7.4 Evidence of Market Efficiency

 7.4 Evidence of Market Efficiency

Sophisticated statistical analyses of stock and other securities prices indicate that they follow a “random walk.” 

If securities prices in efficient markets are not random, and determined by fundamentals, particularly interest rate, inflation, and profit expectations. Why is random is their direction, up or down, in the next period?

That’s because relevant news cannot be systematically predicted. (If it could, it wouldn’t be news.) 

So-called technical analysis, the attempt to predict future stock prices based on their past behavior, is therefore largely a chimera. On average, technical analysts do not outperform the market. 

Three types of market efficiency: weak, semi-strong, and strong. Today, most financial markets appear to be semistrong at best.

In every age, financial markets tend to be more efficient than real estate markets, commodities markets, labor, and many services markets because financial instruments have a very high value compared to their weight, uniform quality, and little subject to wastage.

Futures markets have arisen to make commodities markets more efficient. 

Mortgage markets, also help to improve the efficiency of real estate markets.

Labor and services markets are the least efficient of all. People won’t or can’t move to their highest-valued uses; they adapt very slowly to technology changes; and regulations imposed by governments and others by labor unions, limit their flexibility on the job. 

Markets for education, healthcare, and custom construction services are also highly inefficient due to high levels of asymmetric information.

Many legitimate companies try to sell information and advice to investors. The value of that information and advice, however, may be limited. 

Even if the research is unbiased and good, by the time the newsletter reaches you, even if it is electronic, the market has probably already priced the information, so there will be no above-market profit opportunities remaining to exploit.

Only one investment advice newsletter, Value Line Survey (VLS), has consistently provided advice that leads to abnormally high risk-adjusted returns.

It isn’t clear if VLS has deeper insights into the market, if it has simply gotten lucky, or if its mystique has made its predictions a self-fulfilling prophecy: investors believe that it picks super stocks, so they buy its recommendations, driving prices up, just as it predicted! 

January Effect, the predictable rise in stock prices that for many years occurred each January until its existence was recognized and publicized. 

Financial securities, including stocks, tend to overshoot when there is unexpected bad news. After a huge initial drop, the price often meanders back upward over a period of several weeks. This suggests that investors should buy soon after bad news hits, then sell at a higher price a few weeks later. 

Sometimes, prices seem to adjust only slowly to news, even highly specific announcements about corporate profit expectations. That suggests that investors could earn above-market returns by buying immediately on good news and

selling after a few weeks when the price catches up to the news. 

The small-firm effect, returns on smaller companies, are abnormally large. Why then don’t investors flock to such companies, driving their stock prices up until the outsized returns disappear? Some suspect that the companies are riskier than researchers believe. 

The most important example of financial market inefficiencies is so-called asset bubbles or manias.

Periodically, market prices soar far beyond what the fundamentals suggest they should. During stock market manias, like the dot-com bubble of the late 1990s, investors apparently popped sanguine values forg into models like the Gordon growth model.

Our brains are pretty scrambled, especially when it comes to

probabilities and percentages. 

Behavioral finance uses insights from evolutionary psychology, anthropology, sociology, the

neurosciences, and psychology to try to unravel how the human brain functions in areas related to finance. [10] For example, many people are averse to short selling, selling (or borrowing and then selling) a stock that appears overvalued with the expectation of buying it back later at a lower price.

Human foible is that we tend to be overly confident in our own judgments. Many actually believe that they are smarter than the markets in which they trade.

Another source of inefficiency in financial markets is asymmetric information, when one party to a transaction has better information than the other.

Greater transparency and more fervent attempts to overcome the natural limitations of human rationality would help to move the markets closer to strong form efficiency.

References

Wright, R.E. & Quadrini, V. (2009). Money and Banking. Saylor Foundation. Licensed under

      Creative Commons Attribution-NonCommercial-ShareAlike CC BY-NC-SA 3.0 license.  

      Available from: https://www.saylor.org/site/textbooks/Money%20and%20Banking.pdf