Download Advances in Artificial Economics: The Economy as a Complex by Charlotte Bruun PDF

By Charlotte Bruun

This publication is predicated on displays at AE’2006 (Aalborg, Denmark) – the second one symposium on man made Economics. As a brand new confident simulation procedure, Agent-Based Computational Economics (ACE) has in recent times confirmed its power and applicability. insurance during this quantity extends to renowned questions of economics, just like the lifestyles of marketplace potency, and to questions raised by means of new analytical instruments, for instance networks of social interaction.

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Additional resources for Advances in Artificial Economics: The Economy as a Complex Dynamic System (Lecture Notes in Economics and Mathematical Systems)

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These assumptions hold for all the simulations reported in this paper. First, traders are restricted to trade one unit at a time. This restriction on traded quantities simplifies the strategy space and allows direct comparisons with existing theoretical results. Second, buying orders are constrained by the available cash and selling orders by the available endowment of the asset; that is, budget constraints hold. This is consistent with a value-based strategy (“buy low, sell high”), which is a seemingly natural requirement of rationality for traders’ behaviors.

Have a substantially lower excess volume than the other two protocols under any of our variants of intelligent trading; regardless of these, the former two never exhibit more than 4% excess volume, while the latter two never go below 40%. Second, increasing trading intelligence tends to reduce excess volume, most notably in the continuous double auction, but does not eradicate the differences. We fit a linear model to the data using a robust regression based on an M estimator; see Venables and Ripley (2002).

If BA is greater than the accepted offer, a buyer could have obtained the same profits whatever the value of the bid was. Following this strategy choice decision, the resulting population will have a particular proportion of the three types of software bidding agents (ZIP, GD and K). To have a graphical idea of the dynamics of this proportion, we will represent the strategy space by a two dimensional simplex grid with vertices corresponding to the pure strategies (all ZIP, all GD or all K). We draw three regions to represent the populations that have a dominant strategy when more than 33% of the agents use the strategy.

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