Investigating the Impact of Monetary Rewards on Choice Behavior, Decision Making and Risk Management
What biological and social mechanisms influence our decision-making processes? Where do our judgment and rationale for our choices stem from, such as in the context of money management? Can a better understanding of these natural and social phenomena improve our finances? In this project, I investigated risk decisions and their implications for financial professionals such as investors, traders, or brokers. I am using the Choices13K data set, an open data source retrieved from GitHub that is among the most expansive human decision response on risk-choice problems datasets with at least 13,000 responses.
In this study, the participants participated in a series of experiments where they faced two options: a risk-averse or risk-seeking gamble. Each gamble had a different set of possible outcomes. For example, if they chose Gamble A, there was a certain probability of a 100% chance of a $0 return (risk-averse); however, if they chose Gamble B, there was a lottery outcome with a 50-50% chance of winning or losing $100 (risk-seeking). My research question studies if and how participants' responses to the risky-choice problem contrast when there are known probabilities (certainty) versus unknown probabilities (ambiguity and lottery).
I use neuroscience, psychology, and biology research to investigate the underlying processes that impact decision-making in the context of financial decisions and risk management. In neuroscience, I investigated how desire activates our neural reward and dopamine systems, which influences the limbic system and neocortex, where some decision-making occurs. The field of psychology demonstrates that behavioral biases and behavioral finance protocols help researchers observe how emotions and pleasure-seeking approach vs. loss aversion approach impact decision-making. And lastly, within the study of biology and decision-making, I studied interoceptive abilities and genetics, such as testosterone, and how the levels of each explain the nuances of financial decision-making. In my methodology, I perform a t-test, logistic regression, and a correlation matrix to respond to my research question.
How do the participant's responses to the Gamble B risky-choice problem, with unknown probabilities (lottery), contrast when the participant receives the feedback (Feedback) or information (Amb)?
The alternative hypothesis states at least one different mean score of participants' choice Gamble B (bRate) depending on whether they receive feedback or information about the outcomes of the variables. The true difference between the group means would contrast and therefore not include zero to indicate the means vary based on the treatment provided, the treatment being the feedback or information levels.
Based on the literature, I support the alternative hypothesis and believe there will be a difference in the mean score of participant's choice of Gamble B (bRate) depending on the treatment and level provided: whether they receive Feedback (receive or did not receive) or Amb (none or complete information). Kahneman and Tversky's research on decision-making and risk perception indicates that the feedback and perception used to frame risky-choice problems influence the participant's choice.
I would like to thank Professor Dutt for her support and patience throughout this seminar and research design. I want to thank the Celebrating Collaborations committee for allowing me to present my preliminary findings and gain experience sharing my literature and statistical methods with an audience. Third, I would like to thank the professors in the Statistical and Data Science department that have me previously and have prepared me for this seminar. And lastly, I would like to thank my family and friends.