“Ships will sail around the world but the Flat Earth Society will flourish. There will continue to be wide discrepancies between price and value in the marketplace, and those who read their Graham & Dodd will continue to prosper.” – Warren Buffett.
Astronomists can predict the motion of the planets and the stars with incredible accuracy thousands of years into the future, but try to estimate the level of the ASX200 next year, and you’ll get as many opinions as you have analysts. A 2012 study of more than 11,000 analysts from 41 countries by the University of Waterloo and Boston College found that target price predictions were accurate only to within 18% for a 3-month horizon, and 30% for a 12 month horizon - hardly the type of accuracy necessary to launch a rocket to the moon and back. Why, when our predictions come to the world of finance, are we seemingly in the dark?
In the realm of science, causality reigns supreme. Reproducibility - the ability of an entire experiment or study to be reproduced - is one of the main principles of the scientific method. It relies on the Ceteris Paribus principle (where all other variables are held constant), which typically requires some sort of controlled environment to achieve, such as laboratory conditions. Given enough information in such an environment, the outcome from a series of physical events is able to be predicted with great accuracy.
Finance students, on the other hand, are taught that share prices are inherently unpredictable; that they follow a Random Walk. This unpredictability is said to arise out of the tenets of Samuelson and Fama’s Efficient Market Hypothesis, whereby markets are informationally efficient. The theory states that in a strong-form efficient market, all relevant information is already incorporated into share prices and thus the only information left to move prices is new, and by definition, unpredictable information. It is thus the incorporation of this unpredictable information into share prices as it comes to light which results in the random movement of prices.
However, there is ample evidence that the market is not strong-form efficient (which would require all relevant information to be instantly reflected in prices). Every case of insider trading proves that there is information which is not available to the public which is yet to be reflected in share prices. And as for instantaneous incorporation of news into prices, there is evidence of sluggish price response to earnings announcements. Evidence of price momentum up to 90 days after company announcements shown by Rendleman, Jones and Latane in 1982, suggests that the market is not even entirely semi-strong form efficient (whereby all publicly known information is quickly incorporated into prices).
So if the market is not totally efficient, at least in the strong-form case, this would imply that share price movements can be predicted to a degree. For instance, the executive making an announcement of unexpected windfall gains to the market should be confident that the company’s share price is likely to rise afterwards as a result – he is merely constrained by insider trading laws from acting on this information. Thus, legal barriers such as insider trading laws create asymmetric information in the market place (which may lead to the deviation of asset prices from their true value), but they are by no means its only cause.
Michael Lewis, in his several of his popular books, exposes in great detail how some of the major market players like investment banks actively try to create market opacity and information asymmetry.
In Liar’s Poker (1989) Lewis details how Over-the-counter (OTC), rather than exchange-based trading in fixed-income securities (bonds) allowed Salomon Brothers and other investment banks to earn obscene profits at the expense of unwitting clients.
In The Big Short (2010) he investigates how some investment banks (in particular Goldman Sachs) were able to impinge upon the independence of credit-ratings agencies, allowing them to knowingly securitise and re-sell toxic Collateralised Debt Obligations (CDOs) at AAA-rated prices, reaping billions in profit (and coincidently allowing several savvy investors to place huge short-bets on their eventual collapse via Credit Default Swaps (CDSs) at fantastic odds).
In his latest exposé, Flash Boys (2014), Lewis reveals how High Frequency traders pay investment banks for the privilege of processing client orders in their so called ‘Dark Pools’ (private exchanges). While the lack of transparency in Dark Pools allows block trading by institutional investors not wishing to impact market prices with their large orders, it also provides the perfect environment for predatory trading practices by High-Frequency Traders (HFTs), and creates an inherent conflict of interest for the investment banks (who are in the pay of the HFTs to the detriment of their clients).
It is clear from the examples above that there is a lot of money to be made from information asymmetry in the market. If the market was truly strong form efficient, there would legitimately be no way of consistently earning abnormal returns, as prices would always reflect underlying value.
For instance, if subprime CDOs had been rated correctly and priced for the junk that they were in the years leading up to the GFC, it is logical to think that the severity of the ensuing crisis would have been greatly reduced, or perhaps even averted all together. Who in their right minds would have written Credit Default Swaps (insurance against default) on subprime CDOs for the measly premiums that AIG did? Lewis described it as selling discount fire-insurance on a house that was already ablaze.
While there were a small number of investors who could see that the proverbial house was on fire, and loaded up on the cheap insurance, most market players relied on the ratings of Moody’s and Standard and Poor’s. Unfortunately, these key agencies had significant conflicts of interest, whereby they rated their client’s (the investment banks) products for a fee. Also, due to the intentionally complex structuring of the products, they were heavily reliant on risk models of the investment banks, who had a vested interest in minimising the apparent risk (and therefore maximising the price) of the products. Thus, market prices were able to deviate significantly from underlying value. When the risk had become too obvious to hide and was finally priced-in by the market, the impact on the financial system was dire.
Alas, it would appear that the severity of the GFC was made magnified in part by intentional obfuscation by market players.
The real world is far from a laboratory environment. There is much information that we do not know, and many external factors that we have no control over. While the Efficient Market Hypothesis and the notion of random-walk share prices enjoy strong academic support, it is clear that the market is not totally efficient. Information asymmetry creates avenues for market exploitation, and thus some industry players try to foster opacity and complexity of market products and the market itself, in the pursuit of abnormal returns. Although the law of cause and effect is surely as much at work in the financial markets as in a science lab, it is the many unknown factors present in the market, both external and created from within, which lead to pricing inaccuracy and contribute to the formation of financial black swans.