Pls answer all parts for UPVOTE a) The efficient market hypothesis predicts that
ID: 1138841 • Letter: P
Question
Pls answer all parts for UPVOTE
a) The efficient market hypothesis predicts that “the future returns on the two portfolios, the Winners and the Losers, should be the same since you are not supposed to be able to predict changes in stock prices from past returns.” Thaler (2018) mentioned that he and his coauthors had a different prediction. What was their prediction? Explain the rationale behind their prediction
b) Define the uncertainty effect (UE). What are the three possible reasons for the UE? Simonsohn (2009) examined the rationale behind the UE using experiments. Summarize the findings from the experiments.
c) Briefly explain the DRM "Day Reconstruction Method"? What are the advantages of this method compared to other methods related to Behavioral Economics?
Explanation / Answer
Ans. C).
The Day Reconstruction Method (DRM) is designed to collect data describing the experiences a person has on a given day, through a systematic reconstruction conducted on the
following day. The DRM builds on the strengths of time-budget measurement (Juster &Stafford, 1985; Robinson & Godbye, 1997) and experience sampling (Stone, Shiffman, &DeVries, 1999), and employs techniques grounded in cognitive science. Key advantages of the DRM include:
• Joint assessment of activities and subjective experiences
• Information about the duration of each experience, allowing for duration weighted analyses of experiences
• Lower respondent burden than typical for experience sampling methods
• More complete coverage of the day than typical for experience sampling
methods
• Lower susceptibility to retrospective reporting biases than typical for global reports of daily experiences
• High flexibility in adapting the content of the instrument to the needs of the satisfy study. The Day Reconstruction Method (DRM) for assessing daily experience and subjective well-being is reviewed. The DRM is a promising method as it assesses feelings within situations and activities, and therefore goes beyond asking who is happy to asking when they are happy. The technique might be less burdensome on respondents than experience-sampling, and might reduce memory biases that are inherent in global recall of feelings. However, evidence for the validity and reliability of the DRM is limited and is not entirely supportive. Research is needed on the psychometrics of the DRM, for example by comparing it to mobile phone assessments and other forms of experience-sampling, as well as to global reports of feelings in situations. Conceptual issues with computing overall subjective well-being by weighting a respondent’s activity scores by the time spent in them are discussed. Despite the promises of the DRM, the many unresolved issues with it and the alternative of using on-line electronic experience-sampling techniques suggest that more research is needed before the value of the DRM is established. Ans. B ) A state of uncertainty where some possible outcomes have an undesiredeffect or significant loss. Measurement of risk. ... It will appear that a measurable uncertainty, or 'risk' proper, as we shall use the term, is so far different from an unmeasurable one that it is not in effect anuncertainty at all. The uncertainty principle says that we cannot measure the position (x) and the momentum (p) of a particle with absolute precision. The more accurately we know one of these values, the less accurately we know the other. Individual valuation of a binary lottery at values less than the lottery's worst outcome has been designated as the "uncertainty effect". Our paper aims to explore the boundary conditions of the uncertainty effect by investigating a plausible underlying process and proposing two possible methods. First, we examine how providing an exogenous evaluation opportunity prior to judging the value of the lottery affects individuals' judgments, and find that first valuing the worst outcome and then the lottery eliminates the uncertainty effect. Second, we explore whether introducing additional cognitive load dampens how far decision makers correct their initial evaluations, and find that additional cognitive load is able to eliminate the uncertainty effect