Dynamic order submission strategies with competition between a dealer market and a crossing network.

We present a dynamic microstructure model where a dealer market (DM) and a crossing network (CN) interact. We consider sequentially arriving agents having different valuations for an asset. Agents maximize their profits by either trading at a DM or by submitting an order for (possibly) uncertain execution at a CN. We develop the analysis for three different informational settings: transparency, “complete” opaqueness of all order flow, and “partial” opaqueness (with observable DM trades). We find that a CN and a DM cater for different types of traders. Investors with a high eagerness to trade are more likely to prefer a DM. The introduction of a CN increases overall order flow by attracting traders who would not otherwise submit orders (“order creation”). It also diverts trades from the DM. The transparency and “partial” opaqueness settings generate systematic patterns in order flow. With transparency, the probability of observing a CN order at the same side of the market is smaller after such an order than if it was not. Buy (sell) orders at a CN are also less likely to attract subsequent sell (buy) orders at the DM.Competition; Market; Order; Strategy;

Dynamic order Submission Strategies with Competition between a Dealer Market and a Crossing Network

We present a dynamic microstructure model where a dealer market (DM) and a crossing network (CN) interact. We consider sequentially arriving agents having different valuations for an asset. Agents maximize their profits by either trading at a DM or by submitting an order for (possibly) uncertain execution at a CN. We develop the analysis for three different informational settings: transparency, “complete” opaqueness of all order flow, and “partial” opaqueness (with observable DM trades). We find that a CN and a DM cater for different types of traders. Investors with a high eagerness to trade are more likely to prefer a DM. The introduction of a CN increases overall order flow by attracting traders who would not otherwise submit orders (“order creation”). It also diverts trades from the DM. The transparency and “partial” opaqueness settings generate systematic patterns in order flow. With transparency, the probability of observing a CN order at the same side of the market is smaller after such an order than if it was not. Buy (sell) orders at a CN are also less likely to attract subsequent sell (buy) orders at the DM.

Can auctions control market power in emissions trading markets.

Using eight sessions (twenty-four ten-period markets) in a double ABA cross-over design, we demonstrate clear evidence of market power in double-auction emission trading markets (agents who are not constrained to only buy or sell). Conventional theory predicts that in half of the market-power environments monopsony should emerge and in half monopoly should emerge. Market-power outcomes are frequently observed, most often in the form of price discrimination, and most effectively by monopsonists.

Three Minimal Market Institutions with Human and Algorithmic Agents: Theory and Experimental Evidence

We define and examine three minimal market games (sell-all, buy-sell, and double auction) in the laboratory relative to the predictions of theory. These closed exchange economies have some cash to facilitate transactions, and include feedback. The experiment reveals that (1) the competitive general equilibrium (CGE) and non-cooperative (NCE) models are reasonable anchors to locate most but not all the observed outcomes of the three market mechanisms; (2) outcomes tend to get closer to CGE predictions as the number of players increases; (3) prices and allocations in double auctions deviate persistently from CGE predictions; (4) the outcome paths across the three market mechanisms differ significantly and persistently; (5) importance of market structures for outcomes is reinforced by algorithmic trader simulations; and (6) none of the three markets dominates the others across six measures of performance. Inclusion of some mechanism differences into theory may enhance our understanding of important aspects of markets.Strategic market games, Laboratory experiments, Minimally intelligent agents, Adaptive learning agents, General equilibrium

Agent-based simulation of a financial market

This paper introduces an agent-based artificial financial market in which heterogeneous agents trade one single asset through a realistic trading mechanism for price formation. Agents are initially endowed with a finite amount of cash and a given finite portfolio of assets. There is no money-creation process; the total available cash is conserved in time. In each period, agents make random buy and sell decisions that are constrained by available resources, subject to clustering, and dependent on the volatility of previous periods. The model herein proposed is able to reproduce the leptokurtic shape of the probability density of log price returns and the clustering of volatility. Implemented using extreme programming and object-oriented technology, the simulator is a flexible computational experimental facility that can find applications in both academic and industrial research projects.Comment: 11 pages, 3 EPS figures, LaTEX. To be published in Physica A (Proceedings of the NATO Advanced Research Workshop on Application of Physics in Economic Modelling, Prague 8-10 February 2001

Bubbles and crashes with partially sophisticated investors

We consider a purely speculative market with finite horizon and complete information. We introduce partially sophisticated investors, who know the average buy and sell strategies of other traders, but lack a precise understanding of how these strategies depend on the history of trade. In this setting, it is common knowledge that the market is overvalued and bound to crash, but agents hold different expectations about the date of the crash. We define conditions for the existence of equilibrium bubbles and crashes, characterize their structure, and show how bubbles may last longer when the amount of fully rational traders increases.speculative bubbles ; crashes ; bounded rationality