Evidence map›Paper›PMID 34437550›Full record

ArticlePloS one2021

To maximize or randomize? An experimental study of probability matching in financial decision making.

Andrew W Lo, Katherine P Marlowe, Ruixun Zhang

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.2field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 13 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Andrew W LoMIT Sloan School of Management, Cambridge, MA, United States of America.
Katherine P MarloweMIT Laboratory for Financial Engineering, Cambridge, MA, United States of America.
Ruixun ZhangMIT Laboratory for Financial Engineering, Cambridge, MA, United States of America.ORCID 0000-0002-7670-8393
Santa Fe Institute · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Probability matching, also known as the "matching law" or Herrnstein's Law, has long puzzled economists and psychologists because of its apparent inconsistency with basic self-interest. We conduct an experiment with real monetary payoffs in which each participant plays a computer game to guess the outcome of a binary lottery. In addition to finding strong evidence for probability matching, we document different tendencies towards randomization in different payoff environments-as predicted by models of the evolutionary origin of probability matching-after controlling for a wide range of demographic and socioeconomic variables. We also find several individual differences in the tendency to maximize or randomize, correlated with wealth and other socioeconomic factors. In particular, subjects who have taken probability and statistics classes and those who self-reported finding a pattern in the game are found to have randomized more, contrary to the common wisdom that those with better understanding of probabilistic reasoning are more likely to be rational economic maximizers. Our results provide experimental evidence that individuals-even those with experience in probability and investing-engage in randomized behavior and probability matching, underscoring the role of the environment as a driver of behavioral anomalies.

Indexed as

Decision Making, Computer-AssistedFinancial ManagementModels, EconomicHumansProbabilityRandom Allocation

Identifiers

PMID34437550
PMCPMC8389367
OpenAlexW3195224894

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.