# Volume 19: The Efficient Market Hypothesis

### It's Why You (Probably) Can't Beat the Market

*“The stock market is a device for transferring money from the impatient to the patient,” – Warren Buffett*

As a society, we have decided to invest our time, our currency, and some of our greatest minds towards the task of beating the market. Teams of Ph. D’s sit in New York, Chicago, Greenwich and elsewhere, looking for any tiny edge they can exploit. They combine form a giant machine, taking in information, spitting out predictions for asset prices.

As our knowledge base becomes larger - satellite pictures of Iowa cornfields, micro-data on consumer spending, professional “Fed Watchers” – this machine is able to incorporate more information, faster. With all of this effort, we do a pretty good job; stocks, bonds, commodities and foreign exchange rates must cost just about what they are worth. But this, itself, is a problem. If you can only buy or sell something for what it’s worth, then there is no way to profit. If there were no way to profit, then all of this effort would be wasted. Something doesn’t add up.

This is the Efficient Market Hypothesis, and its paradox.

The Efficient Market Hypothesis is wrong. If you can figure out how and when it’s wrong, you’ll soon find yourself a billionaire.

What is the Efficient Market Hypothesis?

Do professional investors beat the market?

How does anybody make any money?

**What is the Efficient Market Hypothesis?**

Classical economics is the explanation of production, consumption and transfer of wealth. It predicts how much the price and quantity of apples will change after a weak harvest. It gives direction for how changes in tax policy will affect the economy.[1] It tackles the thorny issues involved when governments regulate the crossing of otherwise arbitrary lines, otherwise known as international trade.

As international capital markets became larger and more sophisticated in the early 20th century, we realized that financial assets don’t always follow the same economic rules as physical goods. To study these differences, Finance Theory began to forge its way as a separate discipline. The Efficient Market Hypothesis, or EMH, belongs to Finance Theory.[2]

In 1950, despite formal financial markets having existed for over 350 years, we still had little theoretical understanding of how assets were (or should be) priced.[3] We knew it had something to do with risk; investors demand higher expected returns for a garage-based start-up than for a U.S. Treasury Bond. But we knew that not all risk was worth of reward. Just because the casino game of roulette has massive risk doesn’t mean its return is better than other investments. We also knew that diversification was generally a good idea. As early as 1615, Sancho Panza told us that a wise man does not keep all his eggs in one basket. But that’s just about all we knew.[4]

A large, early step in the development of finance theory was **portfolio optimization**. Advanced by Harry Markowitz and others in the early 1950s, portfolio optimization uses correlation to increase returns without increasing risk. Holding a portfolio split between two assets generally has less risk than a portfolio holding only one.[5] Adding additional assets allows even better portfolios. Taking into account the entire investment universe, an optimal portfolio can be constructed for any desired amount of risk. Because this is a limit which theoretically can not be exceeded, these portfolios are called the **efficient frontier**.

*Figure 1 - The Efficient Frontier and Capital Allocation Line*

The next step towards understanding asset prices was the development of the **Capital Asset Pricing Model** (CAPM). Figure 1 shows the efficient frontier; however, you’ll see an additional point, representing the return possible from a risk-free portfolio. Investors can put any or all of their funds in this portfolio. A line starting at this point will be tangent to our efficient frontier at a single point, which we call the **tangency portfolio. **An investment of some of our assets in this tangency portfolio, with the rest in the risk-free asset, will outperform any other investment. Each investor can choose their own risk tolerance. The portfolios so described are on the **capital allocation line**, or CAL.[6]

But, therein lies the rub. Taken to an illogical extreme, all an investor needs to do is identify their personal tolerance for risk, feed it into an algorithm, and invest in the resulting portfolio. These investments won’t be based on whether a company is well run, or if people actually want its products, but rather market parameters like volatility and correlation.[7] The results of the algorithm will be optimized, in that, for a given level of risk, the portfolio will have an expected return greater than or equal to any other portfolio. This is a serious issue for mutual fund managers, asset allocators, and other who charge millions to advise clients on portfolio construction.

The Capital Asset Pricing Model and Capital Allocation Line are theoretical constructs; there is no perfect algorithm for real-world markets. But, even if