Dynamic Learning and Market Making in Spread Betting Markets with Informed Bettors
研究了博彩公司在面对知情投注者时如何设置点差线以避免被操纵，提出了一种名为惯性策略的动态学习与定价算法，既能有效收集市场信息又能抵御策略性操纵。
How Bookies Can Outwit Sophisticated Bettors Sports-betting markets are based entirely on predictions. A bettor has to pick a winning contestant, and a market maker―a bookie―bets on the opponent. As bookies have to take the other side of every bet, it is of great value to understand the market making problem, that is, how to set the spread lines as “prices” for the bookies. Nevertheless, understanding of this problem is limited. Specifically, sophisticated bettors exist in the market, and a bookie can be manipulated by skillful bettors because of information asymmetry. In “Dynamic Learning and Market Making in Spread Betting Markets with Informed Bettors,” Birge, Feng, Keskin, and Schultz study the market-making problem under information asymmetry and market manipulation. They show that, although many popular learning and pricing algorithms, such as Bayesian policies, are effective in learning, they are vulnerable to strategic manipulations. The authors propose a dynamic learning and pricing algorithm, called the inertial policy, that collects information from the market effectively but also protects the bookie from strategic manipulations.