- 22 Dezember 2017
- 208
- 124
Abstract. Financial markets such as stock exchanges and electronic prediction markets frequently use the services of an entity called the market-maker to ensure that the market’s traders can make their transactions. Recently, several strategies that can be used by market-makers to control market trading prices have been proposed by various researchers. A detailed comparison of these market maker strategies using real trading data extracted from financial markets is essential to understanding the relative merits and requirements of the different market-maker strategies. We address this aspect of market-maker strategies by empirically comparing different strategies with data obtained from the NASDAQ market. Our results show that a reinforcement learning-based strategy performs well in maintaining low spread as well as in obtaining high utilities, whereas other strategies only succeed in either maintaining low spread or outperforming others in utilities. 1
Keywords: Market-maker strategy, electronic financial markets, market-maker simulation.
1 Introduction Over the past few years, the rapid growth and success of automated techniques for e-commerce have resulted in their wide adoption in various domains beyond traditional B2B and B2C commodity markets. For example, in financial markets human traders are being replaced by automated agents that efficiently buy and sell financial securities. Currently many modern exchanges, such as NYSE, NASDAQ, and Toronto Stock Exchange as well as electronic prediction markets, such as tradesports.com, use such automated agents called market-makers to regulate prices and quantities of securities or stocks traded by the market’s participants. A market-maker holds a certain number of securities in its inventory with the purpose of being able to sell them to an interested buyer, or to buy securities from a seller selling securities in the market. A market can have either a single market-maker or multiple market-makers that compete with each other.
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Keywords: Market-maker strategy, electronic financial markets, market-maker simulation.
1 Introduction Over the past few years, the rapid growth and success of automated techniques for e-commerce have resulted in their wide adoption in various domains beyond traditional B2B and B2C commodity markets. For example, in financial markets human traders are being replaced by automated agents that efficiently buy and sell financial securities. Currently many modern exchanges, such as NYSE, NASDAQ, and Toronto Stock Exchange as well as electronic prediction markets, such as tradesports.com, use such automated agents called market-makers to regulate prices and quantities of securities or stocks traded by the market’s participants. A market-maker holds a certain number of securities in its inventory with the purpose of being able to sell them to an interested buyer, or to buy securities from a seller selling securities in the market. A market can have either a single market-maker or multiple market-makers that compete with each other.
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