MARKET EFFICIENCY — DEFINITION AND TESTS

Market Efficiency and Investment Valuation

• Question of whether markets are efficient, and if not, where the inefficiencies lie, is central to investment valuation.

• If markets are, in fact, efficient, the market price is the best estimate of value. and the process of valuation becomes one of justifying the market price.
• If markets are not efficient, the market price may deviate from the true value. and the process of valuation is directed towards obtaining a reasonable estimate of this value.

What is an efficient market?

• Efficient market is one where the market price is an unbiased estimate of the true value of the investment.
• Implicit in this derivation are several key concepts -

(a) Market efficiency does not require that the market price be equal to true value at every point in time. All it requires is that errors in the market price be unbiased, i.e. that prices can be greater than or less than true value, as long as these deviations are random.

(b) The fact that the deviations from true value are random implies, in a rough sense, that there is an equal chance that stocks are under or over valued at any point in time, and that these deviations are uncorrelated with any observable variable. For instance, in an efficient market, stocks with lower PE ratios should be no more or less likely to under valued than stocks with high PE ratios.

(c) If the deviations of market price from true value are random, it follows that no group of investors should be able to consistently find under or over valued stocks using any investment strategy.

Market Efficiency for Investor Groups

• Definitions of market efficiency have to be specific not only about the market that is being considered but also the investor group that is covered.

• It is extremely unlikely that all markets are efficient to all investors. but it is entirely possible that a particular market (for instance, the New York Stock Exchange) is efficient with respect to the average investor.
• It is also possible that some markets are efficient while others are not, and that a market is efficient with respect to some investors and not to others. This is a direct consequence of differential tax rates and transactions costs, which confer advantages on some investors relative to others.

Classifications

• Strong versus Weak Form Efficiency:

- Under weak form efficiency. the current price reflects the information contained in all past prices, suggesting that charts and technical analyses that use past prices alone would not be useful in finding under valued stocks.

- Under semi-strong form efficiency. the current price reflects the information contained not only in past prices but all public information (including financial statements and news reports) and no approach that was predicated on using and massaging this information would be useful in finding under valued stocks.

- Under strong form efficiency. the current price reflects all information. public as well as private, and no investors will be able to consistently find under valued stocks.

Implications of market efficiency

• An immediate and direct implication of an efficient market is that no group of investors should be able to consistently beat the market using a common investment strategy.
• An efficient market would also carry very negative implications for many investment strategies and actions that are taken for granted -

(a) In an efficient market, equity research and valuation would be a costly task that provided no benefits. The odds of finding an undervalued stock should be random (50/50). At best, the benefits from information collection and equity research would cover the costs of doing the research.

(b) In an efficient market, a strategy of randomly diversifying across stocks or indexing to the market, carrying little or no information cost and minimal execution costs, would be superior to any other strategy. that created larger information and execution costs. There would be no value added by portfolio managers and investment strategists.

(c) In an efficient market, a strategy of minimizing trading. i.e. creating a portfolio and not trading unless cash was needed, would be superior to a strategy that required frequent trading.

What market efficiency does not imply:

An efficient market does not imply that -

(a) stock prices cannot deviate from true value ; in fact, there can be large deviations from true value. The only requirement is that the deviations be random.

(b) no investor will ‘beat’ the market in any time period. To the contrary, approximately half of all investors, prior to transactions costs, should beat the market in any period.

(c) no group of investors will beat the market in the long term. Given the number of investors in financial markets, the laws of probability would suggest that a fairly large number are going to beat the market consistently over long periods, not because of their investment strategies but because they are lucky. It would not, however, be consistent if a disproportionately large number of these investors used the same investment strategy.

• In an efficient market, the expected returns from any investment will be consistent with the risk of that investment over the long term, though there may be deviations from these expected returns in the short term.

Necessary conditions for market efficiency

• Markets do not become efficient automatically. It is the actions of investors, sensing bargains and putting into effect schemes to beat the market, that make markets efficient.
• The necessary conditions for a market inefficiency to be eliminated are as follows -

(1) The market inefficiency should provide the basis for a scheme to beat the market and earn excess returns. For this to hold true -

(a) The asset (or assets) which is the source of the inefficiency has to be traded .

(b) The transactions costs of executing the scheme have to be smaller than the expected profits from the scheme.

(2) There should be profit maximizing investors who

(a) recognize the ‘potential for excess return’

(b) can replicate the beat the market scheme that earns the excess return

(c) have the resources to trade on the stock until the inefficiency disappears

Efficient Markets and Profit-seeking investors: The Internal Contradiction

• There is an internal contradiction in claiming that there is no possibility of beating the market in an efficient market and then requiring profit-maximizing investors to constantly seek out ways of beating the market and thus making it efficient.
• If markets were, in fact, efficient, investors would stop looking for inefficiencies. which would lead to markets becoming inefficient again.
• It makes sense to think about an efficient market as a self-correcting mechanism. where inefficiencies appear at regular intervals but disappear almost instantaneously as investors find them and trade on them.

Propositions about market efficiency

Proposition 1: The probability of finding inefficiencies in an asset market decreases as the ease of trading on the asset increases. To the extent that investors have difficulty trading on a stock, either because open markets do not exist or there are significant barriers to trading, inefficiencies in pricing can continue for long periods.

• Example:
• Stocks versus real estate
• NYSE vs NASDAQ

Proposition 2: The probability of finding an inefficiency in an asset market increases as the transactions and information cost of exploiting the inefficiency increases. The cost of collecting information and trading varies widely across markets and even across investments in the same markets. As these costs increase, it pays less and less to try to exploit these inefficiencies.

Example:

Initial Public Offerings. IPOs supposedly make excess returns, on average.

Emerging Market Stocks. Do they make excess returns?

Investing in ‘loser’ stocks. i.e. stocks that have done very badly in some prior time period should yields excess returns. Transactions costs are likely to be much higher for these stocks since-

(a) they then to be low priced stocks, leading to higher brokerage commissions and expenses

(b) the bid-ask becomes a much higher fraction of the total price paid.

(c) trading is often thin on these stocks, and small trades can cause prices to move.

Corollary 1: Investors who can estabish a cost advantage (either in information collection or transactions costs) will be more able to exploit small inefficiencies than other investors who do not possess this advantage.

• Example: Block trades effect on stock prices & specialists on the Floor of the Exchange
• Establishing a cost advantage, especially in relation to information, may be able to generate excess returns on the basis of these advantages. Thus a John Templeton, who started investing in Japanese and othe Asian markets well before other portfolio managers, might have been able to exploit the informational advantages he had over his peers to make excess returns on his portfolio.

Proposition 3: The speed with which an inefficiency is resolved will be directly related to how easily the scheme to exploit the ineffficiency can be replicated by other investors. The ease with which a scheme can be replicated itselft is inversely related to the time, resouces and information needed to execute it. Since very few investors single-handedly possess the resources to eliminate an inefficiency through trading, it is much more likely that an inefficiency will disappear quickly if the scheme used to exploit the inefficiency is transparent and can be copied by other investors.

• Example: Investing on stock splits versus Index Arbitrage

Testing market efficiency

• Tests of market efficiency look at the whether specific investment strategies earn excess returns. Some tests also account for transactions costs and execution feasibility. In every case, a test of market efficiency is a joint test of market efficiency and the efficacy of the model used for expected returns.
• When there is evidence of excess returns in a test of market efficiency, it can indicate that markets are inefficient or that the model used to compute expected returns is wrong or both.
• There are a number of different ways of testing for market efficiency, and the approach used will depend in great part on the investment scheme being tested.

A. Event Study

An event study is designed to examine market reactions to, and excess returns around specific information events. The information events can be market-wide, such as macro-economic announcements, or firm-specifc, such as earnings or dividend announcements.

• Step 1: Identify the event

(1) The event to be studied is clearly identified, and the date on which the event was announced pinpointed.

Announcement Date

___________________________________|___________________________________

Step 2: Collecting Returns

(2) Once the event dates are known, returns are collected around these dates for each of the firms in the sample. In doing so, two decisions have to be made.

• First, the analyst has to decide whether to collect weekly, daily or shorter-interval returns around the event. This will, in part, be decided by

- how precisely the event date is known

- by how quickly information is reflected in

• Second, the analyst has to determine how many periods of returns before and after the announcement date will be considered as part of the ‘event window’.

_____________|_______________________|________________________|_________

Return window: -n to +n

_____________|_______________________|________________________|_________

Return window: -n to +n

where,

ERjt = Excess Returns on firm j for day t (t = -n. 0. +n)

Step 4: Calculate the crosssectional average

(4) The excess returns, by day, are averaged across all firms in the sample and a standard error is computed.

Average excess return on day t=

where,

N = Number of events in the event study

Step 5: Estimate the statistical significance

(5) The question of whether the excess returns around the announcement are different from zero is answered by estimating the t statistic for each n, by dividing the average excess return by the standard error -

T statistic for excess return on day t = Average Excess Return / Standard Error

If the t statistics are statistically significant, the event affects returns; the sign of the excess return determines whether the effect is positive or negative.

Illustration 1: Example of an event study — Effects of Option Listing on Stock prices

• Academics and practitioners have long argued about the consequences of option listing for stock price volatility. On the one hand, there are those who argue that options attract speculators and hence increase stock price volatility. On the other hand, there are others who argue that options increase the available choices for investors and increase the flow of information to financial markets, and thus lead to lower stock price volatility and higher stock prices.
• One way to test these alternative hypotheses is to do an event study, examining the effects of listing options on the underlying stocks’ prices. Conrad(1989) did such a study, following these steps -

Step 1: The date on which the announcement that options would be listed on the Chicago Board of Options on a particular stock was collected.

Step 2: The prices of the underlying stock(j) were collected for each of the ten days prior to the option listing announcement date, the day of the announcement, and each of the ten days after.

Step 3: The returns on the stock (Rjt) were computed for each of these trading days.

Step 4: The beta for the stock ( b j) was estimated using the returns from a time period outside the event window (using 100 trading days from before the event and 100 trading days after the event).

Step 5: The returns on the market index (Rmt) were computed for each of the 21 trading days.

Step 6: The excess returns were computed for each of the 21 trading days -

ERjt = Rjt — b j Rmt. t = -10,-9,-8. +8,+9,+10

The excess returns are cumulated for each trading day.

Step 7: The average and standard error of excess returns across all stocks with option listings were computed for each of the 21 trading days. The t statistics are computed using the averages and standard errors for each trading day.

Option Listing and Stock Returns: The Results