Topic
Loss aversion
About: Loss aversion is a research topic. Over the lifetime, 2898 publications have been published within this topic receiving 115198 citations.
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TL;DR: This paper examined how the presentation of investment results affects risk taking using an experiment in which participants view results either asset by asset or aggregated into a portfolio result, and found that separating investment results by asset decreases subsequent risk taking.
Abstract: We examine how the presentation of investment results affects risk taking using an experiment in which participants view results either asset by asset or aggregated into a portfolio result. Our experiment examines the investment choices of a nationwide sample of 249 participants in a simulation of investing for retirement. Segregating investment results by asset decreases subsequent risk taking. Those presented segregated results lower their equity proportion by 4.21% and their portfolio volatility by 0.88%. Both decreases are 8% of the mean levels of risk taking, 50.59% and 10.85% respectively. At the beginning of the simulation, we present historical results of the investment options either asset by asset or aggregated into portfolios. Among the small number of participants who spend a significant amount of time studying these historic results, segregating results lowers their equity proportion by 9.81%. Our results are a challenge to fully rational theories of investment choice, but are consistent with a combination of three aspects of prospect theory based models: loss aversion, narrow framing of individual-asset results, and diminishing sensitivity to aggregated gains and losses. Our experiment never varies the presentation of investment results across time, thus our results are distinct from the effect of myopic loss aversion.
28 citations
TL;DR: In this paper, the authors studied the wealth and pricing implications of loss aversion in the presence of arbitrageurs with Epstein-Zin preferences and found that loss aversion affects an investor's survival prospects mainly through its effect on the investor's portfolio holdings.
28 citations
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TL;DR: An open tournament for prediction of human choices in fundamental economic decision tasks is presented and it is suggested that integration of certain behavioral theories as features in machine learning systems provides the best predictions.
Abstract: Behavioral decision theories aim to explain human behavior. Can they help predict it? An open tournament for prediction of human choices in fundamental economic decision tasks is presented. The results suggest that integration of certain behavioral theories as features in machine learning systems provides the best predictions. Surprisingly, the most useful theories for prediction build on basic properties of human and animal learning and are very different from mainstream decision theories that focus on deviations from rational choice. Moreover, we find that theoretical features should be based not only on qualitative behavioral insights (e.g. loss aversion), but also on quantitative behavioral foresights generated by functional descriptive models (e.g. Prospect Theory). Our analysis prescribes a recipe for derivation of explainable, useful predictions of human decisions.
28 citations
TL;DR: In this article, the authors investigated the impact of behavioral biases on investor's financial decision making and concluded that Confirmation, Illusion of control, Excessive optimism, Overconfidence biases have direct impact on the investor's decision making while status quo, Loss aversion and Mantel accounting biases have no impact according to data collected from financial institutions.
Abstract: The study aimed to investigate the impact of behavioral biases on investor’s financial decision making. Current research studies the behavioral biases including overconfidence, confirmation, and illusion of control, loss aversion, mental accounting, status quo and excessive optimism. The study is significant for the investors, policy makers, investment advisors, and bankers. Empirical data has been collected through administrating a questionnaire. Correlation and Linear regression model techniques are used to investigate whether investor decision making is affected by these biases. The study concluded that the Confirmation, Illusion of control, Excessive optimism, Overconfidence biases have direct impact on the investor’s decision making while status quo, Loss aversion and Mantel accounting biases have no impact according to data collected from financial institutions.
28 citations
TL;DR: In this paper, the authors examine how the direction of price changes affects the value people place on avoiding renewable energy externalities in Poland and investigate the influence of individuals' financial loss aversion and financial risk preferences on this valuation, finding that the more risk seeking people are in a financial domain the more they are willing to pay for proposed changes in renewable energy development, at the same time people who are more risk averse require less compensation before they accept externalities from renewable electricity production.
28 citations