Reference Point Adaptation Research Articles

Reference Point Adaptation and Disposition Effect: Evidence from Institutional Trading

Using a large proprietary database of institutional trades, we investigate whether, and to what extent, the dynamic adaptation of reference point translates into variations in the disposition effect, and establish three key results. First, the propensity to realize losses declines sharply with the magnitude of prior losses due to insufficient adaptation of reference point. Second, recent adverse information accelerates investors’ adaptation to price depreciation and increases investors’ willingness to realize losses. Finally, a priori of losing money in highly speculative investments decreases investors’ aversion to realize losses. Collectively, the findings suggest that both prior outcomes and recent expectations contribute to the reference point adaptation and the variations in disposition effect.

Reference point adaptation: Tests in the domain of security trading

According to prospect theory [Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk, Econometrica, 47, 263–292], gains and losses are measured from a reference point. We attempted to ascertain to what extent the reference point shifts following gains or losses. In questionnaire studies, we asked subjects what stock price today will generate the same utility as a previous change in a stock price. From participants’ responses, we calculated the magnitude of reference point adaptation, which was significantly greater following a gain than following a loss of equivalent size. We also found the asymmetric adaptation of gains and losses persisted when a stock was included within a portfolio rather than being considered individually. In studies using financial incentives within the BDM procedure [Becker, G. M., DeGroot, M. H., & Marschak, J. (1964). Measuring utility by a single-response sequential method. Behavioral Science, 9(3), 226–232], we again noted faster adaptation of the reference point to gains than losses. We related our findings to several aspects of asset pricing and investor behavior.

Intrathecal programmed infusion of Baclofen in spasticity

Indicator based many-objective evolutionary algorithms generally introduce the performance indicator as the selection criterion in environmental selection. In the calculation of some indicators, the reference points as sampled points on Pareto fronts are very important for their calculation. However, it is difficult to obtain good reference points on various types of Pareto fronts. To address this issue, this paper proposes an enhanced-indicator based many-objective evolutionary algorithm with adaptive reference point, termed EIEA. The algorithm proposes a reference point adaptation method to dynamically adapt the reference points for the calculation of indicators. Moreover, the calculation of IGD-NS is enhanced by employing the modified distance calculation to introduce the Pareto compliant which can further comprehensively measure the convergence and diversity. The proposed EIEA adopts Pareto dominance and the enhanced IGD-NS as the first selection criterion and the secondary selection criterion in environmental selection, respectively. The intensive experiments demonstrate that the proposed algorithm has good performance in solving problems with various types of Pareto fronts, surpassing several representative many-objective evolutionary algorithms for many-objective optimization.