FIN 422: Student Managed Investment Fund

FIN 422: Student Managed Investment Fund
Topic 1: Efficient Capital Markets, Behavioral Finance, and Technical Analysis Larry Schrenk, Instructor

Overview 5.1 Efficient Capital Markets 5.2 Behavioral Finance
5.3 Implications of Efficient Capital Markets 5.4 Technical Analysis 5.5 Advantages of Technical Analysis 5.6 Challenges to Technical Analysis 5.7 Technical Trading Rules and Indicators

Learning Objectives @

Readings Reilley, et al., Investment Analysis and Portfolio Management, Chap. 5

5.1 Efficient Capital Markets

5.1 Efficient Capital Markets
An efficient capital market is one in which security prices adjust rapidly to the arrival of new information, which implies that the current prices of securities reflect all information about the security

5.1.1 Why Should Capital Markets Be Efficient?
An informationally efficient market: A large number of competing profit-maximizing participants analyze and value securities, each independently of the others New information regarding securities comes to the market in a random fashion Profit-maximizing investors cause security prices to adjust rapidly to reflect the effect of new information

5.1.1 Why Should Capital Markets Be Efficient?
The combined effect of: Information coming in a random, independent, unpredictable fashion, and Numerous competing investors adjusting stock prices rapidly to reflect this new information means that: Security price changes should be independent and random The security prices that prevail at any time should be an unbiased reflection of all currently available information In an efficient market, the expected returns implicit in the current price of a stock should be consistent with the perceived risk of the stock

5.1.2 Alternative Efficient Market Hypotheses
Random Walk Hypothesis – Changes in security prices occur randomly Fair Game Model Current market price reflects all available information about a security, and the expected return based upon this price is consistent with its risk Efficient Market Hypothesis (EMH) Divided into three sub-hypotheses depending on the information set involved

Weak-Form EMH Current prices reflect all security-market historical information, including the historical sequence of prices, rates of return, trading volume data, and other market-generated information This implies that past rates of return and other market data should have no relationship with future rates of return In short, prices reflect all historical information

Semistrong-Form EMH Current security prices reflect all public information, including market and non-market information This implies that decisions made on new information after it is public should not lead to above-average, risk-adjusted profits from those transactions In short, prices reflect all public information

Strong-Form EMH Stock prices fully reflect all information from public and private sources This implies that no group of investors should be able to consistently derive above-average, risk-adjusted rates of return This assumes perfect markets in which all information is cost-free and available to everyone at the same time In short, prices reflect all public and private information

5.1.3 Tests and Results of Efficient Market Hypotheses
Like most hypotheses in finance and economics, the evidence on the EMH is mixed Some studies have supported the hypotheses and indicate that capital markets are efficient Results of other studies have revealed some anomalies related to these hypotheses, indicating results that do not support the hypotheses

Weak-Form Hypothesis: Statistical tests of independence between rates of return Risk–return results for trading rules that make investment decisions based on past market information relative to the results from a simple buy-and-hold policy

Statistical Tests of Independence Autocorrelation tests Runs tests Tests of Trading Rules Testing constraints Use only publicly available data Include all transactions costs Adjust the results for risk Only better-known technical trading rules have been examined Too much subjective interpretation of data Almost infinite number of trading rules

Results of Simulations of Specific Trading Rules Trades a stock when the price change exceeds a filter value Studies of this trading rule have used a range of filters from 0.5 percent to 50 percent When the pre-2000 trading costs were considered, all the trading profits turned to losses. The recent lower trading costs could have a different result Testing results generally support the weak-form EMH, but results are not unanimous

Semistrong-Form Hypothesis: Tests and Results Two sets of studies: Studies to predict future rates of return using available public information beyond pure market information considered in the weak-form tests Time-series analysis of returns or the cross-section distribution of returns for individual stocks. Event studies that examine how fast stock prices adjust to specific significant economic events Studies test whether it is possible to invest in a security after the public announcement of a significant event Security prices should adjust rapidly, such that it would not be possible for investors to experience superior risk-adjusted returns by investing after the public announcement and paying normal transaction costs

Adjustment for Market Effects Test results should adjust a security’s rate of return for the rate of return of the overall market during the period considered Abnormal rate of return ARit = Rit - Rmt where: ARit = abnormal rate of return on security i during period t Rit = rate of return on security i during period t Rmt =rate of return on a market index during period t

Alternate Semistrong Tests Return Prediction Studies Predict the time series of future rates of return for individual stocks or the aggregate market using public information Predict Cross-Sectional Returns Look for public information regarding individual stocks that will help predict the cross-sectional distribution of future risk-adjusted rates of return Tests involve a joint hypothesis and are dependent both on market efficiency and the asset pricing model used

Results of Return Prediction Studies The time-series analysis assumes that in an efficient market the best estimate of future rates of return will be the long-run historical rates of return Tests attempt to determine whether any public information will provide superior estimates of returns for a short-run horizon (one to six months) or a long-run horizon (one to five years) Risk Premium Proxies Short-horizon returns have limited results Long-horizon returns analysis has been quite successful based on: Default spread Term structure spread

Quarterly earnings reports may yield abnormal returns due to unanticipated earnings change Earnings surprise Abnormal stock returns during the 13 or 26 weeks following the announcement of a large unanticipated earnings change Results indicate that the market does not adjust stock prices to reflect the release of quarterly earnings surprises as fast as expected by the semistrong EMH

The January Anomaly Stocks with negative returns during the prior year had higher returns right after the first of the year Tax selling toward the end of the year has been mentioned as the reason for this phenomenon Such a seasonal pattern is inconsistent with the EMH Several studies in foreign markets found abnormal returns in January, but the results could not be explained by tax laws

Other Calendar Effects All the market’s cumulative advance occurs during the first half of trading months Monday/weekend returns were significantly negative For large firms, the negative Monday effect occurred before the market opened (it was a weekend effect), whereas for smaller firms, most of the negative Monday effect occurred during the day on Monday (it was a Monday trading effect)

Predicting Cross-Sectional Returns Assuming an efficient market, all securities should have equal risk-adjusted returns because security prices should reflect all public information that would influence the security’s risk Studies typically examine the usefulness of alternative measures of size or quality to rank stocks in terms of risk-adjusted returns All of these tests involve a joint hypothesis because they consider the efficiency of the market but also depend on the asset pricing model for the measure of risk used in the test If a test determines that it is possible to predict risk-adjusted returns, these results could occur because the market is not efficient, or they could be because the measure of risk is faulty and, therefore, the measures of risk-adjusted returns are wrong

Price-Earnings Ratios Low P/E stocks experienced superior risk-adjusted results relative to the market, whereas high P/E stocks had significantly inferior risk-adjusted results Publicly available P/E ratios possess valuable information regarding future returns This is inconsistent with semistrong efficiency

Price-Earnings/Growth Rate (PEG) Ratios Studies have hypothesized an inverse relationship between the PEG ratio and subsequent rates of return Inconsistent with the EMH The results are mixed Several studies using either monthly or quarterly rebalancing indicate an anomaly In contrast, a study with more realistic annual rebalancing indicated that no consistent relationship exists between the PEG ratio and subsequent rates of return

The Size Effect Several studies have examined the impact of size on the risk-adjusted rates of return The studies indicate that risk-adjusted returns for extended periods indicate that the small firms consistently experienced significantly larger risk-adjusted returns than large firms Firm size is a major efficient market anomaly The small-firm effect is not stable from year to year

Neglected Firms and Trading Activity Firms divided by number of analysts following a stock Small-firm effect was confirmed Neglected firm effect caused by lack of information and limited institutional interest Neglected firm concept applied across size classes Size effect was confirmed, but no significant difference was found between the mean returns of the highest and lowest trading activity portfolios

Book Value–Market Value Ratio Significant positive relationship found between current values for this ratio and future stock returns Results inconsistent with the EMH Size and BV/MV dominate other ratios such as E/P ratio or leverage This combination only works during expansive monetary policy

Results of Event Studies Stock split studies Show that splits do not result in abnormal gains after the split announcement, but before Initial public offerings Seems to be underpriced by almost 18 percent, but that varies over time, and the price is adjusted within one day after the offering Exchange listing Listing of a stock on an national exchange such as the NYSE may offer some short-term profit opportunities for investors

Unexpected world events and economic news Stock prices quickly adjust to unexpected world events and economic news and hence do not provide opportunities for abnormal profits Announcements of accounting changes Are quickly adjusted for and do not seem to provide opportunities Corporate events Stock prices rapidly adjust to corporate events such as mergers and offerings

Summary on the Semistrong-Form EMH Evidence from tests of the semistrong EMH is mixed Hypothesis receives almost unanimous support from the numerous event studies on a range of events Mixed results come from exchange listing studies Numerous studies on predicting rates of return over time or for a cross section of stocks presented evidence counter to semistrong efficiency Results for cross-sectional predictors indicated anomalies counter to market efficiency

Strong-Form Hypothesis: Tests and Results Strong-form EMH contends that stock prices fully reflect both public and private This implies that no group of investors with private information will consistently earn above-average profits Testing Groups of Investors Corporate insiders Security analysts Professional money managers

Corporate Insider Trading Corporate insiders include major corporate officers, directors, and owners of 10 percent or more of any equity class of securities Insiders must report to the SEC each month on their transactions in the stock of the firm for which they are insiders Corporate insiders generally experience above-average profits, especially on purchase transactions Implies that many insiders had private information from which they derived above-average returns on their company stock

Security Analysts Tests have considered whether it is possible to identify a set of analysts who have the ability to select undervalued stocks The analysis involves determining whether, after a stock selection by an analyst is made known, a significant abnormal return is available to those who follow their recommendations

The Value Line Enigma Value Line (VL) publishes financial information on about 1,700 stocks The report includes a timing rank from 1 down to 5 Firms ranked 1 substantially outperform the market Firms ranked 5 substantially underperform the market Changes in rankings result in a fast price adjustment Some contend that the Value Line effect is merely the unexpected earnings anomaly due to changes in rankings from unexpected earnings

Analysts Recommendations There is evidence in favor of existence of superior analysts who apparently possess private information Analysts appear to have both market timing and stock-picking ability Consensus recommendations do not contain incremental information, but changes in consensus recommendations are useful The most useful information consisted of upward earning revision

Performance of Professional Money Managers Trained professionals, working full time at investment management If any investor can achieve above-average returns, it should be this group If any non-insider can obtain inside information, it would be this group due to the extensive management interviews that they conduct

Most tests examine mutual funds New tests also examine trust departments, insurance companies, and investment advisors While it is difficult to do a specific comparison between “universes” and the benchmarks, the overall results seem to indicate, at best, some weak support for the strong-form EMH

Conclusions Regarding the Strong-Form EMH Tests of the strong-form EMH have generated mixed results Results for corporate insiders did not support the hypothesis Results for Value Line rankings have changed over time and currently tend toward support for the EMH Individual analysts’ recommendations and changes in overall consensus estimates seem to contain significant information Historical performance by professional money managers provided support for the strong-form EMH Because money managers are similar to most investors who do not have access to inside information, these recent results are more relevant to the hypothesis Therefore, there is positive support for the strong-form EMH as applied to most investors

5.2 Behavioral Finance

5.2 Behavioral Finance It is concerned with the analysis of various psychological traits of individuals and how these traits affect the manner in which they act as investors, analysts, and portfolio managers The emphasis has been on identifying portfolio anomalies that can be explained by various psychological traits Three “Tributaries” Psychology Social psychology Neurofinance

5.2.1 Explaining Biases Prospect Theory
Contends that utility depends on deviations from moving reference point rather than absolute wealth Overconfidence (confirmation bias) Look for information that supports their prior opinions and decision Noise Traders Influenced strongly by sentiment, they tend to move together, which increases the prices and the volatility Escalation Bias Put more money into a bad investment

12 Biases 12 Bias that Might Have an Impact on Investing Behavior
Cooperation and Altruism Bidding and the Winner’s Curse Endowment Effect Status Quo Bias Loss Aversion Mental Accounts Winning by Losing Seeking Solace Percentages Calendar Effects Cash Dividends Overreaction The Psychology of Investing by John R. Nofsinger, Prentice Hall, 2008.

1. Cooperation and Altruism
Cooperation may be a viable investment strategy People’s motives may lead to actions different than conventional rationality, i.e. individual selfishness, would suggest What to do? Think about other alternatives, other perspectives on investing. Learn to think “outside the box”

2. Bidding and the Winner’s Curse
Bidding may lead to a suboptimal result when you bid your fair value Assuming everyone else has the correct value, if you won you overpaid! What to do? Be careful in setting your bid prices Generally, don’t bid your fair value—bid lower Don’t get emotional in your bid prices for financial assets You don’t have to buy it at this price!

3. Endowment Effect Sometimes we perceive that an asset’s value increases by virtue of our ownership Once you own something, its value hasn’t increased or changed Did the value really increase with your purchase? What to do? Realize that just because you own something does not increase the value of that asset Do not get too emotionally attached to a financial or other asset that you own

4. Status Quo Bias Sometimes individuals prefer the status quo over a new, more preferable position There is an aversion to change, even if the change is for the better Change may actually be good What to do? Try to be open minded with new ideas Be open to new ideas as long as they follow the principles of successful investing and your Investment Plan that you put together

5. Loss Aversion Often losses are given more weight in our minds than potential gains in any position These weights are more than utility theory would suggest What should this view on losses do to the way you form portfolios? What to do? Give gains and losses equal weight in your analysis It is the gains and losses of the overall portfolio that are important, not individual securities

6. Mental Accounts Often investors keep mental accounts rather than viewing individual assets as part of a total portfolio We try to save ourselves from ourselves We borrow 12% for a car versus taking the money from our investment account for the kids college savings (which are earning 2% annually) We know we may not pay it back if we do not borrow from a bank What to do? Set up separate accounts for separate goals

7. Winning by Losing Sometimes we actively trade stocks instead of buying index funds or ETFs which we know are lower cost and take a lot less time to invest We know index funds generally outperform the actively managed funds And we do not have the time, energy, or the money to try to beat the market What to do? If you do not have the time, energy, and money, invest in “sleep-well” portfolios of index funds You will at least get market returns and will generally beat most actively managed funds

8. Seeking Solace (abdicating responsibility)
Sometimes we follow newspaper/newsletter advice which we know has been shown to under-perform We prefer to take other’s advice rather than doing our own homework If the performance goes bad, we can blame others (we don’t have to take responsibility) What to do? Realize the limitations of these recommendations If you have no better knowledge, invest in index funds/ETFs which are passively managed

9. Percentages We sometimes move in and out of asset classes and stocks instead of keeping specific asset class percentages relatively constant (within our minimum and maximum amounts from our Investment Plan) We get lower returns from increased trading costs and may have more risk than we want What to do? Develop a good Investment Plan and rebalance as needed to your limits Work to reduce trading, taxes, and transactions costs

10. Calendar Effects The impact of tax and reporting is not consistent with theory. Behaviorists point out: Returns are a function of cash flows, which tend to be concentrated around calendar turns. Institutions tend to “window dress,” i.e., sell unwanted and buy desired stocks for period-end reports What to do? Don’t worry about calendar effects Invest for the long-term consistent with your Investment Plan and calendar effects will take care of themselves

11. Cash Dividends Theory has shown that dividends are irrelevant in the absence of taxes and transactions costs. Behaviorists suppose: Dividends can be justified by “mental accounts” which increase current income at the expense of “higher self control” equity accounts Older high-net worth investors value dividends more highly and concentrate in high income securities (preferred habitat) theory What to do? Invest for the long-term according to your Investment Plan and follow your strategy Emphasize capital gains over dividends

12. Overreaction Many investors assign a probability to asset returns based on past theory Appropriate reaction to a negative event is to update a prior probability to the most recent event Overreaction is when they assign too high a value What to do? Stay diversified, true to your Investment Plan, and don’t invest on rumors Invest for the long-term, not on rumors

5.2.2 Fusion Investing Integration of two elements of investment valuation-fundamental value and investor sentiment During some periods, investor sentiment is rather muted and noise traders are inactive, so fundamental valuation dominates market returns In other periods, when investor sentiment is strong, noise traders are very active and market returns are more heavily impacted by investor sentiments

Book Recommendation Vijay Singal. Beyond the Random Walk : A Guide to Stock Market Anomalies and Low-Risk Investing. Oxford University Press, HG4521 .S

Singal. Beyond the Random Walk

5.3 Implications of Efficient Capital Markets

5.3 Implications of Efficient Capital Markets
Overall, the results of many studies indicate the capital markets are efficient as related to numerous sets of information On the other hand, there are substantial instances in which the market fails to rapidly adjust to public information

5.3.1 Efficient Markets and Fundamental Analysis
Fundamental analysts believe that there is a basic intrinsic value for the aggregate stock market, various industries, or individual securities, and these values depend on underlying economic factors Investors should determine the intrinsic value of an investment at a point in time and compare it to the market price

If you can do a superior job of estimating intrinsic value, you can make superior market timing decisions and generate above-average returns Intrinsic value analysis involves: Aggregate market analysis Industry and company analysis

Aggregate Market Analysis with Efficient Capital Markets EMH implies that examining only past economic events is not likely to lead to outperforming a buy-and-hold policy because the market adjusts rapidly to known economic events Merely using historical data to estimate future values is not sufficient You must estimate the relevant variables that cause long-run movements

Industry and Company Analysis with Efficient Capital Markets Wide distribution of returns from different industries and companies justifies industry and company analysis Must understand the variables that effect rates of return and Do a superior job of estimating future values of these relevant valuation variables, not just look at past data

Important relationship between expected earnings and actual earnings Accurately predicting earnings surprises Strong-form EMH indicates likely existence of superior analysts Studies indicate that fundamental analysis based on E/P ratios, size, and the BV/MV ratios can lead to differentiating future return patterns

How to Evaluate Analysts or Investors Examine the performance of numerous securities that this analyst or investor recommends over time in relation to the performance of a set of randomly selected stocks of the same risk class Stock selections of a superior analyst or investor should consistently outperform the randomly selected stocks Consistency requirement is crucial because you would expect a portfolio developed by random selection to outperform the market about half the time

Conclusions about Fundamental Analysis Estimating the relevant variables is as much an art and a product of hard work as it is a science Successful investor must understand what variables are relevant to the valuation process and have the ability and work ethic to do a superior job of estimating these important valuation variables

5.3.2 Efficient Markets and Portfolio Management
Portfolio Managers with Superior Analysts Concentrate efforts in mid-cap stocks that do not receive the attention given by institutional portfolio managers to the top-tier stocks The market for these neglected stocks may be less efficient than the market for large well-known stocks

Portfolio Managers without Superior Analysts Determine and quantify your client's risk preferences Construct the appropriate portfolio Diversify completely on a global basis to eliminate all unsystematic risk Maintain the desired risk level by rebalancing the portfolio whenever necessary Minimize total transaction costs

The Rationale and Use of Index Funds and Exchange-Traded Funds Efficient capital markets and a lack of superior analysts imply that many portfolios should be managed passively (so their performance matches the aggregate market and minimizes the costs of research and trading) Institutions created market (index) funds, which duplicate the composition and performance of a selected index series

Insights from Behavioral Finance Opportunities to derive abnormal rates of return by acting on some of the deeply ingrained biases of investors Findings support the notion that the stocks of growth companies typically will not be growth stocks because analysts become overconfident in their ability to predict future growth rates and eventually derive valuations that either fully value or overvalue future growth Supports the notion of contrary investing, confirming the notion of the herd mentality of analysts Important to recall the loss aversion and escalation bias Recognize that market prices are a combination of fundamental value and investor sentiment

5.4-7 Technical Analysis

5.4 Technical Analysis Technical analysts see no need to study the multitude of economic, industry, and company variables to arrive at an estimate of future value because they believe that past price and volume movements or some other market series will signal future price movements Technicians also believe that a change in the price trend may predict a forthcoming change in some fundamental variables, such as earnings and risk, before the change is perceived by most fundamental analysts

5.4.1 Underlying Assumptions of Technical Analysis
The market value of any good or service is determined solely by the interaction of supply and demand Supply and demand are governed by numerous rational and irrational factors. Included in these factors are economic variables considered by the fundamental analyst as well as opinions, moods, and guesses. The market weighs all these factors continually and automatically Disregarding minor fluctuations, the prices for individual securities and the overall value of the market tend to move in trends, which persist for appreciable lengths of time Prevailing trends change in reaction to shifts in supply and demand relationships. These shifts, no matter why they occur, can be detected sooner or later in the action of the market itself

5.5 Advantages of Technical Analysis
Technical analysis is not heavily dependent on financial accounting statements. The technician contends that there are several major problems with accounting statements: Lack information needed by security analysts GAAP allows firms to select reporting procedures, resulting in difficulty comparing statements from two firms Psychological factors and other nonquantifiable variables do not show up in financial statements

5.7 Technical Trading Rules and Indicators

5.7.1 Contrary-Opinion Rules
Mutual Fund Cash Positions Buy when the mutual fund cash position is high, sell when low Credit Balances in Brokerage Accounts Buy when credit balances increase, sell when credit balances fall Investment Advisory Opinions When a large proportion of investment advisory services are bearish, this signals a market trough and the onset of a bull market

5.7.2 Follow the Smart Money Confidence Index
Measures the yield spread between high-grade bonds and intermediate grade bonds Declining (increasing) yield spreads increase (decrease) this index and are a bullish (bearish) indicator T-Bill/Eurodollar Yield Spread Decreases in this spread indicates greater confidence and is a bullish indicator Debit Balances in Brokerage Accounts (Margin Debt) Such balances represent buying on margin, which is assumed to be done by largely sophisticated investors Increases are a bullish signal

5.7.3 Momentum Indicators Breadth of Market
Measures the number of issues increased, and the number of issues declined each day The advance–decline index is typically a cumulative index of net advances or net declines Exhibit 5.4 Stocks above Their 200-Day Moving Average The market is considered to be overbought and subject to a negative correction when more than 80 percent of the stocks are trading above their 200-day moving average

5.7.4 Stock Price and Volume Techniques
Dow Theory The oldest technical trading rule Stock prices as moving in trends analogous to the movement of water Three types of price movements over time Major trends are like tides in the ocean Intermediate trends resemble waves Short-run movements are like ripples

Importance of Volume Technicians watch volume changes along with price movements as an indicator of changes in supply and demand The technician looks for a price increase on heavy volume relative to the stock’s normal trading volume as an indication of bullish activity Conversely, a price decline with heavy volume is considered bearish Technicians also use a ratio of upside–downside volume as an indicator of short-term momentum for the aggregate stock market

Support and Resistance Levels A support level is the price range at which the technician would expect a substantial increase in the demand for a stock A resistance level is the price range at which the technician would expect an increase in the supply of stock and a price reversal It is also possible to envision a rising trend of support and resistance levels for a stock

Moving Average Lines MA lines are meant to reflect the overall trend for the price series Shorter MA lines (the 50-day versus 200-day) reflect shorter trends If prices reverse and break through the moving-average line from below accompanied by heavy trading volume, most technicians would consider this a positive change, and vice versa If the 50-day MA line crosses the 200-day MA line from below on good volume, then this would be a bullish indicator

5.7.5 Efficient Markets and Technical Analysis
Assumptions of technical analysis directly oppose the notion of efficient markets The belief patterns of price adjustment directly contradicts advocates of the EMH who believe that security prices adjust to new information very rapidly If the capital market is weak-form efficient as indicated by most of the results, then prices fully reflect all relevant market information so technical trading systems that depend only on past trading data cannot have any value

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