Efficient markets. Business schools spend entire semesters trying to teach their undergrads to understand this concept, and they still mostly fail. But I’m going to teach it to you here.
Imagine there is a company that runs amusement parks. They make an entirely predictable profit year in and year out. There is nothing surprising about how well they do financially. Everybody loves their parks and always will. They are only open in the summers.
If this company were publicly trading their stock, it would be tempting to think that you could buy their stock in April, just before they start to make money, and sell it in September, before they hibernate for the winter.
However, because everybody knows that they only operate in the summer, the price of their stock is not going to go down in the winter when they make no profit, because it is not a surprise. They are also not going to have their stock increase in price in the summer because they are making money, because that’s what everyone expects them to do.
Sticking to my Tesla theme for examples: at time of writing, Tesla’s market cap is $53 billion. General Motors’ market cap is $55 billion. What can we take away from this information? More or less, we can infer that the market believes the expected value of Tesla as a company is equal to the expected value of GM. Now, perhaps Tesla is riskier, and actually the expected value is higher than GM’s, but the current price is lower because we need a higher expected return to be willing to take on that risk.
However, at the very least, we can learn that if what we personally believe the outcome will be is that Tesla will become just like GM (no small feat from here, since GM sells 10 million cars every year, and Tesla has sold about 300,000 cars in their existence), we should probably not think Tesla is a particularly attractive stock (unless we think both GM and Tesla are very attractive, but you get the point).
To think Tesla is a very attractive stock relative to GM, we have to believe they will be a more profitable company than GM going forward.
Back when Tesla was a $5 billion company, this wouldn’t necessarily be the case. You could believe that Tesla was bound to become about half the size of GM, and that it would make a very handsome investment indeed.
It is very important to understand how the expectations of the market can be inferred by the current price. And there is another angle of the efficient markets hypothesis!
When news comes out, often people are tempted to sell their stock if it is bad news or buy a stock if it is good news. They are overlooking a key part of how efficient markets work.
Let us say that Tesla is trading at $300 per share.. If great news about Tesla comes out, pretend Uber has ordered 1 million Teslas asap for their automated car project, should I rush to my trading app and buy Tesla?
Let’s talk about what happens the moment before and the moment after that news comes out.
The moment before Tesla announces the great results about the Uber deal (and often these happen when markets are closed), shares are trading hands at $300 per share. The moment after the deal is announced, shares will likely be trading higher. All people with outstanding orders to sell their Tesla stock at $310 per share will likely cancel those standing orders and move the price at which they will sell up.
So at 3:59PM, right before the market closes and before the information is known, Tesla is trading at $300. The deal is announced at 6PM, and by 9:31 the next morning, trades are happening at $330 per share. There need not be any trades anywhere between $300 and $330. If everybody agrees what this deal will do for Tesla as a company, no opportunity is created to buy or sell the stock and make a quick buck.
If you understand these two ideas, that market expectations can be found in a price (at least an approximation of expectations), and that if information is known publicly, that is does not create an opportunity for arbitrage, congratulations, you now have a better understanding of efficient markets than most finance majors.