Why It Is Possible to Make Above Average Returns – Even in Efficient Markets

There is a well-known hypothesis in financial economics, called the Efficient Market Hypothesis (EMH), that spawns a lot of debate. The EMH states that financial markets are ‘informationally efficient’. In other words: a financial asset’s market price always incorporates and reflects all available relevant information. Hence no investor can consistently use such information to find stocks that earn him above average returns. After all: such information is already reflected in the asset’s price; so if there is a lot of ‘positive’ information about the company, the stock’s market price will have increased, and if there’s a lot of ‘negative’ information, the price will have decreased.

I want to make an argument why, even if the EMH holds, it might still be possible to consistently earn above average returns on investments. The argument is basically very simple. Let’s first recall the EMH. We know that an efficient market is a market in which the price of a financial asset (let’s say a stock) always incorporates and reflects all available information. Hence, you cannot benefit from the set of available information in such a way that you can consistently earn above average returns on investing in the asset – or any asset for that matter. But does it follow from this that you cannot consistently achieve above average returns? I don’t think so.

Because what if you are consistently better than other investors in anticipating future information? Then, even though the stock’s market price reflects all available information, you can utilize this anticipated future information to decide whether to buy or sell a stock. And if you can anticipate future information (which is information not yet incorporated and reflected in the stock’s price) better than the average investor, then you can earn above average returns, time after time.

This all sounds pretty abstract. So let’s look an example. Suppose there is a stock of a company that produces wind turbines – call it ‘stock A’. Furthermore, let’s suppose that at this point in time investors are on average not confident about wind energy’s potential. They might think that the cost of producing wind energy is too high, its profits depend solely on the current regulation, or that it will still take a long time before our fossil fuels are depleted, making the switch to wind energy not urgent yet. Given these considerations the stock trades at a price of – let’s say – 10. Let’s assume that this price indeed incorporates and reflects all available information – such as information contained in annual reports, expert analyses etc. Hence it seems reasonable to say that you cannot consistently earn above average returns on this stock by utilizing only this pool of existing information.

But what if you believe that, given the ever increasing energy consumption and ever decreasing level of fossil fuels, society has in the middle-long term no choice but to turn to alternative forms of energy – forms such as wind energy? If you think this is true, then you can anticipate that any future information about the wind-turbine producer will be positive – at least more positive than today’s information is. You can anticipate that the future information will show an increase in the firm’s revenues, or – for example, in case the firm is close to bankruptcy but you know that its managers don’t profit from a bankruptcy – a decrease in costs. Given that the market is efficient, you know that at the time this information will become public, the market price of the stock will increase to reflect this information, to a price of let’s say 20. If you can anticipate such future information consistently, then you can anticipate the future stock price consistently, allowing you to consistently earn above average returns – despite the perfectly efficient market.

An equivalent way to look at this matter is to say that you take into account more information than the average investor in calculating the stock’s fair value. Let’s say that you are doing a net present value calculation, and you have estimated the firm’s future cash flows. In case of stock A, investors used estimated cash flows that lead them to a fair value of 10. However, given your anticipation of future information, you estimate these cash flows to be higher – leading you to a higher valuation of the stock. Again: if you can consistently anticipate future information better than the average investor, you can consistently earn above average returns – even in an efficient market.

Why You Should Always Do What You’re Afraid To Do

Ralph Waldo Emerson said: ‘Always do what you are afraid to do.’ And this rule seems a reasonably good guide for self-improvement. Because it turns out that people are often afraid to do the things they are least familiar with. Whether is approaching a girl in a club, giving a speech to 50 people, or setting up a business: things make us feel anxious because we have little experience doing it. In such cases the anxiety often pushes you away from doing the thing, hence still leaving you clueless about what you will experience, or even further increasing your anxiety.

But there is something odd here: because the things that you are least familiar with provide you with the biggest opportunities to learn. After all: if you are not familiar with something, it means that you have little knowledge of it. It means that you are still at the start of the learning curve; that the ‘marginal utility per unit of experience’ is very high. Therefore, being afraid of something might be a damn good indicator that there is a lot of potential for you to learn about the thing. Hence it might be wise to always do what you are afraid to do.

This reasoning seems cogent, doesn’t it? But there is one problem with Emerson’s rule…it is not always true. There are cases in which fear should actually push you away from doing something – not pull you into doing something. Think about the fear of jumping of a building, or the fear of approaching a tiger. Given that you want to improve yourself, it seems unwise to jump of a building, or to be ripped to pieces by an angry tiger.

So the best we can do is to say that the rule is a heuristic: a guide in life, that points you – in most cases – to the areas in life where you can learn a lot. But how do you know in what cases you should act upon the rule, and in what cases you should realize that doing so might actually put you in danger? I think we have to distinguish between two kinds of fear here: socially conditioned fears and innate fears. The first are things such as being afraid to start a business or to make a move on a girl*: we have been told, or we have experienced at first hand, that such endeavours might cause emotional pain – even though they are not inherently dangerous. Innate fears, on the other hand, are things such as being afraid of tigers, which seems like a reasonable fear. Tigers are dangerous; despite your experiences with one. In other words: it seems that innate fears try to protect us from real threats, while socially conditioned fears don’t always do so.

Taking this into account, ‘Always do what you are afraid of’ is likely to make you learn a lot.

But what do you think?

*it might be true that socially conditioned fears are grounded in biology, hence being innate. If we take evolutionary psychology seriously, for example, it might be true that the fear to approach women is in fact innate. Hence there seems to be a continuum from innate to socially conditioned fears; not a categorical difference.