6533b831fe1ef96bd1298fee
RESEARCH PRODUCT
The Dynamics of Quote Prices in an Artificial Financial Market with Learning Effects
Andrea ConsiglioAnnalisa RussinoValerio Lacagninasubject
Mark to modelMicroeconomicsFinancial economicsfinancial market market volatility learning process copula function portfolio optimizationFinancial marketMarket systemOrder bookPortfolioBusinessPortfolio optimizationVolatility (finance)Market liquiditydescription
In this paper we study the evolution of bid and ask prices in an electronic financial market populated by portfolio traders who optimally choose their allocation strategy on the basis of their views about market conditions. Recently, a growing literature has investigated the consequences of learning about the returns process1. There has been an increasing interest in analyzing what are the implications of relaxing the assumption that agents hold correct expectations. In particular, it has been asked the fundamental question of understanding if typical asset-pricing anomalies (like returns predictability, and excess volatility) can be generated by a learning process about the underlying economy. In this paper we focus on the process by which information is incorporated into prices, examining the relationships among the dynamics of price changes, and the time variation of liquidity and of trading activity. We design an order book market system. Agents enter the market sequentially, and they trade to adjust their portfolio according to their optimal target
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2007-05-19 |