Tag Archives: Stock market

Twitter vs. Tweeter and the Efficient-Market Hypothesis

This past Friday, I didn’t spend much time in front of the computer, but when I happened to pop onto Twitter to see if there was any news, I noticed a couple of tweets that were rather alarming:

Some folks may look at that and laugh or think it’s funny. I don’t. I think it’s embarrassing. First, I’m hoping that “investors” doesn’t necessarily mean people who manage other people’s money. If that’s the case, I would be very sorry for those people who happened to have someone managing their money that didn’t know the different between Twitter and Tweeter. Yes, I realize they’re very close, but when you’re investing money, don’t you want to be sure you know what you’re doing? Second, how can this mistake even be happening? I could see maybe a few people making this mistake, but for the stock to be up 489%? I wonder if maybe much of that extra trading was people realizing that other people think that it’s the Twitter stock, so they start buying the stock.

That last point really doesn’t make sense, though, because Twitter’s IPO just went public.

Another disheartening thing to think about as a result of Tweeter is the efficient-market hypothesis. This is a fancy way of saying that the stock market (or financial markets) should have the most current information. Meaning, if someone hears good news about company X, they’ll begin to buy that stock (which will make the stock rise and more people will hear the news and the stock will rise some more). This process continues until, theoretically speaking, the stock has reached the price that people are no longer willing to continue buying the stock.

Well, if we think about what happened on Friday, it certainly blows the efficient-market hypothesis out of the water. So, I ask again — how could so many people get that wrong?

 

Don’t Fall for the Gambler’s Fallacy: List of Biases in Judgment and Decision-Making, Part 7

A little later in the day than I would have liked, but today’s cognitive bias is the gambler’s fallacy. The bias gets its name from, as you’d expect, gambling. The easiest example to think of is when you’re flipping a coin. If you flip a coin 4 times and each of those 4 times the coin turned up heads, you’d expect the coin to turn up tails on the next (or at least have a higher chance of turning over tails), right? WRONG!

The odds are exactly the same on the 5th turn as the 6th turn as the 66th turn as the 11,024th turn. Why? Because the two instances of flipping the coin are independent events. (Note: we’re ignoring, for the time being, any effects that quantum reality might have on a given event in the past and the future.) So, every time you flip a coin, that’s an independent event — unaffected by earlier events.

Another important example is the reverse fallacy. That is, if we think that heads are “hot” because it’s been flipped a number of time, thinking that there’s a better chance that heads will be flipped is also a fallacy. Again, this is an independent event — unaffected by previous events.

This fallacy is so named because there’s a famous example of the gambler’s fallacy happening at the Monte Carlo Casino where, on roulette, black came up 26 times in a row. A number of gamblers reasoned that red would come up because there had been such an unlikely number of blacks that came up in a row. As the story goes, they lost millions.

Other examples of the gambler’s fallacy:

  • Childbirth: “we’ve had 3 boys, so we’re going to have a girl now…”
  • Lottery: “I’ve lost 3,000 times, so I’m due for a win…”
  • Sports: “Player X is playing really well, they’re bound to start playing bad…”
  • Stock market: “Stock X has had 7 straight down days, so it’s bound to go up on this next trading day…”

Ways for Avoiding the Gambler’s Fallacy

1) Independent Events vs. Dependent Events

The biggest way to avoid the gambler’s fallacy is to understand the difference between an independent event and a dependent event. In the classic example, the odds of a coin landing on heads or tails is — negligibly — 50/50 (I say negligibly because there are those who contend that the “heads side” weighs more and thus gives it a slight advantage). An example of a dependent event would be picking cards from a deck. There are 52 cards in a deck and if you pick one card without replacing it, your odds of picking one of the other 51 cards increases (ever so slightly).

If you liked this post, you might like one of the other posts in this series: