An Improved MV Method for Stock Allocation Based on the State-Space Measure of Cognitive Bias with a Hybrid Algorithm

An Improved MV Method for Stock Allocation Based on the State-Space Measure of Cognitive Bias with a Hybrid Algorithm

In classical finance theory, cognitive bias does not play any role in predicting returns. With the development of the economy, the classical theory gradually finds it difficult to offset the irrational demand through arbitrage. Due to the rise of behavioral economics, how to allocate stock portfolio...

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Bibliographic Details
Main Authors: Liwen Wang, Hecheng Wu, Gang Li, Weixue Lu
Format: Article
Language:English
Published: MDPI AG 2020-06-01
Series:Symmetry
Subjects:
stock allocation
portfolio efficiency
cognitive bias
mean-variance method
Online Access:https://www.mdpi.com/2073-8994/12/6/1036
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spelling doaj-37e5063520ef4d8eb0276935065523a72020-11-25T02:24:59ZengMDPI AGSymmetry2073-89942020-06-01121036103610.3390/sym12061036An Improved MV Method for Stock Allocation Based on the State-Space Measure of Cognitive Bias with a Hybrid AlgorithmLiwen Wang0Hecheng Wu1Gang Li2Weixue Lu3College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaCollege of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaCollege of Economics, Northeastern University at Qinhuangdao, Qinhuangdao 066000, ChinaCollege of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaIn classical finance theory, cognitive bias does not play any role in predicting returns. With the development of the economy, the classical theory gradually finds it difficult to offset the irrational demand through arbitrage. Due to the rise of behavioral economics, how to allocate stock portfolios in the highly subjective environment is an unavoidable problem. Considering the decision heterogeneity between the rational market and the irrational one, the mean-variance (MV) method was improved in the construction of a market bias index for stock portfolio allocation, which we called EMACB (exponential moving average of cognitive bias)-variance method. Besides, due to the lack of related research, we introduced a measure of aggregate investor cognitive bias by adopting the state-space model. Finally, the proposed method was applied in an investment allocation example to prove its feasibility, and its advantages were emphasized by a comparison with another relevant approach.https://www.mdpi.com/2073-8994/12/6/1036stock allocationportfolio efficiencycognitive biasmean-variance method
collection DOAJ
language English
format Article
sources DOAJ
author Liwen Wang
Hecheng Wu
Gang Li
Weixue Lu
spellingShingle Liwen Wang
Hecheng Wu
Gang Li
Weixue Lu
An Improved MV Method for Stock Allocation Based on the State-Space Measure of Cognitive Bias with a Hybrid Algorithm
Symmetry
stock allocation
portfolio efficiency
cognitive bias
mean-variance method
author_facet Liwen Wang
Hecheng Wu
Gang Li
Weixue Lu
author_sort Liwen Wang
title An Improved MV Method for Stock Allocation Based on the State-Space Measure of Cognitive Bias with a Hybrid Algorithm
title_short An Improved MV Method for Stock Allocation Based on the State-Space Measure of Cognitive Bias with a Hybrid Algorithm
title_full An Improved MV Method for Stock Allocation Based on the State-Space Measure of Cognitive Bias with a Hybrid Algorithm
title_fullStr An Improved MV Method for Stock Allocation Based on the State-Space Measure of Cognitive Bias with a Hybrid Algorithm
title_full_unstemmed An Improved MV Method for Stock Allocation Based on the State-Space Measure of Cognitive Bias with a Hybrid Algorithm
title_sort improved mv method for stock allocation based on the state-space measure of cognitive bias with a hybrid algorithm
publisher MDPI AG
series Symmetry
issn 2073-8994
publishDate 2020-06-01
description In classical finance theory, cognitive bias does not play any role in predicting returns. With the development of the economy, the classical theory gradually finds it difficult to offset the irrational demand through arbitrage. Due to the rise of behavioral economics, how to allocate stock portfolios in the highly subjective environment is an unavoidable problem. Considering the decision heterogeneity between the rational market and the irrational one, the mean-variance (MV) method was improved in the construction of a market bias index for stock portfolio allocation, which we called EMACB (exponential moving average of cognitive bias)-variance method. Besides, due to the lack of related research, we introduced a measure of aggregate investor cognitive bias by adopting the state-space model. Finally, the proposed method was applied in an investment allocation example to prove its feasibility, and its advantages were emphasized by a comparison with another relevant approach.
topic stock allocation
portfolio efficiency
cognitive bias
mean-variance method
url https://www.mdpi.com/2073-8994/12/6/1036
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AT hechengwu improvedmvmethodforstockallocationbasedonthestatespacemeasureofcognitivebiaswithahybridalgorithm
AT gangli improvedmvmethodforstockallocationbasedonthestatespacemeasureofcognitivebiaswithahybridalgorithm
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