Can Bounded Rationality Be
Identified in the Australian
Stock Market?
Roberta Powell
PhD Candidate
University of Queensland
Queensland University of Technology
Overview
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Introduction
Bounded Rationality
Empirical Measure of Bounded Rationality
Sample
Model
Econometric Approach
Results
Conclusion
Questions
Introduction
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Identification of Bounded Rationality in
Australian Stock Market
Companies from S&P/ASX 200 classified as
optimizers or satisficers with proxy
Adapted Noise Trader Model
Cohort Dummy Variables
TSCS and OLS/PCSE
Bounded Rationality
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Neoclassical Economics
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Herbert Simon – Bounded Rationality
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Optimizers
Satisficers
Aspiration levels
Resource scarcity
Other Research
Empirical Measure of Bounded
Rationality
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SG&A to represent deliberation cost
SG&A/MV ratio
Quartiles
Optimizers and satisficers
Gainers and losers
Sample
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S&P/ASX 200 Index
High capitalisation
139 Australian companies
All industry sectors represented
SG&A dataset for Australia
Model
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Adapted Noise Trader Model
Inclusion of optimisers, satisficers, gainers and
losers
Noise trading as demand side bounded
rationality
SG&A expenditure as supply side bounded
rationality
Model Equations
Δpi,t = αp + t + β.volresi,t + εp,i,t
dyi,t = αdy + t + γ.dyi,t-1 + εdy,i,t
xri,t = αxr + t + ζ1xri,t-1 + ζ2voli,t-1 + εxr,i,t
where
εt ~ N(0, σ2n)
i = company
t = temporal period
Econometric Approach
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TSCS data
Cohort Dummy variables
OLS/Panel Corrected Standard Errors
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Serial correlation in residuals – LDV
PCSE
Wald Tests
Specification Tests
Results
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Significance of Cohort Dummies Across
Market
Significance of Cohort Dummies Across
Industry Sectors
Conclusion
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Herbert Simon questioned the neoclassical
model - Theory of Bounded Rationality
Insight into the Australian stock market
SG&A and Adapted Noise Trader Model
TSCS single coefficient cohort dummy
variable estimations using OLS/PCSE
Some evidence for optimisers and satisficers in
the Australian stock market
Questions