Intraday trading patterns in an intelligent autonomous agent-based stock market

Kluger, Brian D.; McBride, Mark E.

doi:10.1016/j.jebo.2011.01.032

Cited by 28 publications

(13 citation statements)

References 31 publications

(29 reference statements)

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“…GA has also been used in Neo et al (2003Neo et al ( , 2006 to model two-side learning mechanism in corporate financing. A recently study using GA in limit order market includes Kluger and McBride (2011) in which informed and uninformed traders use GA to decide when to entry the market during a trading day and the model is able to generate some intraday trading patterns. This paper focuses on how uninformed traders use GA to learn from short-lived information and how the informed and uninformed traders interact via a limit order book.…”

Section: Introductionmentioning

confidence: 99%

Learning and Information Dissemination in Limit Order Markets

Wei

Zhang

et al. 2013

SSRN Journal

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What can traders learn and how does learning affect the market? When information is asymmetric, short-lived, and uninformed traders learn, we present an artificial limit order market model to examine the effect of learning, information value, and order aggressiveness on information dissemination efficiency, bid-ask spread, order submission, and order profit of traders. We find that learning helps the uninformed traders to acquire private information more effectively and hence improves market information dissemination. Also the informed traders in general consume liquidity while the uninformed traders mainly supply liquidity. More interestingly, due to the learning and short-lived information, the bid-ask spread and its volatility are positively related to the probability of informed trading. The results help us to understand the behavior of uninformed traders and provide substantial insight and intuition into the trading process.

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Section: Introductionmentioning

confidence: 99%

Learning and Information Dissemination in Limit Order Markets

Wei

Zhang

et al. 2013

SSRN Journal

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“…Here the team's work was concentrated on using the GAs for the needs of decision trees. Kluger and McBride [11] showed implementation of agent-based systems for exploring investment models in intraday investments.…”

Section: Introductionmentioning

confidence: 99%

High frequency trading regarding trade in goods of agricultural origin

Sporysz¹,

Matušek²,

Fitowski³

2017

MERAA

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This work presents the usage model in high frequency trading mechanisms concerning goods of agricultural origin. The aim of this study is to verify this type of solution on the basis of historical data covering the period from Options varying in both the horizon and the time interval have been considered. The best results have been achieved with respect to the historical time horizon for appointing the benchmark proportion of securities and exceeding one day, as well as one-minute time interval. It is worth emphasizing that the investment issue constitutes a very complex problem influenced by a large number of factors. Owing to this fact, no universal mode of conduct guaranteeing profits may be unequivocally indicated. It is possible only to define a scenario, which shall prove effective with a substantial degree of probability.

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“…Agent-based models have been applied to analyze the influence of either the behaviour of financial market investors (Harras and Somette, 2011;Kaizoji, 2003Kaizoji, , 2004Kluger and McBride, 2011;LeBaron, 2012;Takahashi and Terano, 2003;Thurner, 2011;Thurner et al, 2012) or banking market structure and regulation (Geanakoplos et al, 2012;Georg, 2011;Webber and Willison, 2011;Westerhoff, 2008) on systemic risk. Thus far, no comparison of bank-based and marketbased financial systems with respect to systemic risk and the effectiveness of banking regulations in a single model has been conducted in the literature.…”

Section: Introductionmentioning

confidence: 99%

Untitled

Neuberger

Rissi

2014

JBFE

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The macroprudential regulatory framework of Basel III imposes the same minimum capital and liquidity requirements on all banks around the world to ensure global competitiveness of banks. Using an agent-based model of the financial system, we find that this is not a robust framework to achieve (inter)national financial stability, because efficient regulation has to embrace the economic structure and behaviour of financial market participants, which differ from country to country. Market-based financial systems do not profit from capital and liquidity regulations, but from a ban on proprietary trading (Volcker rule). In homogeneous or bank-based financial systems, the most effective regulatory policy to ensure financial stability depends on the stability measure used. Irrespective of financial system architecture, direct restrictions of banks' investment portfolios are more effective than indirect restrictions through capital, leverage and liquidity regulations. Applying the model to the Swiss financial system, we find that increasing regulatory complexity excessively has destabilizing effects. These results highlight for the first time a necessary change in the regulatory paradigm to ensure the effectiveness and efficiency of financial regulations with regards to fostering the resilience of the financial system.

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Intraday trading patterns in an intelligent autonomous agent-based stock market

Cited by 28 publications

References 31 publications

Learning and Information Dissemination in Limit Order Markets

Learning and Information Dissemination in Limit Order Markets

High frequency trading regarding trade in goods of agricultural origin

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