کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
410434 679146 2009 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Predicting investment behavior: An augmented reinforcement learning model
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Predicting investment behavior: An augmented reinforcement learning model
چکیده انگلیسی

The goal of this paper is to augment the ordinal temporal-difference type (TD-type) reinforcement learning model in order to detect the most suitable learning model of the human decision-making process in financial investment tasks. The simplicity and robustness of the TD-type learning model is fascinating. However, the available evidence and our observation suggest the necessity of introducing the nonlinear effect in learning and the possibility that additional factors might play important roles in the investment decision-making process. To extend the ordinal TD-type learning model, we adopt a three-layered perceptron as the basis function and the hierarchical Bayesian method to calibrate the parameter values. The result of the predictive test suggests that the augmented TD-type learning model constructed in this paper can evade the overfitting and can predict people's investment behavior well as compared to other familiar learning models.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 72, Issues 16–18, October 2009, Pages 3447–3461
نویسندگان
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