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Maximizing Wealth and Happiness: Improving Investor Decisions Through Improved Affective Forecasting

Please use this identifier to cite or link to this item: http://hdl.handle.net/1811/48340

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Title: Maximizing Wealth and Happiness: Improving Investor Decisions Through Improved Affective Forecasting
Creators: Easwar, Karthik
Advisor: Burnkrant, Robert
Issue Date: 2011-03
Abstract: Investor behavior has long been plagued by a conservatism that keeps individuals from maximizing their wealth. We examine how experience and explicit feedback can reduce two of the main impediments to successful investor decision making: loss aversion and myopia. Consistent with Kermer’s et al. (2006) claim that loss aversion is a symptom of poor affective forecasting, we are able to demonstrate that poor affective forecasting undermines investor decision-making by fueling loss aversion and inspiring myopic and suboptimal investment decisions. Importantly, we are also able to show that explicit feedback illustrating the gap between an individual’s affective forecast and actual affective response reduces affective forecasting errors. Once investors become better affective forecasters, they are less inclined to fear a temporary setback, which is observed through reduced loss aversion and investment decisions that focus on maximizing long-term earnings. In other words, improving affective forecasting can help consumers maximize both wealth and happiness.
Embargo: A three-year embargo was granted for this item.
Series/Report no.: 2011 Edward F. Hayes Graduate Research Forum. 25th
Keywords: Affect
Prospect Theory
Description: Business: 1st Place (The Ohio State University Edward F. Hayes Graduate Research Forum)
URI: http://hdl.handle.net/1811/48340
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