With daily or even weekly returns, the correlation turns negative, with paper profits to be made of the price reversals. As you go from weeks to months, the correlation turns positive with price momentum carrying the day. Finally, as you look at returns over many years (3 to 5 years), price reversals become the rule rather than the exception. This instability explains why it is so difficult for momentum investors to keep making money, since the key to making money seems to be avoiding the inflection points where momentum turns to reversal.

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Temporal Patterns
In addition to exhibiting correlation across time, stock prices seem to also follow patterns in calendar time. In this session, we look at two of the most commonly noted calendar time phenomena in stock prices. The first is the January effect, where stocks have done much better in January than in any other month of the year. While the January effect is commonly attributed to tax loss selling (at the end of the previous year) and institutional rebalancing, the most interesting feature of the January effect is that it is primarily attributable to the smallest firms in the market, with about half of the so-called small cap premium being earned in the first two weeks of the calendar year. The second effect is the weekend effect, where Mondays have historically been the worst day of the week to invest in stocks. This effect, though, seems to have weakened in the last two decades, with Fridays competing with Mondays for worst day-of-the-week honors.

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Technical Analysis
In this session, we look at charts and technical indicators as predictors of stock prices. Rather than provide a laundry list of technical indicators, we classify them into five groups, based upon the “behavioral” component that each tries to exploit. In the first group we include “contrarian” indicators, which try to measure what a group of investors (small individual investors, mutual funds, financial newsletter writers) think about the market with the intent of doing the opposite. In the second, we look at indicators that try to get ahead of shifts in demand and supply that will affect prices. In the third, we exploit slow learning in markets by using momentum indicators, hoping to generate profits as the markets adjust to good or bad news slowly. In the fourth, we identify experts or investors who are more knowledgeable than we are and try to follow their actions. In the fifth, we include long term (and mystical) indicators that are built on the presumption that there are long-term waves (that are both predictable and unstoppable) that drive market movements.

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Introduction to Value Investing
In this session, we begin by defining value investing. In our view, value investors invest in companies where they believe that the value from assets in place (investments already made) exceeds the price paid. As a consequence, they are drawn to mature companies in established businesses. Value investing can come in many forms, and there are at least three broad groups of value investors: passive screeners, contrarian investors and activist investors. We close the session by looking at two legends in the value investing space: Ben Graham, whose books represent the basis for value investing and Warren Buffett, whose every word is parsed for meaning by value investors.

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Value Investing: The Passive Screeners
In this session, we look at being a passive value screener, using “screens” for cheapness and quality to find the best bargains in the market. We look at earnings screens, book value screens, revenue screens and dividend yield screens, by first noting the intuition behind each screen, then the evidence on how that screen has performed over time and finally the possible weak spots with each screen. We end the session by setting up a general framework for value screening that tries to find mismatches: cheap stocks that have good fundamentals.

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Value Investing: The Contrarians
In this session, we look at buying stocks that have lost favor with the market, on the presumption that investors tend to over react to bad news. In particular, we look at two classes of contrarian investing. In the first, we examine the returns from buying the biggest losers in terms of stock prices over the previous year. While the overall evidence suggests that you can make significant returns from this strategy, we look at possible leakage from transactions costs and not having long enough time horizons. In the second, we evaluate whether you can generate positive returns from buying badly managed or poorly run companies, partly because the market has lowered expectations for these companies so much that it does not take much to beat these expectations.

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Value Investing: The Activists
In this session, we look at activist value investing, where you not only buy cheap companies, but also provide the catalysts for prices to adjust to value. In particular, we examine the strategy of investing in poorly managed companies and changing their asset mix, capital structure, dividend policy and corporate governance with the intent of increasing value (and price) over time. We classify activist investors into three groups, lone wolves (individual investors), activist mutual funds and activist hedge funds/private equity investors and examine differences in how they approach investing.

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Value Investing: Where is the beef?
Value investors often regard themselves as the grown ups in the room, the “sensible” investors in a market that is driven by fads and whims. In this session, we look at the returns earned by value investors and find little cause for celebration. Active value mutual funds underperform value index funds by more than active growth mutual funds underperform their index counterparts. While there are pockets of outperformance among individual and activist value investors, the overall conclusion that we reach is that active value investing does not deliver on its promise. We close the session by looking at possible reasons for this gap between promise and practice

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Investing on hope: Growth and Small Cap Investing
In this session, we set the table for growth investing as a philosophy by defining growth investing as an approach based upon the presumption that markets misprice growth assets more than assets in place. With this definition in place, we categorize growth investing into four groups: investing in small market cap companies, investing in initial public offerings, screening for growth at a reasonable price (GARP) and activist growth investing. We close the session by looking at the first of these four approaches, small cap investing, by first examining the empirical evidence on a small cap premium, then looking at the volatility of that premium over time periods and end by evaluating the reasons given for why the small cap premium may exist in the first place.

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Get in on the ground floor: The IPO story
In this session, we look at the process by which private businesses enter the public market place and whether investors can exploit frictions in that process to generate higher returns. We begin by describing the sequence of an initial public offering, from the investment banking underwriting agreement to the final offering date. We then examine the behavior of IPOs on the offering date, where, at least on average, the stock price jumps about 10-15% from the offering price. Trying to capture this “under pricing “ is difficult for investors to do for three reasons: a selection bias, where you tend to be over invested in over priced IPOs and under invested in under priced ones, a “hot and cold” markets problem, where you find almost nothing to invest in during cold IPO periods and too many choices in hot periods and a post-issue timing quandary, where you can lose most of your profits if you hold an IPO too long. We conclude on an optimistic note, by looking at ways you can modify the strategy to counter all three problems.

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Growth Investing: Growth at a reasonable price (GARP)
In this session, we look at screening stocks to find stocks where growth is being priced too low by markets. We first look at earnings growth screens, where you pick stocks that have either high past earnings growth or high earnings growth expected in the future, and note that neither screen has done well in delivering returns. We then focus on investing in high PE ratio stocks, a strategy that has done badly over long time periods, but that does offer high returns in sub-periods. Finally, we look at screens that incorporate both PE and growth, either by looking for companies that trade at PE ratios that are less than their expected growth rates, or by looking for companies that trade at low ratios of PE to growth rates (PEG ratios).

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Activist Growth Investing: Be your own change agent
In this session, we look at growth investing strategies where you not only invest in growth companies but also play a role in their growth. In particular, we focus on venture capital investing, by looking at the process by which a young, start-up negotiates with a venture capitalist and how the latter tries to profit from the investment. We also evaluate the failure risk that venture capitalists face, while investing in young companies, and the overall returns generated by venture capital investing over long time periods.

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Growth Investing: Against the tide of history?
In this session, we wrap up our discussion of growth investing by looking at why some investors may choose to be growth investors, even though it has historically not delivered the types of return that value investing has. In particular, we note that investors who are good at timing macro or market-wide shifts in interest rates and earnings can also generate high returns from growth investing. We also present evidence that activity (collecting and processing information, doing research) has a much bigger payoff with growth stocks than with value stocks, perhaps because markets make bigger mistakes with growth stocks and investors are far more likely to give up on intrinsic valuation.

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Information Trading: Trade on the news?
In this session, we introduce information trading (as a philosophy) by first delineating how efficient markets should respond to new information, as opposed to slow learning or over reacting markets. We then lay out different ways in which investors can play the information game: by getting a whiff of forthcoming information announcements (from private sources, rumors or research) and trading on that basis, by trading on the information announcement itself on the assumption that the immediate market reaction is likely to be skewed or investing after the announcement on the presumption that markets learn slowly or over react.

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Information Trading: Following the Insiders
In this session, we look at a strategy of following the insiders in a company, buying when they are buying and selling when they are, on the assumption that insiders know more about a company’s value than market participants. To evaluate whether this strategy works, we first look at whether insider trading is a good predictor of stock returns in subsequent time periods. While we do find that insider buying (selling) is followed by positive (negative) market returns, we also find that the signal is often wrong and that timely access to the insider trading information is critical. We also find insider trading is more predictive, if top executives are involved and at smaller companies. Finally, we conclude that we would generate far more lucrative payoffs if we had access to illegal insider trading information.

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Information Trading: Following the analysts
In this session, we look at equity research analysts and consider whether following their advice is a market-beating strategy.  We begin by looking at earnings estimates from analysts and note that while they are better predictors of actual earnings than time series models (which use only past earnings), the improvement in accuracy is modest and primarily in short term forecasts. We also note that revisions made by analysts to earnings estimates often generate short-term price momentum in stocks, perhaps because analysts can get clients to trade on those revisions. Finally, we look at analyst recommendations, by first reporting on the bias in the process (with positive recommendations vastly outnumbering negative recommendations) and then looking at the price impact of these recommendations. We note that sell recommendations have larger, long-term price impact than buy recommendations and that some analysts have more impact than others, either because their recommendations are built around stronger narratives or because they have more institutional following. A strategy of investing based upon analyst recommendations is unlikely to yield high returns unless it is focused on smaller, less followed companies and more influential, unbiased analysts.

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Information Trading: Public Information – Earnings Reports
In this session, we begin our discussion of trading based upon public information by looking at earnings reports. Since markets react to the news in earnings reports, we begin by categorizing that news into good, neutral and bad, by comparing the actual earnings to the predicted earnings. Not only do we see a price change that is consistent with the nature and magnitude of the surprise (positive price changes on positive surprises) but we also see two other phenomena. The first is that prices start to drift in the direction of the surprise even before the earnings report is made public (suggesting that someone is trading illegally ahead of the report) and that they continue to drift in the same direction after the report comes out (suggesting a slow learning market). We also look at earnings reports that are delayed and find that they are more likely to contain bad news. Finally, we look at the speed of price reaction on the day of the report and find that prices adjust quickly to earnings surprises, suggesting that any investment strategy built around earnings surprises has to be built around speedy trading/execution.

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Information Trading: Public Information – Other than Earnings
In this session, we turn our attention to public announcements other than earnings. We begin by looking at acquisition announcements, establishing that the winners in acquisitions are clearly target company stockholders and that many acquisitions don’t work in delivering value to acquiring company stockholders either at the time of the announcement or in the years after. We look at investment strategies built around acquisitions, with the most lucrative one being the identification of potential target companies ahead of the acquisition announcements. We also look at stock splits, where the evidence of a price reaction is mixed, and dividend announcements, where increases (decreases) in dividends are accompanied by stock price increases (decreases), though the price effect has decreased over time.

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Too good to be true? Pure Arbitrage
In this session, we lay down the requirements for pure arbitrage: assets that have identical cash flows that trade at different prices at the same point in time in different markets, with a guarantee that that the price difference will close. We note that pure arbitrage is most likely to occur in the derivatives markets and establish the arbitrage relationships that should govern the pricing of futures and options. With futures on storable commodities and financial assets, we create positions that have the same cash flows and risk using the futures and the underlying assets, and argue that if these positions have different costs, arbitrage is possible. With options, we introduce the notion of a replicating portfolio, where combining the underlying asset with borrowing/lending can create the same cash flows as an option, and argue that arbitrage is possible if the option and the replicating portfolio trade at different prices. We also look at arbitrage across options (calls and puts, options with different strike prices). With both futures and options, we conclude that arbitrage opportunities seem to exist in the early years after a new derivative is listed but fade as investors learn how to price the derivative.

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Close Enough? Near Arbitrage
In this session, we look at near arbitrage, where you have two very similar (but not identical) assets trading at different prices at the same point in time or two identical assets that are mispriced with no guarantee that the price difference will close. In both cases, we argue that while you can create low-risk positions, it is impossible to create the riskless, guaranteed profit positions that characterize pure arbitrage. We look at three examples of near arbitrage: a stock that is listed and traded on different markets (either as a multiple listing or depository receipt), a closed end fund (with the possibility of liquidation or open ending) and convertible mispricing (where the stocks, bonds, convertible bonds and options on the same company are mispriced, relative to each other). With each of these, we argue that investors with sufficient capital and the power to force convergence can make excess returns.

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Not riskless, not even close! Pseudo or Speculative Arbitrage
In this session, we focus on strategies that are often labeled as “arbitrage” but are really speculative, risky strategies that may or may not generate excess returns. First, we look at paired arbitrage, a practice of finding two companies that have historically moved together, where the current price relationship is not consistent with historic norms. While the strategy has made money for investors over time, the evidence suggests that the returns have come with risk and that the excess returns have faded over time. Second, we examine “merger arbitrage”, the practice of buying target company shares after a merger/acquisition is announced, hoping to make money from the price being higher when the deal is consummated. Again, while the returns are generally positive, it is exposed to the risk that the acquisition may fail, causing the stock price to drop back to pre-announcement levels. With speculative arbitrage strategies, we note the importance of adjusting borrowing (financial leverage) to reflect the risk in the strategy. We close the session by looking at hedge funds, noting three findings: that they have historically generated higher returns, given their risk exposures, than the rest of the market, that these higher returns come from a few big hedge fund winners (rather than from overall consistency) and that the worst hedge funds usually go out of business.

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Market Timing: Setting the table
In this session, we begin by arguing that all investors are market timers, insofar as they decide how much to invest and when to invest, with the difference being more of degree. The allure of market timing comes from the payoff that it delivers to those who are successful at it, since successful market timers will easily beat their counterparts in stock picking. The cost of market timing is that you may end up out of the market at exactly the wrong times (the periods where the market is going up).

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Market Timing Approaches: Non-financing & Technical Indicators
In this session, we begin by classifying non-financial indicators that have been used to time markets into three groups: spurious indicators that are correlated the market but have no economic relationship, feel good indicators that try to measure investor optimism and often work better as contemporaneous rather than leading indicators of stock prices and hype indicators that attempt to measure the fad factor in stock prices, with the assumption that hype goes before a fall. With technical indicators, we note that past market price movements have generally not been good indicators of future movements but that trading volume and volatility shifts may provide more timing promise.

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Market Timing Approaches: Mean Reversion & Macro Fundamentals
In this session, we begin by looking at market timing approaches that are built on the presumption that there is a normal level for a financial market and that prices revert back to this normal level. In the context of stocks, this usually takes the form of a normal PE, computed using either current or normalized earnings, with the assumption that if stocks collectively are trading at a PE higher (lower) than the normal PE, they are over (under) priced. With interest rates, the norm is defined as a range of interest rates based upon history and an assumption that interest rates will revert back to this range over time. In the second part of the session, we examine whether you can use macro economic data on interest rates and real growth to forecast future stock prices and find little basis for trading profits.

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Market Timing Approaches: Valuing the Market
In this session, we look at extending valuation approaches developed for valuing individual stocks to valuing the entire market. We begin by using an intrinsic valuation model to value the S&P 500 as the present value of expected cash flows on the index. While the approach is promising, it is dependent upon historical data and can provide poor signals, if there has been a systematic shift in risk preferences or growth potential. We also look at valuing a market on a relative basis, by either comparing it’s pricing over time or by comparing pricing across markets.

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Market Timing: Does it work?
In this session, we look the track record of market timers. We begin with mutual funds and note that the cash holdings of mutual funds are implicit measures of market timing, increasing when funds are bearish and decreasing when they are bullish. We find little evidence of market timing ability either among mutual fund managers, in general, or even among just tactical asset allocation funds. The evidence is a little more positive for hedge funds, insofar as some of them are better at forecasting forthcoming changes in liquidity and adjusting their portfolios accordingly.  Neither investment newsletter writers nor market strategists are investment banks seem to do well at timing markets. Notwithstanding this evidence, we look at four ways in which investors can bring market timing into their portfolios: through the asset allocation decision, by switching investment styles ahead of market shifts, by rotating through sectors as the economy evolves or by speculating using index options or futures.

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The case for passive investing: Active investors’ track record
In this session, we make the argument for passive investing by looking at the performance of active investors. We begin by looking at individual investors and note that they collectively under perform the market and that the under performance gets worse as they get more active. There is some cause for hope, though, since the very best investors do substantially out perform the market, especially if they stick to the companies that they know and don’t diversify too much. With mutual funds, the evidence is not favorable, since mutual funds under perform indices and the under performance cuts across all classes of mutual funds. Collectively, active investing does not seem to provide much of a payoff.

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More on investor performance: Continuity & Consistency
In this session, we continue examining the payoff to active investing by evaluating how much continuity there is in performance. We find little overall evidence of consistency, with investors in the top quartile in any time period just as likely to drop to the bottom quartile, as they are to stay in the top quartile. While there is some predictive power in mutual fund rankings and ratings, it comes from “hot hands” in mutual funds where the very best and the very worst mutual funds see a continuation of performance into the following time period. The overall under performance of money managers can be traced to four factors: high transactions costs, greater tax costs for investors (often caused by too much trading), failed attempts at market timing and various problems that can traced to incentive structures and behavioral factors.

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Passive Investing Choices
In this session, we look at the choices available for investors who choose the passive investing route. The first option is to invest in index funds, which have grown in terms of both dollar value and variety over the last four decades. They offer the benefits of tracking indices (of whichever asset class you want) with very little cost. The second is to choose among an ever-increasing array of exchange-traded funds (ETF), which also try to mimic indices, but can be bought and sold like individual stocks. The third is to try to have your cake and eat it too, by investing in enhanced index funds that claim to offer the benefits of index funds (low costs and index integrity) while generating slightly higher returns (using derivatives or by over investing in the best stocks in the index).

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The Grand Finale
In this session, we close by looking at the process of finding the best investment philosophy for you, as an investor. To make this choice, you have to begin with a personal assessment (patience, your need to be part of a group, age) and follow up with a financial assessment (job security, funds to invest, tax status). You then have to follow up by developing a sense and understanding of how markets works (and do not) based upon both the evidence and your own investment experiences. At the end of the process, you can end up with the either an investment philosophy that best fits you or a collection of philosophies that complement each other.

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