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Confounding dynamic risk taking propensity with a momentum prognostic strategy: the case of the Columbia Card Task (CCT).

Markiewicz Ł, Kubińska E, Tyszka T - Front Psychol (2015)

Bottom Line: We argue that the HOT version confounds an individual's willingness to accept risk with their beliefs in trend continuation vs. trend reversal in a prognostic task.Thus, we provide evidence that, when considered as a dynamic risk propensity measure, the number of turned over cards in the HOT version of the CCT is a contaminated measure and reflects two phenomena: (1) risk preference and (2) the decision-maker's belief in trend continuation.We speculate that other dynamic risk taking measures can also be biased by a momentum strategy.

View Article: PubMed Central - PubMed

Affiliation: Centre for Economic Psychology and Decision Sciences, Kozminski University Warsaw, Poland.

ABSTRACT
Figner et al. (2009) developed the Columbia Card Task (CCT) to measure risk-taking attitudes. This tool consists of two versions: in the COLD version the decision maker needs to state in advance how many cards (out of 32) they want to turn over (so called static risk taking), in the HOT version they have the possibility of turning over all 32 cards one-by-one until they decide to finish (dynamic risk taking). We argue that the HOT version confounds an individual's willingness to accept risk with their beliefs in trend continuation vs. trend reversal in a prognostic task. In two experimental studies we show that people believing in trend continuation (momentum subjects) turn over more cards than those believing in trend reversal (contrarians) in the HOT version of the task. However, this is not the case in the COLD version. Thus, we provide evidence that, when considered as a dynamic risk propensity measure, the number of turned over cards in the HOT version of the CCT is a contaminated measure and reflects two phenomena: (1) risk preference and (2) the decision-maker's belief in trend continuation. We speculate that other dynamic risk taking measures can also be biased by a momentum strategy.

No MeSH data available.


Related in: MedlinePlus

Study 2: the number of turned over cards in the HOT CCT separately for momentum and contrarian participants.
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Figure 3: Study 2: the number of turned over cards in the HOT CCT separately for momentum and contrarian participants.

Mentions: In Study 2 we retested hypothesis H1, assuming that prognostic strategy, as measured externally for the CCT, would influence the number of turned over cards in the HOT condition. We assumed that in the HOT condition the momentum followers would turn over more cards than the contrarians. To validate the results of Study 1 t-test was conducted which showed that momentum followers turned over more cards than contrarians [t(25) = 2.270, p = 0.032; d = 0.927]. The result (Figure 3), with large effect size this time, therefore provides additional support for the Study 1 results and adds significantly to research using other recency task. The difference between Studies 1 and 2 was the different event sequence used in the recency test (see Figure 1), and therefore the results show that verification of H1 does not depend on the sequence used to divide people into contrarian and momentum groups.


Confounding dynamic risk taking propensity with a momentum prognostic strategy: the case of the Columbia Card Task (CCT).

Markiewicz Ł, Kubińska E, Tyszka T - Front Psychol (2015)

Study 2: the number of turned over cards in the HOT CCT separately for momentum and contrarian participants.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4528171&req=5

Figure 3: Study 2: the number of turned over cards in the HOT CCT separately for momentum and contrarian participants.
Mentions: In Study 2 we retested hypothesis H1, assuming that prognostic strategy, as measured externally for the CCT, would influence the number of turned over cards in the HOT condition. We assumed that in the HOT condition the momentum followers would turn over more cards than the contrarians. To validate the results of Study 1 t-test was conducted which showed that momentum followers turned over more cards than contrarians [t(25) = 2.270, p = 0.032; d = 0.927]. The result (Figure 3), with large effect size this time, therefore provides additional support for the Study 1 results and adds significantly to research using other recency task. The difference between Studies 1 and 2 was the different event sequence used in the recency test (see Figure 1), and therefore the results show that verification of H1 does not depend on the sequence used to divide people into contrarian and momentum groups.

Bottom Line: We argue that the HOT version confounds an individual's willingness to accept risk with their beliefs in trend continuation vs. trend reversal in a prognostic task.Thus, we provide evidence that, when considered as a dynamic risk propensity measure, the number of turned over cards in the HOT version of the CCT is a contaminated measure and reflects two phenomena: (1) risk preference and (2) the decision-maker's belief in trend continuation.We speculate that other dynamic risk taking measures can also be biased by a momentum strategy.

View Article: PubMed Central - PubMed

Affiliation: Centre for Economic Psychology and Decision Sciences, Kozminski University Warsaw, Poland.

ABSTRACT
Figner et al. (2009) developed the Columbia Card Task (CCT) to measure risk-taking attitudes. This tool consists of two versions: in the COLD version the decision maker needs to state in advance how many cards (out of 32) they want to turn over (so called static risk taking), in the HOT version they have the possibility of turning over all 32 cards one-by-one until they decide to finish (dynamic risk taking). We argue that the HOT version confounds an individual's willingness to accept risk with their beliefs in trend continuation vs. trend reversal in a prognostic task. In two experimental studies we show that people believing in trend continuation (momentum subjects) turn over more cards than those believing in trend reversal (contrarians) in the HOT version of the task. However, this is not the case in the COLD version. Thus, we provide evidence that, when considered as a dynamic risk propensity measure, the number of turned over cards in the HOT version of the CCT is a contaminated measure and reflects two phenomena: (1) risk preference and (2) the decision-maker's belief in trend continuation. We speculate that other dynamic risk taking measures can also be biased by a momentum strategy.

No MeSH data available.


Related in: MedlinePlus