Conference item
Extending and Evaluating Agent-Based Models of Algorithmic Trading Strategies.
- Abstract:
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Algorithmic trading (AT) strategies aim at executing large orders discretely, in order to minimize the order's impact, whilst also hiding the traders' intentions. Most AT evaluation methods range from running the AT strategies against historical data (back testing) to evaluating them on simulated markets. The contribution of the work presented in this paper is twofold. First we investigated different types of agent-based market simulations and suggested how to identify the most suitable marke...
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- Publication status:
- Published
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- Publisher copy:
- 10.1109/ICECCS.2012.18
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Bibliographic Details
- Publisher:
- IEEE Publisher's website
- Pages:
- 351-360
- Host title:
- ICECCS
- Publication date:
- 2012-01-01
- DOI:
- Source identifiers:
-
330957
- ISBN:
- 9781467321563
Item Description
- Keywords:
- Pubs id:
-
pubs:330957
- UUID:
-
uuid:a8632ba3-ab5f-40df-a799-f6b715df59ab
- Local pid:
- pubs:330957
- Deposit date:
- 2013-11-17
Terms of use
- Copyright date:
- 2012
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