As you probably know, derivatives trading is a multibillion dollar industry, both online and offline. Derivatives trading attracts all sorts of traders, from the casual weekend wager on the favorite index on Friday afternoon to those that become experts or even professionals at derivatives trading. Despite the size of this industry, until recently there has not been a lot of significant research on how to make the right bet. In other words, is there a real strategy that one who wants to wager on a trading event can use? Or is it really all up to the luck of the draw?

You may have noticed that we are literally swimming in data lately. If you want to find out any detail, no matter how minute, about a scrip, chances are that data is available somewhere. Yes, there may be a price attached to some data, but the information is there somewhere. Yet, the availability of all this data might be masking the real problem.

Here is what you may not know, the other side of the story, the real truth about all this information. Maybe you don’t actually need all that data, all those detailed analytical reports and projections after all. Yes, this may sound like heresy to some in the derivatives trading world, but you will want to pay real close attention to the next few lines here.

In fact, recent research by Song-Oh Yoon and colleagues at the Korea University Business School suggests that when you zero in on the details of a team or event (e.g., RBIs, unforced errors, home runs), you may weigh one of those details too heavily. For example, you might consider the number of games won by a team in a recent streak, and lose sight of the total games won this season. As a result, your judgment of the likely winner of the game is skewed, and you are less accurate in predicting the outcome of the game than someone who takes a big picture approach. In other words, it is easy to lose sight of the forest for the trees.

Yoon and his research team explored the optimal process of prediction in a series of studies examining bets made on soccer matches and baseball games. In their first study, they reviewed more than one billion (yes, billion) bets placed in 2008-2010 through Korea’s largest sports-betting company, “Sports ToTo.” They characterized the bets in one of two ways: (a) bets that involved a general prediction (i.e., win or lose), and (b) bets that involved a specific prediction (i.e., a precise score). Critically, they wanted to know which type of bet was more likely to result in an accurate prediction of the overall winner. Despite the fact that the specific bets were arguably more difficult and involved greater effort than general bets, they led to diminished success in predicting the global outcome of the game (i.e., which team won). This disadvantage was especially pronounced for games in which the favored team won.

These findings suggest that adopting a holistic approach when predicting outcomes, even for multi-faceted events like sporting competitions, may be more effective than dwelling in the details. However, because these findings reflect performance in a natural setting, they are open to alternative interpretations. For example, different kinds of people (e.g., risk-averse versus risk-seeking) may be more prone to placing different kinds of bets (e.g., general versus specific). In addition, different opportunities for reward may influence betting behavior, thus encouraging those making specific bets to take risks on unlikely outcomes. To control for these factors, Yoon’s team examined betting behavior in a controlled laboratory paradigm.

In three different experiments, participants were asked to make predictions about upcoming sporting events. In each study, half of the participants were randomly selected to make general win/lose predictions, while the other half were asked to make specific score predictions. The dependent measure was the same for both groups: Could they predict the winners?

The pattern of performance across the three studies was remarkably consistent: Participants who made general win/lose predictions were reliably better at projecting the winners of the sporting events than those who made specific score predictions. This advantage was evident regardless of whether reward opportunities were relative (i.e., only the participant with the highest overall performance received cash) or individual (participants received cash for every correct prediction).

Notably, experts did outperform novices. Nonetheless, even experts were reliably better in predicting winners when making general bets than when making specific bets. It seems that even in cases where greater knowledge may offer an advantage, the act of focusing on that knowledge can disrupt decision-making. Thus, while a lifelong baseball fan is more likely to pick the winning team than someone who has never watched a game, for either person a quick prediction about the winner is likely to be more accurate than one that follows deep reflection.

Yoon’s team confirmed this notion by assessing the kinds of information participants were using to make their predictions. As you might expect, those assigned to the general win/lose group reported relying on global assessments (e.g., overall impression of the teams, performance of the teams in years past) to a greater extent than those assigned to the specific score group. In addition, reliance on global information significantly predicted success for all participants. Even for those in the specific score group, use of detailed knowledge (e.g., strength of the defense, coaching talent) was not associated with better performance, while use of global information was.

These data align with lessons learned from research on basic personal decisions. Whether choosing a jelly bean flavor, rating the attractiveness of a face, or selecting a poster to hang in a room, people are more satisfied with their selection and less likely to change their minds when they make their decisions quickly, without systematically analyzing their options or mulling over the reasons for their choice. The advice is thus the same whether considering complex scenarios or simple situations: Don’t overthink it.

This research goes on to indicate that by focusing on minute details, a trader may lose sight of the big picture. Here is an easy to understand illustration, straight from their research findings. Those who wager on simple uptrend/downtrend scenarios using a pre-calculated stop, significantly win more than those who wager on specific target levels.

Bottom line: Don’t get lost in the details. The ‘gut’ feeling you have about a specific trade is more likely to be a winner than bundles of pages of statistics.

( Loosely based on an article published by Scientific American )

 

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