Christian Slamka

On the Forecast Accuracy of Sports Prediction Markets

Accurate forecasts are essential in many areas such as business and sports forecasting. Prediction markets are a promising approach for forecasting future events and are increasingly used to aggregate information on particular future events of interest such as elections, sports events, and Oscar winners. In this paper, we present the results of an empirical study that compares the forecast accuracy of a prediction market for the FIFA World Cup 2006 to predictions derived from the FIFA world ranking and to a random predictor. We find that prediction markets for the FIFA World Cup outperform predictions based on the FIFA world ranking as well as the random predictor in terms of forecast accuracy.

Prediction Market Performance and Market Liquidity: A Comparison of Automated Market Makers

The use of prediction markets (PMs) for forecasting is emerging in many fields because of its excellent forecasting accuracy. However, PM accuracy depends on its market design, including the choice of market mechanism. Standard financial market mechanisms are not well suited for small, usually illiquid PMs. To avoid liquidity problems, automated market makers (AMMs) always offer buy and sell prices. However, there is limited research that measures the relative performance of AMMs. This paper examines the properties of four documented and applied AMMs and compares their performance in a large-scale simulation study. The results show that logarithmic scoring rules and the dynamic pari-mutuel market attain the highest forecasting accuracy, good robustness against parameter misspecification, the ability to incorporate new information into prices, and the lowest losses for market operators. However, they are less robust in case of noisy trading, which makes them less appropriate in environments with high uncertainty about true prices for shares.

Applications of Prediction Markets

This chapter presents previous fields of application of prediction markets. Subsequently, we discuss several field experiments in more detail. We start with a description of the 2006 FIFA World Cup prediction market called STOCCER. Moreover, we also present the political stock market PSM and the Australian Knowledge eXchange AKX. At the end of the chapter we give an outlook on how prediction markets can be used to generate and evaluate innovative products and services.

Key Design Elements of Prediction Markets

Before studying more advanced applications of prediction markets, it is necessary to gain a basic understanding of their key design elements. Like any market, prediction markets have to be designed and implemented very carefully in order to ensure that they are suitable for aggregating traders’ information (Weinhardt et al., 2003, Weinhardt et al., 2006a). The key design elements comprise the specification of contractstraded in a prediction market, the trading mechanism, and the incentivesprovided to ensure information revelation (Spann and Skiera, 2003). Moreover, diversity of information is required in order to provide a basis for trading (Wolfers and Zitzewitz, 2004). Heterogeneous expectations about the future among traders are desirable and the selection of tradersis thus also considered a key design issue (Tziralis and Tatsiopoulos, 2007b). The following subsections describe these design elements in more detail.

Fundamentals of Prediction Markets

After a short history of prediction markets in Section 2.1, we define prediction markets as markets that run for “the primary purpose of aggregating information so that market prices forecast future events” (Berg and Rietz, 2003) in Section 2.2. The theoretic foundations of prediction markets are found in Hayek’s analysis of market-based economies and in the rose of information in Fama’s efficient market hypothesis in Section 2.3. The interaction between incentives for trade information revelation by trading transactions and the resulting adaption of prices is illustrated by a hands-on example in Section 2.4 on the operational principle of prediction markets.