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on Computational Economics |
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Issue of 2013‒08‒31
four papers chosen by |
| By: | Carl Chiarella (Finance Discipline Group, UTS Business School, University of Technology, Sydney); Xue-Zhong He (Finance Discipline Group, UTS Business School, University of Technology, Sydney); Lijian Wei (Finance Discipline Group, UTS Business School, University of Technology, Sydney) |
| Abstract: | How do traders process and learn from market information, what trading strategies should they use, and how does learning affect the market? This paper proposes a learning model of an articial limit order market with asymmetric information to address these issues. Using a genetic algorithm as a learning mechanism, we show that learning, in particular the learning from uninformed traders, improves market informational efficiency and has a significant impact on the stylized facts of limit order markets, order submission, liquidity supply and consumption, the hump shaped order book near the quote, and the bid-ask spread. Moreover, the learning affects the evolution process of the trading strategies for all traders. The model provides some insights into market efficiency, the interaction of traders, the dynamics of limit order books, and the evolution of trading strategies. |
| Keywords: | Limit order book; evolution; genetic algorithm learning; asymmetric information; trading strategy |
| JEL: | G14 C63 D82 |
| Date: | 2013–08–01 |
| URL: | http://d.repec.org/n?u=RePEc:uts:rpaper:335&r=cmp |
| By: | Banse, Martin; Shutes, Lindsay; Dixon, Peter; Van Meijl, Hans; Rimmer, Maureen; Tabeau, Andrzej; Woltjer,Geert; Rothe, Andrea |
| Abstract: | One objective of Computable general equilibrium (CGE) models is the analysis of economywide effects of policy measures. The focus of the Factor Markets project is to analyse the functioning of factor markets for agriculture in the EU-27, including the Candidate Countries. While agricultural and food markets are fully integrated in a European single market, subject to an EU-wide common policy, the Common Agricultural Policy (CAP), this is not the case for the agricultural factor markets capital, labour and land. There are partly serious differences with regard to member state regulations and institutions affecting land, labour and capital markets. The presentation of this heterogeneity of factor markets amongst EU Member States have been implemented in the CGE models to improve model-based analyses of the CAP and other policy measures affecting agricultural production. This final report comprises the outcome of a systematic extension and improvement of the Modular Applied GeNeral Equilibrium Tool (MAGNET) model starting from an overview of the current state of the art to represent factor markets in CGE models to a description of work on labour, land and capital in MAGNET. |
| Date: | 2013–06 |
| URL: | http://d.repec.org/n?u=RePEc:eps:fmwppr:159&r=cmp |
| By: | Daniel Fricke; Thomas Lux |
| Abstract: | We investigate the effects of a Financial Transaction Tax (FTT) in an order-driven artificial financial market. FTTs are meant to limit short-term speculative behavior by reducing the amount of excess liquidity in the system. To quantify these effects, adjustments in trading strategies and their effects on liquidity need to be taken into account. We model an agent-based continuous double-auction, allowing for a continuum of investment strategies within the chartist/fundamentalist framework. For certain parameter combinations, our model is able to reproduce certain stylized facts of financial time-series. We find largely positive effects of the FTT for small tax rates. Additionally, for large tax rates we find the effects not to be as negative as previously found |
| Keywords: | Transaction Tax, Tobin Tax, Market Microstructure, Agent-Based Models, Speculative Bubbles |
| JEL: | H20 C63 D44 |
| Date: | 2013–08 |
| URL: | http://d.repec.org/n?u=RePEc:kie:kieliw:1868&r=cmp |
| By: | Galbiati, Marco (Bank of England); Soramaki, Kimmo (Financial Network Analytics) |
| Abstract: | Given a network of client-clearer relationships, we define central clearing as a function transforming bilateral trading exposures into centrally cleared exposures. By using numerical simulations, we study how this function is affected by the network's topology, focusing on the exposures of the central counterparty. By assuming that margin requirements are a linear function of exposures, we also draw conclusions as to how the network topology affects aggregate margin requirements. |
| Keywords: | Central counterparty; CCP; clearing; settlement; network analysis |
| JEL: | E58 G01 G18 |
| Date: | 2013–08–16 |
| URL: | http://d.repec.org/n?u=RePEc:boe:boeewp:0480&r=cmp |