Probability distortion of truncated quantile critics for stock trading environment

This paper proposes the use of Cumulative Prospect Theory (CPT) in combination with Truncated Quantile Critics (TQC) for stock trading. CPT is a popular model of decision making under risk that has been shown to better describe human behavior than traditional models such as expected utility theory....

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Foo, Marcus Jun Rong
مؤلفون آخرون: Patrick Pun Chi Seng
التنسيق: Final Year Project
اللغة:English
منشور في: Nanyang Technological University 2023
الموضوعات:
الوصول للمادة أونلاين:https://hdl.handle.net/10356/166624
الوسوم: إضافة وسم
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المؤسسة: Nanyang Technological University
اللغة: English
الوصف
الملخص:This paper proposes the use of Cumulative Prospect Theory (CPT) in combination with Truncated Quantile Critics (TQC) for stock trading. CPT is a popular model of decision making under risk that has been shown to better describe human behavior than traditional models such as expected utility theory. TQC is a variant of the popular Quantile Regression DQN algorithm that has been shown to be more sample efficient. By combining these two models, our approach aims to better capture the decision making process of human traders. Furthermore, we incorporate Prelec weighting as a side study to mitigate time inconsistency in decision making. Our experiments in stock trading show that our proposed approach outperforms traditional methods in various portfolio metrics.