Market Efficiency: Influencers

Efficient markets 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 [Short Selling](

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.

Related Downloads

Related Quizzes

Market Efficiency
Finance Train Premium
Accelerate your finance career with cutting-edge data skills.
Join Finance Train Premium for unlimited access to a growing library of ebooks, projects and code examples covering financial modeling, data analysis, data science, machine learning, algorithmic trading strategies, and more applied to real-world finance scenarios.

Free Guides - Getting Started with R and Python

Enter your name and email address below and we will email you the guides for R programming and Python.

Saylient AI Logo

Accelerate your finance career with cutting-edge data skills.

Join Finance Train Premium for unlimited access to a growing library of ebooks, projects and code examples covering financial modeling, data analysis, data science, machine learning, algorithmic trading strategies, and more applied to real-world finance scenarios.