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The Effectiveness of Financial Derivatives as Prediction Markets.

I was intrigued by the discussions in class on how odds in markets such as horse race betting may have predictive value. This is because the odds are a form of wisdom of the masses, as it is determined by the weighted average of beliefs of those who participate in the market. Furthermore, the reminder at the end of class that we should not participate in these markets if we do not know what we are doing reminded me of a form of prediction markets used in real economic and finance scenarios: financial derivatives. In another class, we discussed that futures markets are commonly used by farmers to predict the price of agricultural products. This led me to ponder, how effective is the market financial derivatives as a prediction market?

The main advantages of using financial derivatives as a prediction market are that they quickly react to new information, are largely efficient in terms of liquidity and access, and that they are impervious to manipulation (Snowberg et al, 2012). The third advantage is because that in prediction markets, as we have learned in class, the optimal way to maximize log payoff is to bet your beliefs, so attempts to sway the strike prices of financial derivatives by not betting one’s beliefs are futile, because they will result in lower expected payoffs. As a result, some markets financial derivatives serve as excellent prediction markets that frequently outperform professional forecasters and polls. It is clear that prediction markets will outperform polls, because in polls, the opinions of the most qualified and least qualified predictor is equal, but in prediction markets, those who back their opinions with the most money are often the most qualified thus skewing the odds of the prediction market more towards their beliefs. For instance, economic derivatives ran by banks like Goldman Sachs and Deutsche Bank allow people to bet on what they believe macroeconomic outcomes such as unemployment claims will be and pay out to the people who get it right. Commonly the distribution of “bets” on these financial derivatives paints a more accurate picture of what macroeconomic outcomes will be compared to the forecasts of economists (Snowberg et al, 2012), as those who forecast successfully will have more money in the future to make forecasts as well, and those who lose money are likely to leave the market.

On the other hand, the effectiveness of using financial derivatives as prediction markets has several limitations. Firstly, there is a conflict in the basic assumptions of a prediction market. In class, we assume everyone wishes to maximize their payoffs, but that is not the case in financial derivatives, as many investors buy or sell derivatives to hedge for other risks and do not intend on gaining payoffs. These participants in the financial derivatives market will lead to inaccurate predictions, as the purpose of the market is not just solely speculation anymore. Volume and liquidity is another factor that limits the effectiveness of financial derivatives. Just like in every prediction market, if there are only a few participants, it is unlikely for there to be any meaningful and persistent predictions, as the “wisdom of the crowd” does not exist. Financial derivatives require there to be enough widespread interest, the actual underlying subject to be significant, and enough money in the market for it to function (Cowen, 2021).  However, this issue is rather contrived, considering that if there is not enough interest in the topic for a prediction market to form around it, the topic is probably not important enough to warrant a need for predictions in the first place.

Overall, financial derivatives are an interesting form of real world prediction markets. They can often be more accurate than professional forecasters, but there are several limitations that prevent them from operating like a prediction market would in theory.

 

Reference List

Snowberg, E., Wolfers, J., & Zitzewitz, E. (2012). NBER WORKING PAPER SERIES PREDICTION MARKETS FOR ECONOMIC FORECASTING. http://www.nber.org/papers/w18222
Cowen, T. (2021). Predicting the Future of Prediction Markets. Bloomberg.com. Retrieved 22 November 2021, from https://www.bloomberg.com/opinion/articles/2021-03-04/predicting-the-future-of-prediction-markets.

 

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