Time Framing Bias: What Does This Notion Mean?

The process of betting is affected by numerous biases and psychological phenomena that make ordinary gamblers take wrong decisions and lose their money. In fact, all the bettors are periodically subject to some of them, but it is within the power of professional punters only to withstand them. The key moment here is to know and understand these phenomena. Only in this case, you will be able to evaluate the situation and save your bankroll. Thus, the given article describes such phenomenon as time framing bias.

Time Framing Bias Explained

This phenomenon denotes a situation when someone avoids taking a single bet because it seems to be risky even despite the fact that the expected value (EV) is really positive. So, the bias can be found in those areas where data tend to change quickly and unexpectedly. The best example here is represented by financial markets. It was noticed, that the more often you check the market, the higher chances you have to notice the absence of any real income. In this case, narrow time frames make you believe that your asset will not be beneficial.

The perfect example can be found in the book Fooled By Randomness by Nassim Nicholas Taleb. In his book, the author introduces a situation with a 15% return portfolio of stocks. If the trader checks the portfolio every second, the winning probability will be a bit more than 50%. However, if we increase a time frame to one year, the given probability will be about 90%. The second scenario looks much more attractive, does not it?

Time Framing in the Betting Industry

The phenomenon of time framing bias is not unknown in the betting industry, too. In order to better understand the general principles of this bias, let us consider an actual example with a single coin toss. When people are offered to play a game where heads will result in losing $100 and tails will generate $200, the majority of them object this opportunity. This is what is commonly known as risk aversion. In this case, people tend to focus on a negative scenario neglecting the positive EV of $50.

Scientists explain that ordinary people evaluate losing $1 twice bigger in comparison with winning $1. With this in mind, the EV for the example above will be 0, which explains a hostile approach to the offer.

At the same time, if people are offered the same bet but consisting of two coin tosses, the EV will change a bit. In this case, the Expected Value will be $50 including the loss overvaluation. This situation seems to be more attractive in comparison with one described above.

Even with this in mind, the loss of fear remains stable and powerful, but you should understand that every additional coin toss will respectively decrease the fear and increase the winning probability. To explain, if the same people are offered the same bet based on 100 coin tosses, many of them will agree. According to the calculations made, the Expected Value will be $5,000, while the chance of losing any money will be approximately estimated as 1 in 60,000. However, you should understand that this unbelievable result will be impossible to achieve if you are not bent on accepting the first risky bet.

Conclusion

The main message of the given article is to not evaluate your possible perspectives on the basis of a single and isolated aspect. The time framing bias makes us believe that we will not achieve the positive result even in those situations when the winning probability does exist.