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31 Cards in this Set
- Front
- Back
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Definition of market efficiency |
*A reference to informationally efficiency and is a market where asset prices reflect all available information. *Such as: •Past information •Public information •Private information |
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Factors that affect market efficiency |
*Time frame of price adjustments: allows many traders to earn profits with little risk, then the market is relatively inefficient. *Transaction costs and information-acquisition costs: consider when evaluating the efficiency of a market. *Market value VS intrinsic value: market value is the price at which an asset can currently be bought or sold. Intrinsic value/fundamental value is the value that would be placed on an asset if investors if had a complete understanding of the asset’s investment characteristics. • If investors believe a market is highly efficient, they will usually accept market prices as accurately reflecting intrinsic values *Other factors: •the number of market participants and their trading activity •financial disclosure and •limits to trading (restrictions on short selling) |
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Active VS Passive investment strategies |
*Passive strategies: (buying and holding a broad market portfolio) will outperform active strategies due to cost advantages if markets are highly efficient. *Active investment strategy: may outperform a passive strategy on a risk-adjusted basis if markets are inefficient. |
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Market is viewed on continuum which 2 extremes? |
*These degrees of efficiency also vary through time, across geographical markets, and by type of market. *Completely inefficient: •Small capitalization U.S. stocks •International stocks •Real estate and venture capital *Completely efficient: •Asset price reflect information more quickly and more accurately than in a less-efficient market. •Large capitalization U.S. stocks •U.S. government securities |
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Forms of market efficiency [Eugene Fama] |
*Defined with respect to the available information that reflected in prices to earn abnormal returns *ABNORMAL RETURNS = ACTUAL RETURNS less EXPECTED RETURNS 1. Weak form: past market data 2. Semi-strong form: past market data and public information 3. Strong form: past market data, public information and private information. *Most empirical evidence supports semi-strong-form efficient securities in developed countries |
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Weak form |
*Past trading data are already reflected in current prices and investors cannot predict future price changes by extrapolating prices or patterns of prices from the past. Serial correlation in security returns + usefulness of technical analysis = TESTS OF WEAK FORM *Serial correlation: not enough serial correlation to create a profitable trading rule after considering transaction costs *Technical analysis: the analysis of historical trading information in an attempt to identify recurring patterns in the trading data that can be used to guide investment decisions. *Investors cannot consistently earn abnormal profits using technical analysis strategies in developed markets but opportunities in developing markets. *Technicians often argue that simple statistical tests are not conclusive because they are not applied to the more sophisticated trading strategies and the research excludes the technician’s subjective judgment. |
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Semi-strong form |
*Prices reflect all publicly known and available information: •Publicly available information includes financial statement data and financial market data (such as closing prices). •If a market is semi-strong efficient, then it must also be weak-form efficient. •Fundamental analysis is futile if the market is semi-strong-form efficient. *Financial analysis: •the examination of publicly available information and the formulation of forecasts to estimate the intrinsic value of assets. •Involves the estimation of an asset’s value using company data (earnings) and risk estimates as well as industry and economic data (economic growth/ inflation/interest rates). •Buy and sell decisions depend on whether the current market price is less than or greater than the estimated intrinsic value. |
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Empirical test of investors reaction to information released in even study |
1. Identify the period of study 2. Identify the stocks associated with event within the period 3. Estimate expected return for each company 4. Calculate the excess return as the difference between actual return and expected return 5. Perform statistical analysis on the excess/abnormal return to see if they're different from 0. |
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Strong form |
*It's both semi-strong and weak form efficient *Also means the prices reflect all private information *Tested by whether investors can earn abnormal profits by trading on non-public information (only if they're used) *Securities are not strong form efficient. |
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What good is fundamental analysis? |
*Fundamental analysis can be considered necessary even in an efficient market because it helps market participants understand value-relevant information. *Fundamental analysis can generate abnormal returns if an analyst creates a comparative advantage with respect to public information |
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What good are portfolio managers? |
*In an efficient market, passive portfolio management should outperform active portfolio management once costs are considered.*Efficiency does not rule out the need for portfolio management.*The role of a portfolio manager is not necessarily to “beat the market” but, rather, to establish and manage a portfolio consistent with investors’ objectives. |
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What good is technical analysis? |
*By detecting and exploiting patterns in prices, technical analysts assist markets in maintaining weak-form efficiency.*Not possible to earn abnormal returns because the actions of market participants will arbitrage this opportunity quickly, and the inefficiency will no longer exist. |
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Market pricing anomalies |
*Occurs if a change in the price of an asset or security cannot directly be linked to existing or new information. *If persistent, they are exceptions to the notion of market efficiency *The validity of any evidence supporting the existence of a market anomaly must be consistent over reasonably long periods. *data mining (data snooping): the wide spread search for discovering profitable anomalies, many findings could simply be the product of a process. *An initial hypothesis is developed which is based on economic rationale, followed by tests conducted on objectively selected data to either confirm or reject the original hypothesis. *Data mining the process is reversed where data is often examined with the intent to develop a hypothesis, instead of developing a hypothesis first. |
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Sampling of anomalies |
*The anomalies are placed into categories based on the research method that identified the anomaly. *Time-series anomalies were identified using time series of data. *Cross-sectional anomalies were identified based on analyzing a cross section of companies that differ on some key characteristics. *Other anomalies were identified by a variety of means, including event studies. |
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January (turn-of-the-year) effect |
*Tax-loss selling: Researchers have speculated that, in order to reduce their tax liabilities, investors sell their “loser” securities in December for the purpose of creating capital losses, which can then be used to offset any capital gains.*Window dressing: a practice in which portfolio managers sell their riskier securities prior to 31 December. Selling riskier securities is an attempt to make their portfolios appear less risky. *Other explanations: Most of these anomalies have been eliminated over time. One view is that the anomalies have been exploited such that the effect has been arbitraged away. Another view, however, is that increasingly sophisticated statistical methodologies fail to detect pricing inefficiencies. |
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Calender-based anomalies |
1. Turn-of-the-month effect: Returns tend to be higher on the last trading day of the month and the first 3 trading days of the next month 2. Day-of-the-week effect: The average Monday return is negative and lower than the average returns for the other 4 days, which are all positive 3. Weekend effect: Returns on weekends tend to be lower than returns on weekdays 4. Holiday effect: Returns on stock in the day prior to market holidays tend holidays tend to be higher than other days |
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Overreaction and momentum anomalies |
*Overreaction anomaly: Stock prices become inflated (depressed) for those companies releasing good (bad) news. •Werner DeBondt and Richard Thaler (1985) proposed a strategy that involved buying “loser” portfolios (outperformed) and selling “winner” portfolios (underperformed) based on their total returns over the previous three- to five-year period. *Momentum anomaly: Securities that have experienced high return in the short term tend to continue to generate higher returns in subsequent periods |
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Cross-sectional anomalies |
*Size effect: small-cap companies tend to outperform large-cap companies on a risk-adjusted basis. *Value effect: value stocks tend to outperform growth stocks on a risk-adjusted basis. Value stocks are generally referred to as those with below-average P/E and market-to-book ratios, and above-average dividend yields. |
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Closed-end investment funds |
*NAV - Discount = Value of closed-end fund *Discounts are attributed to management fees or expectations of the managers’ performance (no evidence).*Tax liabilities are associated with unrealized capital gains and losses that exist prior to when the investor bought the shares, hence, the investor does not have complete control over the timing of the realization of gains and losses. Although the evidence supports this hypothesis to a certain extent, the tax effect is not large enough to explain the entire discount. It has often been argued that the discounts exist because of liquidity problems and errors in calculating NAV. The illiquidity explanation is plausible if shares are recorded at the same price as more liquid, publicly traded stocks; some evidence supports this assertion. But as with tax reasons, liquidity issues explain only a portion of the discount effect. |
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Earnings surprise |
*An earnings surprise is the portion of earnings that is unanticipated by investors.*Positive (negative) surprises should cause appropriate and rapid price increases (decreases). *Results indicate that earnings surprises are reflected quickly in stock prices, but the adjustment process is not always efficient. *As a result, companies with the largest positive earnings surprises could subsequently display superior stock return performance
*Evidence indicating that these observed abnormal returns are an artifact of studies that do not sufficiently control for transaction costs and risk. |
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Initial Public offering |
*To help ensure the placement of a new issue, investment bankers frequently set its initial selling price too low.*The percentage difference between the issue price and the closing price at the end of the first day of trading is often referred to as the degree of underpricing.*Evidence suggests that, on average, investors who are able to buy the shares of an IPO at their offering price may be able to earn abnormal profits. *Offering price + abnormal profits = closing price |
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Frontiers of financial survey |
*attempting to benefit from them in practice is not easy. *Most researchers conclude that observed anomalies are not violations of market efficiency but, rather, are the result of statistical methodologies used to detect the anomalies. *If corrected, most of these anomalies disappear. *Another point to consider is that in an efficient market, overreactions may occur, but then so do under-reactions the markets are efficient. *In other words, investors face challenges when they attempt to translate statistical anomalies into economic profits. |
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Loss aversion |
*In traditional models, investors are assumed to be risk averse but the risk they face is that returns are variable and may be either higher or lower than expected. *The disapproval of a loss is assumed to be of equal magnitude to the approval of a similar-sized gain. *Loss aversion refers to investors disliking losses more than they like comparable gains.*Behavioralists argue that it can help explain the overreaction anomaly. |
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Behavioral finance VS Traditional finance |
*Behavioural is a field of financial thought that examines investor behavior and how this behavior affects what is observed in the financial markets: •Investors suffer from cognitive biases that may lead to irrational decision making • Investors may overreact/under-react to new information
*Traditional: • Investors behave rationally • Investors process new information quickly and correctly. |
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Overconfidence |
*Investors do not process information appropriately, and if there is a sufficient number of these investors, stocks will be mispriced. *But most researchers argue that this mispricing is temporary, with prices correcting eventually. *The issues, however, are how long it takes prices to become correctly priced, whether this mispricing is predictable, and whether investors can consistently earn abnormal profits. |
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Other behavioural biases |
*Basic idea is that investors are humans and imperfect and that the beliefs they have about a given asset’s value may not be homogeneous *Representativeness: investors assess outcomes depending on how similar they are to the current state.*Gambler’s fallacy: recent outcomes affect investors’ estimates of future probabilities.*Mental accounting: investors keep track of the gains and losses for different investments in separate mental accounts.*Conservatism: investors tend to be slow to react to changes.*Disposition effect: investors tend to avoid realizing losses but, rather, seek to realize gains.*Narrow framing: investors focus on issues in isolation. |
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Herding (Definition) |
*Clustered trading that may or may not be based on information. *A participant’s trading decision does not necessarily influence the decisions of others. |
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Information cascade |
*Is the transmission of information from those participants who act first and whose decisions influence the decisions of others. *May result in serial correlation of stock returns, which is consistent with overreaction anomalies. |
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Do information cascades result in correct pricing? |
*Some argue that if a cascade is leading toward an incorrect value, this cascade is “fragile” and will be corrected because investors will ultimately give more weight to public information or the trading of a recognized informed trader. *Although documented in markets, do not necessarily mean that investors can exploit them as profitable trading opportunities. |
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Are information cascades rational? |
*If the informed traders act first and uninformed traders imitate the informed traders, this behavior is consistent with rationality. *The imitation trading by the uninformed traders helps the market incorporate relevant information and improves market efficiency. *The empirical evidence is consistent with the idea that information cascades are greater for a stock when the information quality regarding the company is poor. *Hence, information cascades are enhancing the information available to traders. |
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If investors suffer from cognitive biases, must the market be inefficient? |
*Theory suggests YES: • If investors must be rational for efficient markets to exist, then all the foibles of human investors suggest that markets cannot be efficient *Evidence suggests NO: • If all that is required for markets to be efficient is that investors cannot consistently beat the market on a risk-adjusted basis, then the evidence supports market efficiency |
