Probability-Preferences in Gambling

Edwards, Ward

doi:10.2307/1418231

Cited by 232 publications

(92 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Both of these studies are open to the eriticism that the Ss may not have perceived the risks as real. In the Wallach, Kogan, & Bem (1964) experiment, the money risked belonged to the E, and Edwards (1953) suggested that such money may be valued differently from money that was the S's own. Edwards found a preference for riskier gambles when the S used his own money, but this was comparable to the individual choices made before discussion in the group-decision studies.…”

mentioning

confidence: 99%

“…The single group that had a risky shift was predominantly male. The conservatism of the original individual choices is of some interest in view of Edwards's (1953) results. One hypothesis might be that students are conservative with grades, while they are risky with small amounts of money because of the subjective values attached (e.g., one might reason, "I can always earn another $2, no matter how poor I am, but I'm stuck with a poor grade on my re cord forever").…”

mentioning

confidence: 99%

See 1 more Smart Citation

No risky shift effect with real groups and real risks

Clement

Sullivan

1970

Psychon Sci

View full text Add to dashboard Cite

mentioning

confidence: 99%

mentioning

confidence: 99%

No risky shift effect with real groups and real risks

Clement

Sullivan

1970

Psychon Sci

View full text Add to dashboard Cite

“…That is, given measures µ and ν, the problem is to know whether a g exists that satisfies Equation 4 and, if so, compute such g.…”

Section: Choquet Integral and Derivatives With Respect To Fuzzy Measuresmentioning

confidence: 99%

Hellinger distance for fuzzy measures

Torra

Narukawa

Sugeno³

et al. 2013

Proceedings of the 8th Conference of the European Society for Fuzzy Logic and Technology

View full text Add to dashboard Cite

show abstract

“…To address the latter issue, early experimental studies such as Preston and Baratta (1948), Edwards (1953), and Edwards (1954) reveal that decision makers systematically violate the independence axiom of von Neumann and Morgenstern (1947), thus concluding that subjects decide in discord with physical probabilities and seem to apply decision weights to making choices. These findings prompted development of generalized expected utility theories, such as Dual Theory (Yaari (1987)) and creation of Rank-dependent Utility (RDU) as advocated by Edwards (1962), Karmarkar (1978), Karmarkar (1979), Quiggin (1982) and Wakker (1994), whereas another strand of the literature proposed modifications of the utility function itself (e.g., Friedman and Savage (1948), Markowitz (1952), Kahneman and Tversky (1979), Wakker and Tversky (1993)).…”

Section: Preferences In Financial Markets and Experimentsmentioning

confidence: 99%

On the Applicability of Maximum Likelihood Methods: From Experimental to Financial Data

Jakusch

2013

SSRN Journal

View full text Add to dashboard Cite

Abstract. This paper addresses whether and to what extent econometric methods used in experimental studies can be adapted and applied to financial data to detect the best-fitting preference model. To address the research question, we implement a frequently used nonlinear probit model in the style of Hey and Orme (1994) and base our analysis on a simulation stud. In detail, we simulate trading sequences for a set of utility models and try to identify the underlying utility model and its parameterization used to generate these sequences by maximum likelihood. We find that for a very broad classification of utility models, this method provides acceptable outcomes. Yet, a closer look at the preference parameters reveals several caveats that come along with typical issues attached to financial data, and that some of these issues seems to drive our results. In particular, deviations are attributable to effects stemming from multicollinearity and coherent under-identification problems, where some of these detrimental effects can be captured up to a certain degree by adjusting the error term specification. Furthermore, additional uncertainty stemming from changing market parameter estimates affects the precision of our estimates for risk preferences and cannot be simply remedied by using a higher standard deviation of the error term or a different assumption regarding its stochastic process. Particularly, if the variance of the error term becomes large, we detect a tendency to identify SP T as utility model providing the best fit to simulated trading sequences. We also find that a frequent issue, namely serial correlation of the residuals, does not seem to be significant. However, we detected a tendency to prefer nesting models over nested utility models, which is particularly prevalent if RDU and EXP O utility models are estimated along with EU T and CRRA utility models.

show abstract

Probability-Preferences in Gambling

Cited by 232 publications

References 0 publications

No risky shift effect with real groups and real risks

No risky shift effect with real groups and real risks

Hellinger distance for fuzzy measures

On the Applicability of Maximum Likelihood Methods: From Experimental to Financial Data

Contact Info

Product

Resources

About