Market Efficiency

In this video we will take a look at the concept of market efficiency and the three forms of market efficiency.

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Market efficiency is a very important concept for a portfolio manager. Market efficiency, a concept derived from the Efficient Market Hypothesis, suggests that the price of a security reflects all the information available about that security. So, in an efficient market, no investor has access to any special information that he can use to make an extra profit. In effect, if the markets are efficient, then you can’t beat the market.

The efficient market hypothesis (EMH) was formulated by Eugene Fama in 1970.

If the markets are perfectly efficient, then it does not make sense for the portfolio managers to pursue active investment strategies. The active investment strategies will actually underperform compared to passive strategies because of the additional transaction costs and fees.

So, are our markets really efficient and how do we measure the level of efficiency? One way to do so is to determine the time it takes for a trading activity to affect the price of the security, i.e., the time the information is made available and then time when the security’s price actually reflects it. In foreign exchange market, which is considered very efficient, this time lag may be less than a minute. If the time lag is high, then a trader who has this information will have sufficient time to use this information to make a profit.

Another important point is that if markets are efficient, the security’s price should not be affected by any information that was well anticipated by the investors. Only information that was not fully anticipated by the investors will have an impact on the price.

In a highly efficient market, the investors can expect the security’s market value to reflect its intrinsic value. In inefficient markets the securities can be overvalued or undervalued, that is their fundamental values can be above or below the prices at which they are trading. The traders can buy undervalued stocks and sell overvalued stocks to make a profit.

In reality the markets are not efficient. We can also not say that they are totally inefficient. Depending on a combination of factors markets exhibit varying degrees of efficiency. One such factor is the number of market participants. The more the number of participants such as investors, traders, and other participants, the more efficient is the market. This is simply because the more the number of participants actively involved in the market, the faster any price anomalies will be identified and the faster they will disappear.

The second factor affecting market efficiency is the availability of information. A higher availability of information will lead to higher market efficiency. For example, the information is more easily available in larger exchanges such as NYSE, that makes them more efficient compared to smaller exchanges where the information may not be disseminated that easily. The type of transactions also affect the market efficiency. For example, in over-the-counter markets, the information will not be available easily which makes them inefficient. The information should also be equally available to everyone. That’s why companies are required to disclose the same information to everyone.

Some markets may place restrictions on activities that impede market efficiency. Arbitrage is one such activity. Arbitrage involves taking advantage of price differences between markets. An arbitrageur will buy a security in a market where the price is low and sell it in the market where the price is high and make a risk-free profit. Arbitraging helps in price discovery and makes the markets more efficient. Some markets restrict short sale, which restricts arbitrage trading, which affects market efficiency.

The last factor affecting market efficiency is the transaction costs and other costs associated with trading and analysis. As long as these costs are high, the markets will be inefficient,

Based on the degree of information available, there are three forms of market efficiency. The weak- form of market efficiency states that the current stock prices fully reflect all the past market data. So, the past trading data is fully reflected in the stock prices and the trader cannot forecast the future stock prices based on the past stock prices.

The semi-strong form of market efficiency states that the current stock prices reflect all publicly available information including the past information. The Semi-strong form encompasses the weak-form.

The strong form of market efficiency states that the stock prices incorporate all the information available about the stock including the public and private information. So, if a market is strong form efficient, then even the traders with insider information cannot take advantage of their information to make abnormal profits.

Market Efficiency and Its Three Forms

A wind vane that moves with the slightest movement in breeze is a good representation of an efficient market. A market that quickly accepts and integrates any new information related to assets is called an informationally efficient market or efficient market. In an ideal efficient market the asset price will reflect all past and present information.

In the real world, markets lie somewhere between an efficient and inefficient market. There are several factors that affect the efficiency of a market. Market players like investment managers and analysts are always on the lookout for inefficiencies in the market because these present opportunities for profitable trading opportunities. An efficient market does not enable consistent, risk-adjusted returns and calls for a passive strategy. In a passive strategy a broad portfolio is held and has low transaction and information costs.

An inefficient market on the other hand requires an active strategy which will help in achieving superior risk adjusted returns. It is important therefore to recognize if a market is efficient or inefficient based on certain factors.

In an efficient market asset prices need to reflect information quickly. This is done through trades and the time frame for information assimilation in asset prices is done through this mechanism. The time required to execute these trades can therefore be used as a base value to understand how quickly the inefficiency is being exploited and therefore the time required for adjustment. This in turn helps assess the efficiency of the market. The shortest time taken to make a trade is the minimum time required to assimilate the information into an asset. Studies in the foreign exchange market and developed equity markets have pegged this time to be as low as a minute. If this time window allows several traders to make a profit with minimum risk the market is considered to be inefficient. Market efficiency therefore can be monitored and viewed over a period of time rather than just as a snapshot.

Another important criterion to assess efficient markets is to observe how the market reacts to unexpected or unanticipated information and how that is incorporated into asset prices. This is then reflected in the trades by analysts.

If they perceive that the risk to be now undertaken does not support the returns they will sell it or short it. Traders who believe otherwise will buy it. An efficient market will therefore see a revision of positions when new information is provided.

To understand this let us take the case of what happens when a bond issuer announces they are going to default on an upcoming interest payment. This is done just before the bond market opens. The media had been speculating this event. This was done based on the following events. Suppliers had been insisting on being paid on cash putting pressure on the company’s liquidity. The issuer was under severe financial duress and would not be in a position to make an upcoming interest payment. Finally despite not having options in the capital market, the issuer was seeking a working capital loan which would enable to meet operational expenses for nine months and make upcoming interest payments. Based on this information analysts opine that bond holders will recover $0.36 to $0.38 per dollar face value in the event of the issuer defaulting on the bond.

A highly efficient market would take cognizance and give priority to  the information that the issuer had failed in its negotiations for a line of credit from the bank. Further since the issuer had made an announcement that it would be failing in meeting its upcoming interest payment it would get reflected in the first trade prices after the market opens on the announcement day.

We will delve into the factors that determine the degree of efficiency of markets in the next article.

An Overview of Efficient Markets

<a title="An Overview of Efficient Markets" href="https://financetrain.com/an-overview-of-efficient-markets/">Efficient markets</a> assimilate information that gets reflected in trades. Any new information in efficient markets is adjusted quickly. In reality most markets are neither fully efficient nor fully inefficient. They demonstrate various degrees of efficiency along a continuum between the opposing points of efficiency and inefficiency. The asset prices better reflect information more quickly and accurately in an efficient market rather than an inefficient one. The varying degrees of efficiency vary across geography, time, and different types of markets.

In this article we will look at some of the factors that impact market efficiency.

Market Participants

The number of market participants is a key factor that influences market efficiency. Let us take the example of a relatively small (small-cap) but strong player that is not watched keenly in the market. A small cap analyst who has been keeping tabs on the company’s positive and promising profits and growth recommends a ‘buy’ on this share. The analyst also capitalizes on the fact that the company is relatively lesser known and is not being observed by larger players.

The positive operating profits information takes a while to trickle into the market. In the meantime the small cap analyst has bought shares at prices that do not fully reflect the worth of the company, i.e., at lower than value prices.

Six months later the company further puts forth its results which are good this time round as well. The forgone profit opportunities as a result of mispricing are better known to more market participants this time around, and a large number of shares are sought. This drives the prices of the stocks up thus better reflecting the true value of the share.

In a well traded market with more participants who follow market movements closely market inefficiency like mispricing of a share will quickly be corrected.

Chinese markets for instance restrict trading by foreigners. This reduces the potential for trading and accentuates market inefficiencies.

Availability of Information and Financial Disclosures

The New York Stock exchange, the stock markets of London and Japan offer information on listed companies and trading activity easily. Listed companies are followed by several analysts and therefore efficiency in these markets is high. It is generally much lower in lesser developed markets as one perhaps that is in an emerging market.

The type of market can also determine its level of efficiency. Several securities trade in certain kinds of markets like OTC (over the counter), money market instruments, currencies, swaps and forward markets. The information that is made available regarding these markets vary  and this impacts the level of efficiency of markets.

A market’s efficiency is determined at how successfully they can ensure a level playing field for different players big or small in the market. This is achieved by ensuring that all players have access to all information required to value securities. This includes prevention of insider trading. The SEC expects non-public information that it shares with some investors and marketers must be made public to all investors. If not such investors will have an unfair advantage when it comes to how much to buy or sell. A recent example of such is that of Rajat Gupta who has been found guilty of passing on insider information and tips after board meetings at Goldman Sachs to Raj Rajaratnam, head of a hedge fund. He is looking at 25 years in jail. Punishment for insider trading in USA is severe in order to deter any such instances.

Limits to <a href="https://financetrain.com/short-selling-and-stock-borrowing-costs/">Short Selling</a>

Arbitrage is an activity that increases market efficiency. Arbitrageurs tap into market inefficiencies to make riskless profits. These arbitrageurs are on the constant lookout for market inefficiencies. They look for opportunities where an asset is being traded at different prices. Prices that are adequate to make a neat profit by buying from the underpriced market and sell it in the market where it is valued higher. This results in price differences across markets disappear fast. Some of the limiting factors that can stop arbitrage from functioning as an important tool for market efficiency include lack of transparency in market prices, high transaction costs and operational inefficiencies.

Short selling is considered to be an impediment for arbitrage. In short selling an investor can sell a stock he does not own, by borrowing them from a broker with the promise to replace it at a later date. He will do this if he feels the share is overpriced. Theory suggests it is a method to increase market efficiency. Market players and regulators however feel short selling tends to magnify and can lead to the short sold stock to crash in the market. Studies point out that short selling can help in true price discovery.

The Cost to Acquire Information and Transactional Costs

Traders seek information on how to exploit market inefficiencies. Transaction costs can determine if arbitrage is undertaken. An arbitrageur will short the asset in the higher price market and buy it in the lower price market. If the price difference for the lowest arbitrage trade does not cover the transaction cost the arbitrageur will not conduct the trade. The bounds of arbitrage are usually high in illiquid markets.

Information Acquisition Costs: Efficient market trades are supposed to contain all relevant information. Yet analysts and traders spend a lot in acquiring information before making trades. The historical perspective is that a market is inefficient if active investing helps cover the cost of acquiring information. The current perspective varies in the sense that markets are considered inefficient if after deducting cost of acquiring information, active investing yields profits.

Market Efficiency: Influencers

Eugene Fama in 1970 introduced the forms of efficient markets in the Journal of Finance. Titled “Efficient Capital Markets: A Review of Theory and Empirical Work”, this seminal article outlines the capital markets. He states markets function in three formats:
<ul>
	<li>Weak</li>
	<li>Semi-strong</li>
	<li>Strong</li>
</ul>
The forms are described with respect to available information that is reflected in the price.

Weak form of market efficiency reflects past market data. Semi-strong format reflects past market data and public information. The strong format reflects in addition to past market data and public information, private information as well.

In an efficient market abnormal returns are defined as excess returns over expected returns given security risk and market return. It has been found though that investors do earn abnormal returns based on information available to them, a sign of an inefficient rather than an efficient market.

In a weak form of market, according to Fama, the security will reflect all past market data including historical prices as well as trading volume information. Securities in such a market already reflect historical data and cannot be extrapolated to show future prices. In weak form efficiency, trading rules will try to exploit historical trading data. If such a rule helps produce abnormal risk-adjusted returns after trading costs it contradicts.

Semi-strong format of efficient markets securities will reflect publicly available data such as financial reports, corporate investments etc. Since all publicly available data reflects in the prices, analyzing public data to identify either underpriced or overpriced stocks is not useful. Any new information that is available is quickly shown in stock prices, since this information is available to all parties.

A researcher wanting to assess a semi-strong market will conduct an event study. The researcher will identify a sample period and the companies that paid a special dividend in this period as well as the date of announcement. The expected return on the share for the event date will be calculated. The difference between actual and expected return is tabulated. Statistical tests are then run on this data to see if abnormal returns vary from zero. What this means is that like an efficient market the public information has reflected quickly on the stock prices. If however post the date of announcement abnormal returns are noted there exists trading opportunities. Developed securities market can be considered to be semi-strong efficient markets. The same is not true for markets in developing nations.

The strong form of efficient markets reflect both public and private data. An important inclusion is private data that is otherwise privy only to the company management. Insider trading is prohibited in many markets. It has however been seen that availability of non-public information can yield abnormal returns.

What therefore are the implications of the efficient market hypothesis?
<ul>
	<li>Securities markets are weak form efficient and traders cannot use past data to earn abnormal returns.</li>
</ul>
<ul>
	<li>Securities markets are semi-strong efficient in the sense that publicly available financial information is reflected quickly on securities prices.</li>
</ul>
<ul>
	<li>Securities markets are not strong form efficient as private information cannot be used to trade as per securities rules and regulations.</li>
</ul>
Let us look at these market formats with respect to fundamental analysis, technical analysis and portfolio management.

In fundamental analysis publicly available data is examined to estimate the intrinsic value of shares. Fundamental analysis helps in spreading value-related information and thus create a semi-strong efficient market.

In technical analysis past patterns are studied for possible abnormal returns. If yes, they reduce when they are exploited. Technical analysts who understand and use these patterns to their benefit help create and maintain a weak-form efficient market. Further abnormal returns cannot be booked since such opportunities would have been used already.

Portfolio managers therefore cannot beat the market if they are in the weak or semi-strong formats. However fund managers do not aim to beat the market but meet long-term financial objectives by creating portfolio that is diversified such that it takes into account the risk considerations and tax implications of the investor.

Types of Efficient Markets

<a title="Types of Efficient Markets" href="https://financetrain.com/types-of-efficient-markets/">Efficient markets</a> reflect any new information in the prices of the securities that are traded. However, there are from time to time anomalies in the system that leads to a mispricing of the securities. They are not one off phenomenon but a persistent pattern that buckles the tenants of an efficient market system. For an anomaly to be termed such it has to occur over a long period of time.

Typically researchers develop a hypothesis and test it against a set of data. However in testing market anomalies a process called data mining is conducted. In this method historical data is analyzed for any deviation in patterns and the recurrence of these patterns over a period of time is studied.

Market pricing anomalies can be classified into three broad groups. They are Time Series Anomalies. In this past data is reviewed to identify pricing anomalies. Cross sectional anomalies are arrived at by assessing a cross section of companies. Still other anomalies are identified using methods such as event studies.

Time Series Anomalies can be further categorized into two groups. They are calendar anomalies and momentum and over-reaction anomalies. Let us look at what they mean.

Calendar anomalies

Anomalies were noticed in the first five days of January of each year by a group of researchers in the 80s. Stock market returns during this time of the year far exceeded the rest of the year. This effect was termed January effect or turn of the year effect. This was not accompanied by any new news regarding stocks as the case should have been for an efficient market. A number of explanations have been given for this effect.

One explanation is that investors sell their loser stocks at the end of the year to off-set any capital gains. These loser stocks typically are highly volatile small cap stocks. This leads to a fall in the prices of such stocks which the investor then picks up early in January at attractive prices.

Another explanation attributes this anomaly to a kind of window dressing. Portfolio managers are expected to present their annual reports on December 31st. They drop their riskier stocks during December to make the portfolio look more stable. Then in January the risky stocks are picked back up to earn higher returns.

There are other calendar anomalies such as day of the week, turn of the month, weekend effect, holiday effect and time of the day effect. Most of these effects have stopped being anomalies over time as arbitrageurs have utilized these and the security prices have been readjusted.

In the turn of the month effect there is a spike in the returns at the end of the month and the first three trading days of the next month.

Returns tended to be negative and lower on Monday as compared to the averages of the four other days of the week. This was known as turn of the day effect.

In the weekend effect the returns were lower on an average on weekends rather than those on the weekdays. When the returns on the day prior to a market holidays were higher than other days it was known as the holiday effect.

Momentum and Over-reaction Anomalies

The impact of un-anticipated news on share prices was negative on the short term share price movements and such anomalies were classified under momentum anomalies. A study conducted by Werner DeBondt and Richard Thaler stated that stocks reacted negatively to unexpected news from that company in the short term. Even if the news were positive, since it was unexpected shares reacted badly. This effect was known as over-reaction effect. After studying this anomaly they came up with a method to pick stocks. They termed them as winner and loser stocks. They studied the returns of stocks in both the categories for a time period of three years. The loser stocks it was seen after the initial losses outperformed the market, while winner stocks underperformed the market.

If abnormal profits have been earned in stock markets using this method over a long period of time, it is a contradiction of the weak efficient market, since these profits have been made using historical data.

Pricing Anomalies: Calendar, Momentum and Overreaction Anomalies

Cross sectional anomalies can be categorized into two groups, namely, Value Effect and Size Effect.

Value Effect

Several studies in markets across the world have yielded the following results. Stocks with below average price-to-earnings and market-to-book ratios have consistently outperformed growth stocks over a period of time. This is a contradiction of the semi-strong efficient market form as financial disclosures are used to beat the market consistently.

Fama and French used a three factor model that takes into account the size of the company as measured by the market value of its equity and the company’s book value of equity divided by its market value of equity. This model unlike CAPM (Capital Asset Pricing Model) factors elements of risk which when applied takes the anomalies away.

Size Effect

One study observed that on a risk-adjusted basis small-cap equities out-performed large cap equities. This anomaly was not observed in further studies and was therefore disregarded.

Other anomalies that have been observed and documented include close-end investment fund discounts, returns on initial public offerings and the predictability of returns based on prior information.

Other Anomalies

Close-end investment fund discounts

A close ended fund issues a limited number of shares during one offering, thus fixing the market capitalization till a second offering is made. In theory these shares must trade at their net asset value or NAV. In practice they usually trade at a discount in the 4-10% band. Exceptions have been documented where they traded at a large premium or at deep discounts of 50%. One of the explanations for this quandary is tax liabilities. Pre-purchase liabilities and gains means the investor has little control over the losses or gains he incurs. Another explanation is illiquidity of these shares as compared to more liquid stocks that are traded publicly.

Both these explanations explain the discounts in part and not in entirety.

Earnings Surprise

Pricing anomalies studied in the context of adjustment of stock prices in relation to earnings announcement come under the purview of earning surprise.

Earnings surprise or an unexpected part of earnings that takes investors by surprise should result in a price increase of the stock. Studies have proved that while these earnings surprises have reflected in the stock prices, the actual adjustment has not always been as efficient. A major portion of the adjustment takes place prior to the surprise, but adjustments do take place post the announcement as well. Those with positive surprises have generally gone on to give good stock performances and those with negative surprises poor stock performances. Therefore the possibility of making abnormal profits based on stock surprises exist. Risk and transaction costs however are not truly accounted for in these studies and cannot be used with certainty as a method to earn abnormal profits.

Initial Public Offerings

Companies avail the services of investment banks in pricing and marketing of their shares in their first stock market foray. As the entrants are new, their selling prices are set low and tend to see an increase on the first day of trading.

Underpricing is the percentage difference between the issue price and closing price on the first day. An investor who has purchased at the offer price can make an abnormal profit by offloading their shares at closing prices. If the issue price is too high though and the prices at which they are traded on the first day are too low, losses can be incurred. In reality abnormal profits are not made since markets adjust quickly to the ‘true’ or real value.

Abnormal profits based on prior dividends

Market researchers state that equity returns are impacted by stock volatility, inflation, interest rates and dividend yields. This should indicate market inefficiency especially of weak form. This does not hold true though over a period of time. The relationship between stock prices and dividends has been found to vary from positive to negative from time to time.

Can these studies on pricing anomalies be exploited to make abnormal by the investor? Realistically, no. These studies do not truly show lacunae in market efficiency, but lacunae in the statistical methodologies used to identify the anomalies. There are best left as theory and not put in practice.

Pricing Anomalies: Cross Sectional Anomalies

‘Man is a rational being’ is a hypothesis that has been proved wrong several times over. Each person has their individual rationale in what they do and this is true in the sphere of investing as well. Referred to as cognitive biases the subject of behavioral finance attempts to understand how these biases affect investment decisions. Market and price models assume markets are rational. They also assume that this rationality is reflected in the intrinsic value of the security. Is there therefore room for abnormal profits when individuals move away from rationality?

Behavioral finance models make certain assumptions. We will look at a few of them.

Aversion to Loss

Investors are strongly averse to risk and will take them only if the expected returns are high and compensates them for the risk.

Daniel Kahneman and Amos Tversky came up with a study on how people react to risk called the Prospect Theory. The theory outlines how individuals react differently in undertaking risk for gains and when they concern losses.

Kahneman explains this with an example. A group of Princeton students

were asked to take a bet where if they tossed the coin and got heads they would lose $10, just how much would the researchers have to pay for the student to take the bet? The amount he says is about $125. If a ratio were to be put on how much individuals are averse to losses more than they like winning is put at about 2 to 3. This is seen in the manner in which they would invest as well.

In an interview with PBS, Kahneman states that individuals indicate similar patterns as they did 20 years ago. If changes have occurred they have in the sphere of institutions. You can watch and understand risk aversion in the words of Kahneman himself at <a href="http://www.youtube.com/watch?v=rZUylXXJbhE" target="_blank">http://www.youtube.com/watch?v=rZUylXXJbhE</a>

Overconfidence

On the other end of the spectrum, overconfidence is another characteristic used to explain pricing anomalies. Individuals who are overconfident will stop being rational and over-estimate their abilities to take risk and therefore take calls on securities that are not in their benefit. A group of such investors can lead to the security being mispriced. In the long run, prices will adjust but by then these over confident investors would have taken a hit on their investments. The issue to consider is the actual period of adjustment before markets return to equilibrium, as if it’s possible to predict market mispricing and use it to earn abnormal profits. This is particularly true of large companies, where over confidence occurs and the time of adjustment for new information is far slower.

How individuals take risks and therefore their trading choices are explained by several behavioral models.

Some of them are gamblers fallacy, mental accounting, conservatism, disposition effect, narrow framing and representativeness. All these theories point out that there is no homogeneity in the way they ascertain the price of the asset. This leads to them exhibiting different investing methods, which can explain pricing anomalies to some degree.
<ul>
	<li>Narrow Framing sees investors seeing issues in isolation.</li>
	<li>Disposition effect explains that investors tend to want to avoid mistakes rather than making gains.</li>
	<li>Conservatism is the model that states that many investors tend to react slowly to new information about an asset.</li>
	<li>Mental accounting sees individuals maintaining separate mental accounts of their investments, rather than taking an organic point of view.</li>
	<li>Gamblers fallacy highlights how if an investor is on a winning streak, he will tend to wrongly assume that the trend will continue and make investment assumptions accordingly.</li>
	<li>Representativeness refers to when investors use current trends to predict probability of outcomes.</li>
</ul>
Information Cascades

Behavioral finance uses its models to understand how individuals invest and how the group impacts their behavior as well. Humans like other animals like cows, goats tend to seek strength in numbers and look for signs within the group to invest. Recent examples of this behavior are the mortgage backed securities and the dotcom bubble. The pricing at the peak of these bubbles were not on account of fundamental strengths in the securities, but an irrational exuberance. The sense that ‘if everybody is investing in them so should I’ kicks into play. Once the bubble bursts and money is lost investors in retrospect wonder why they did what they did. This phenomenon is called herding.

Information cascading on the other hand is slightly less irrational. True here too market participants follow someone, but it is based on reported outcomes and data. If an investor is making picks based on an analysts findings and outcomes and an exchange of such information spreads wider and wider in the investment circle we say the information cascade is strong. It is a good mechanism where information is dissipated.

In conclusion it can be said that behavioral finance aims at understanding why investors invest the way they do and thereby market pricing anomalies. How do investors view risk and how do they make decisions. It tries to explain why the emotional tail wags the rational dog.

An Overview of Behavioral Finance

This quiz is a part of the CFA Level 1 reading 'Market Efficiency'. 

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