Heterogeneity in generalized reinforcement learning and its relation to cognitive ability

Chen, Shu‐Heng; Du, Ye-Rong

doi:10.1016/j.cogsys.2016.11.001

Cited by 2 publications

(2 citation statements)

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“…The EWA model allows individual difference in learning. For details about the EWA learning model, the readers are referred to Chen and Du (2017). The parameters in the EWA learning model are remotely used in marketing research (Ho, Lim, & Camerer, 2006).…”

Section: Adaptive Learning Criteria For Decision Choicesmentioning

confidence: 99%

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Market Microstructure Noise, Intraday Stock Market Returns, and Adaptive Learning: Indian Evidence

Sinha

2019

Colombo Bus. J

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What drives intraday traders' sentiments in the stock markets: information or noise? This paper argues that the market microstructure noise (MMN) manifests intraday traders' aggregate sentiments depicted by chaotic and noisy market returns. It examines if intraday stock market returns, returns' variances and higher order moments are erratic, noisy and nonnormal. It shows that the intraday Bombay Stock Exchange (BSE) Sensex and National Stock Exchange (NSE) Nifty index returns approximate to zero-mean, zero-variance but skewed and leptokurtic in distributions. In exploring the intraday market index returns, standardisation process reveals noises in the BSE market, but it is evened up in the NSE market. Since intraday traders' market sentiments and decision choices are behavioural, noisy but adaptive, their decision choices need strategies given that those strategies have numerical "attractions" that determine choice probabilities. We explore the adaptive Experience Weighted Attraction (EWA) learning parameters to show persistent MMN in intraday traders' adaptive learning behaviours.

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Section: Adaptive Learning Criteria For Decision Choicesmentioning

confidence: 99%

“…The parameters in the EWA learning model are remotely used in marketing research (Ho, Lim, & Camerer, 2006). The same can also be used in simulation of portfolio selection (Steinbacher, 2012) and economic guessing (Chen & Du, 2017).…”

Section: Adaptive Learning Criteria For Decision Choicesmentioning

confidence: 99%

Market Microstructure Noise, Intraday Stock Market Returns, and Adaptive Learning: Indian Evidence

Sinha

2019

Colombo Bus. J

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Counterfactual Thinking and Causal Mediation: An Application to Female Labour Force Participation in India

Kumar

Kao²

2023

Understanding Complex Systems

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Heterogeneity in generalized reinforcement learning and its relation to cognitive ability

Cited by 2 publications

References 50 publications

Market Microstructure Noise, Intraday Stock Market Returns, and Adaptive Learning: Indian Evidence

Market Microstructure Noise, Intraday Stock Market Returns, and Adaptive Learning: Indian Evidence

Counterfactual Thinking and Causal Mediation: An Application to Female Labour Force Participation in India

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