| By: |
Sabine Vincent (ETH Zurich);
Tatyana Kovalenko (ETH Zurich);
Vyacheslav I. Yukalov (Joint Institute for Nuclear Research; D-MTEC, ETH Zurich);
Didier Sornette (Swiss Finance Institute; ETH Zürich - Department of Management, Technology, and Economics (D-MTEC)) |
| Abstract: |
We present the first calibration of quantum decision theory (QDT) to an
empirical data set. The data comprise 91 choices between two lotteries (two
"prospects") presented in 91 random pairs made by 142 subjects offered at two
separated times. First, we quantitatively account for the fraction of choice
reversals between the two repetitions of the decisions, using a probabilistic
choice formulation in the simplest possible form with no model assumption and
no adjustable parameter. The prediction of choice reversal is then refined by
introducing heterogeneity between decision makers through a differentiation of
the population into two similar sized groups in terms of "over-confident" and
"contrarian" decision makers. This supports the first fundamental tenet of
QDT, which models the choice of an option as an inherent probabilistic
process, such that the probability of a choice can be expressed as the sum of
its utility and attraction factors. We propose to model (a) the utility factor
with a stochastic version of cumulative prospect theory (logit-CPT), and (b)
the attraction factor with a constant absolute risk aversion (CARA) function.
This makes logit-CPT nested in our proposed parameterisation of QDT, allowing
for a precise quantitative comparison between the two theories. For this data
set, the QDT model is found to perform better at both the aggregate and
individual levels, and for all considered fit criteria both for the first
iteration of the experiment and for predictions (second iteration). The QDT
effect associated with the attraction factor is mostly appreciable for
prospects with big losses. Our quantitative analysis of the experiment results
supports the existence of an intrinsic limit of predictability, which is
associated with the inherent probabilistic nature of choice. |
| Keywords: |
Quantum decision theory, QDT, prospect probability, utility factor, attraction factor, interference, parametrization, hierarchical estimation method, calibration, empirical data, simple gambles, stochastic Cumulative prospect theory, logit-CPT, probabilistic decision making, limits of predictability |
| JEL: |
C44 D81 |
| URL: |
http://d.repec.org/n?u=RePEc:chf:rpseri:rp1631&r=dcm |