Gain-loss Asymmetry Research Articles

Contextual valence influences the neural dynamics of time and magnitude representation during feedback evaluation.

Contextual valence is an important dimension during value-based decision-making. Previous research has revealed behavioral and neural asymmetries between the gain context and the loss context. The present event-related potential study investigated the effects of contextual valence on neural dynamics underlying magnitude and time, two important reward dimensions, during feedback evaluation. Forty-two participants performed a simple guessing task in which they experienced both a gain context wherein high or low rewards were delivered immediately or six months later, and a loss context wherein high or low losses were delivered in the same way. Results showed that in the gain context, time and magnitude information were processed in a parallel way during the time windows of the reward positivity (RewP) and the P3. In the loss context, however, time and magnitude information were processed in a serial way such that time information was encoded during the RewP and P3 periods, whereas magnitude information was not tracked until the time window of the late positive potential. Our findings suggest that the neural dynamics underlying time and magnitude information are distinct between the gain and loss contexts, thus providing a novel perspective for the well-known gain-loss asymmetry.

Gain-loss separability in human- but not computer-based changes of mind

The effect of human-based advice on decision-making represents a “gain-loss asymmetry,” as people tend to conform to others’ advice in the loss than in the gain domain; however, it is unknown whether the same is true for automatically generated advice. To address a research gap in the literature created by ignoring the gain-loss dimension, we compared the utilization of human- and computer-based advices in the gain and loss domains, separately. Sixty-seven college volunteers were given an opportunity to change their initial decision in a gain- or loss-related context after receiving human- or computer-based advice. Event-related potentials were recorded including the N2 (reflecting psychological conflict) and P3 (reflecting subjective confidence) components. Behavioral data revealed a classic “gain-loss asymmetry” effect in the human-based condition, but not in the computer-based condition, indicating that computerized advice utilization remained prominent across different domains. Moreover, the human-based condition showed a larger option-evoked P3 in the gain than in the loss domain, but no difference was found for the computer-based condition; P3 latency was longer in the human-than in the computer-based condition. These findings support the “automation bias” hypothesis (i.e., automations are trusted more than humans), and may help develop automated advice systems.

A Bayesian analysis of gain-loss asymmetry

We perform a quantitative analysis of the gain/loss asymmetry for financial time series by using a Bayesian approach. In particular, we focus on some selected indices and analyse the statistical significance of the asymmetry amount through a Bayesian generalization of the t-test, which relaxes the normality assumption on the underlying distribution. We propose two different models for data distribution, we study the convergence of our method and we provide several graphical representations of our numerical results. Finally, we perform a sensitivity analysis with respect to model parameters in order to study the reliability and robustness of our results. We observe that the magnitude of the asymmetry depends on several factors, such as the considered time-series as well as the threshold parameters used to define the gain/loss asymmetry.

A q-spin Potts model of markets: Gain–loss asymmetry in stock indices as an emergent phenomenon

Spin models of markets inspired by physics models of magnetism, as the Ising model, allow for the study of the collective dynamics of interacting agents in a market. The number of possible states has been mostly limited to two (buy or sell) or three options. However, herding effects of competing stocks and the collective dynamics of a whole market may escape our reach in the simplest models. Here I study a q-spin Potts model version of a simple Ising market model to represent the dynamics of a stock market index in a spin model. As a result, a self-organized gain–loss asymmetry in the time series of an index variable composed of stocks in this market is observed.

Gain-loss asymmetry in delay and effort discounting of different amounts

Loss aversion entails that people attribute greater weight to losses than to equivalent gains. In terms of discounting, it is reflected in a higher discounting rate for gains than for losses. Research on delay discounting indicates that such gain-loss asymmetry may depend on the amount of the outcome being considered. Consequently, here we address the question of how gains and losses are discounted in delay or effort conditions (physical or cognitive) across four outcome amounts. Our results replicate previous findings for intertemporal choices by showing that losses are discounted more slowly than gains, but only for smaller amounts—with no evidence of an asymmetrical evaluation for larger amounts. In physical effort discounting, we found an inverse asymmetry for the smallest amount tested (gains are discounted less steeply than losses). However, this effect was absent for larger amounts. We found no evidence to support a gain-loss asymmetry in the evaluation of gains or losses in cognitive effort. Overall, our findings indicate that loss aversion may not be as pervasive as previously expected, at least when decisions are effort-based.

Mental accounts with horizon and asymmetry preferences

This paper extends mental accounting theory with an investment horizon and asymmetric trade-off between extreme gains and losses. This horizon-asymmetry mental accounting (HAMA) framework widens the spectrum of investors’ optimal portfolio choices considerably. Risk aversion, implied from the mean-variance portfolio theory, and the bond-to-stock ratio decline with the investment horizon. HAMA investors with a large gain–loss asymmetry trade-off are more concerned about skewness and kurtosis rather than variance. To apply the model to United States stock data, we develop a parsimonious semi-parametric version of HAMA that relies on the moments of return distributions. The analysis of optimal portfolios shows that investors who care significantly about upside potential hold asymmetric, leptokurtic, and less diversified allocations.

Losses Loom Larger Than Gains: Neural Correlates Of Behavioral Gain-Loss Asymmetry

Losses Loom Larger Than Gains: Neural Correlates Of Behavioral Gain-Loss Asymmetry

Examining the role of risk in waiting preference and dynamic preference reversal: An experience intertemporal choice study

AbstractShort waits are pervasive in modern life. This study addressed how risk impacts intertemporal decisions that involve short waits (of 72 s or less) and how those decisions change while waiting. We used an experience time‐discounting task sensitive to the impact of risk and which can measure intratrial preference reversals. Three experiments showed that (1) adding uncertainty to outcomes does not change participants' preferences in waiting for a reward, but it reduces their willingness in waiting for a reduction of losses; (2) adding uncertainty to outcomes increases participants' tendency to switch their decisions during the course of waiting; and (3) participants showed no gain–loss asymmetry for risky intertemporal choices.

A Modified Contingent Valuation Method Shrinks Gain-Loss Asymmetry

Large, unpredictably variable gaps between Willingness-to-Accept and Willingness-to-Pay (WTA-WTP gaps) are a methodological concern with the Contingent Valuation Method. The present study investigates WTA-WTP gaps as one manifestation of gain-loss asymmetry: the phenomenon that selling prices exceed buying prices. We investigate some causes of this asymmetry. Using a novel paradigm, and scaled goods, we obtain valuations of three nonmarket goods: one private (Health), and two public (Environment). We systematically explore the effects on gain-loss asymmetry of Good-type (Public vs. Private), Method (Price vs. Choice), and Payment Units (absolute valuation vs. percentage of income). Across methods, gain-loss asymmetry varies by Good-type: it is larger for public goods. We also find that gain-loss asymmetry shrinks, but does not disappear, from Price to Choice. We identify the mechanism of this shrinkage: a bidirectional, asymmetric valuation shift in Gain and in Loss. Eliciting valuations via income percentages instead of absolute values, and reversing the Price/Choice sequence, preserves these effects. Valuations show less variability when elicited as income percentages than when elicited as absolute values. Insofar as smaller and less variable gain-loss asymmetries suggest methodological validity, Choice seems preferable to Price. Further, Income Percentage seems an economically justifiable basis for anchoring contingent valuations.

Waiting in intertemporal choice tasks affects discounting and subjective time perception.

The literature on human delay discounting behavior is dominated by experimental paradigms, which do not impose actual delays. Given that waiting may be aversive even on short timescales, we present a novel delay discounting paradigm to study differences in delay discounting behavior either when real waiting is involved, or not. This paradigm retains the fundamental trade-off between rewards received versus their immediacy. We used hierarchical Bayesian modeling to decompose and test models that separate discounting and subjective time perception mechanisms. We report 2 experiments that also explore the magnitude effect and gain-loss asymmetry. In both experiments, we found greater discounting and nonlinear (convex) time perception in the online waiting task, which required waiting after each choice, compared to a control condition where waiting was deferred until the end of the experiment. Discounting was also measured by a parameter of a hyperbolic-type model and related to reversals of preference between initial desire to wait and then not doing so. These results from our novel paradigm support the emerging view that subjective time perception plays an important role in intertemporal choice in addition to discounting tendencies. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Gain–Loss Asymmetry in Experiential Probability Discounting

Probability discounting is loss in reinforcer value as a function of uncertainty. In typical tasks measuring probability discounting, participants repeatedly choose between a smaller, certain amount and a larger amount at one of several probabilities, and do not experience the outcome they select. Most participants show a gain–loss asymmetry, discounting gains more steeply than losses. We examined whether gain–loss asymmetry also occurred when participants received feedback about the number of points they had gained or lost following choices, and whether discounting rates changed as participants accrued experience of outcomes across the session. We assessed discounting of hypothetical monetary gains and losses twice using a mixed description-experience task. In these tasks, participants chose repeatedly between options that were described, where each choice was then followed by feedback on the number of points gained or lost from the chosen option, but not the unchosen option (i.e. a partial feedback procedure). Neither the first nor second task showed a consistent mean difference in discounting of gains and losses. Discounting in the first task was affected by an interaction of condition order and type of outcome (gains or losses). Furthermore, discounting of losses was more stable across task administrations than discounting of gains. Participants’ tendency to choose the probabilistic option was significantly correlated across conditions. Together, this highlights the crucial role of recent experience of outcomes on probability discounting of gains and losses.

Loss aversion in an agent-based asset pricing model

A well-defined agent-based asset pricing model able to match the widely observed properties of financial time series is valuable for testing the implications of various biases associated with investors' behaviour. Extending one of the most successful models in capturing traders behaviour, we present a new behavioural agent-based asset pricing model. Specifically, we introduce a well-known behavioural bias in the model, loss aversion, and evaluate its implications. First, measuring how close the simulated time series are to its empirical counterparts, we show that the model with loss aversion better matches and explains the properties of real-world financial data, compared with the base model without the behavioural bias. Secondly, we assess the impact of different levels of loss aversion not only on the agents' switching mechanisms, but also on the properties of the time series generated by the model. We demonstrate how for different levels of the loss aversion parameter, the biased agents tend to be driven out of the market at different points in time. Since even the simplest strategies have been shown to survive the competition in an agent-based setting, we can link our findings with the behavioural finance literature, which states that investors' systematic biases lead to unexpected market behaviour, instabilities and systematic errors. Finally, we provide an in-depth analysis of the simulated time series and show the resulting dynamics replicate a rich set of the stylized facts including: absence of autocorrelation, heavy tails, volatility clustering and conditional heavy tails of returns, long memory of absolute returns, as well as volume–volatility relations, gain–loss asymmetry, power-law behaviour and long memory of volume.

Electrophysiological Mechanisms Underlying Time-Dependent Assessments in Moral Decision-Making.

Human decision-making that involves moral dilemmas is a complex process, as individuals try to adhere to their moral values while their actual decisions can be influenced by several situational constraints. When facing a moral conflict that can bring a gain or loss for a decision-maker but a corresponding loss or gain for others, the decision-maker’s choice of resolution strategy lies in its relating to gain-loss asymmetry by placing greater utility weight on his or her immediate gains and delayed losses. Although many neuroimaging studies have unveiled the neural mechanisms that underlie moral decision-making, little attention has been paid to the temporal dynamics of how a decision-maker assesses utility weights differently for a moral (or adaptive) choice that will bring loss (or gain) to himself (and others) when the outcome will be realized in the near versus distant future. This study identifies the electrophysiological mechanisms of time-dependent assessment in individuals’ moral conflict resolution strategies. Twenty-two participants were given a set of moral dilemmas with time intervals that varied from the near future to the distant future. Participants chose between two conflicting options: a self-interest-seeking immoral choice (adaptive) and a principled moral choice (moral). Event-related potentials (ERPs) were recorded, and movement-related potentials (MRPs) were analyzed by being response-locked to individual moral choices. Behavioral results showed that participants took more time to respond and were more likely to make adaptive choices under the near-future condition. When the participants faced moral dilemmas, their brain waves manifested medial frontal negativity (MFN) at early stage ERP of 200–400 ms, possibly reflecting an internal moral conflict. Participants then exhibited larger late positive potentials (LPP) under the near-future condition. In addition, greater effort in implementing motor preparation was found under the near-future condition than under the distant future condition, as supported by the larger Bereitschaftspotential (BP) in the anterior areas. Our results illustrate the temporal dynamics of the electrophysiological mechanisms that underlie time-dependent assessments in moral decision-making, as human brains discount the decision utility of the moral outcomes that will occur in the distant future.

Risk Pricing Under Gain-Loss Asymmetry

Asset prices are derived in closed-form in a framework where agents evaluate risk with gain-loss asymmetry: losses relative to a reference point incur discontinuously more disutility than comparable gains. This asymmetry has a dual impact. First, a level effect: risk prices are made higher by the kink in the preferences. Second, a cross-sectional effect: the pricing of risk is higher (lower) for safer (riskier) assets, so expected returns increase non-linearly with the risk-exposures. This second effect, a crucial departure from standard smooth utility models, is weakened by lower specifications of the reference point and by higher volatilities in aggregate risk.

Use of Electroencephalography for the Study of Gain–Loss Asymmetry in Intertemporal Decision-Making

Intertemporal decision-making refers to the process whereby an individual evaluates and selects among competing alternatives based on the cost and benefit over time. While most previous studies on temporal discounting focused their attention on the gain context, only a few explored the loss context. In the present study, both the event-related potentials (ERPs) and the graph theory analysis were employed to investigate the differences in intertemporal decision-making between the gain and loss frameworks. Our results suggested that participants preferred the short latency/small amount (SS) alternatives and exhibited a smaller discount rate in a loss context compared to a gain framework. Furthermore, our ERP data indicated that the P200 component could constitute a preliminary assessment of the decision-making, related to gain and loss. In contrast, the N2 component was associated with negative emotions and showed significantly bigger amplitudes in the loss context, when compared to the gain framework. Further analyses of brain networks suggested the loss decision-making brain network to have a larger small-worldness index given individuals' loss aversion. Taken together, intertemploral decision-making in a loss context was accompanied by a greater brain response due to the negative emotions linked to loss aversion.

An information-based model for the differential treatment of gains and losses

This study defines reporting conservatism as a higher verification standard for probable gains compared to losses and builds a model that endogenously generates optimal behavior resembling an asymmetric preference for gains versus losses. Our model considers the setting where one party produces a resource and another tries to expropriate it. The key factor determining the extent of the gain-loss asymmetry is the level of information asymmetry or trust between the two parties. The information asymmetry-based results of our model provide a simpler explanation for the vast empirical literature on conservatism, where the bulk of the economic relationships among the parties appear to be information-based with little direct relation to explicit debt contracts, a factor that has been the focus of theoretical arguments. We also suggest new empirical analyzes.

Risk asymmetries in “open science” concept: university technology transfer perspective

Purpose – This paper applies Ahlbrecht and Weber risk asymmetries approach to foundations of Open Science concept. The aim of this study is answering the questions: What are the risk asymmetries in the Open Science evolution process? What are directions of change in Open Science concept? Design/methodology/approach – The paper is prepared in the historical – empirical mainstream. Methodology used in this research was the critical analysis of the state of knowledge based on literature review. Findings – Part I of this paper discusses the framework of the concept of Open Science in research policy. Part II concludes with a brief overview of Open Science concept in university technology transfer process and highlights the risk asymmetries. There were identified three risk asymmetries: in the area of assessment of the quality of the research results, “rapid mode” of increasing of research results in science, intellectual property fraud risk for university. The analysis was made with consideration of two coexisting systems – one still based on OS (OSS – Open Science System) and the other characterized by legal norms (intellectual property rights) of research (IPRS – Intellectual Property Rights System). In one system (OS) appears freedom to “openness” and in the other system (IPRS) there is obligatory in the evaluation of scientific achievements measured as citation in the top journals or obtained patents. Originality/value – The purpose of the study was completed. Open Science considerations were in the context of unprecedented literature. In the study there were used assumptions of Akerlof theory of information asymmetry and Ahlbrecht Weber risk asymmetries, that is as follows: Short-term Long-term asymmetry, Certainty-Risk asymmetry, Gain-Loss asymmetry. There were also proposed Public – Private risks asymmetry.

Time-scale effects on the gain-loss asymmetry in stock indices.

The gain-loss asymmetry, observed in the inverse statistics of stock indices is present for logarithmic return levels that are over 2%, and it is the result of the non-Pearson-type autocorrelations in the index. These non-Pearson-type correlations can be viewed also as functionally dependent daily volatilities, extending for a finite time interval. A generalized time-window shuffling method is used to show the existence of such autocorrelations. Their characteristic time scale proves to be smaller (less than 25 trading days) than what was previously believed. It is also found that this characteristic time scale has decreased with the appearance of program trading in the stock market transactions. Connections with the leverage effect are also established.

Gain-loss asymmetry in neural correlates of temporal discounting: An approach-avoidance motivation perspective.

Gain-loss asymmetry in temporal discounting (i.e., when individuals discount gains more than losses) has been implicated in numerous problematic and addictive behaviors, resulting in enormous personal and societal costs. On the basis of findings from a previous study, we speculated that approach-avoidance motivation would modulate gain-loss asymmetry. To test this speculation, we examined the effects of motivation on gain-loss asymmetry by analyzing functional connectivity. We found that approach and avoidance motivation were negatively associated with functional connectivity between the medial orbitofrontal cortex (MOFC) and the dorsolateral prefrontal cortex and functional connectivity between the MOFC and the posterior parietal cortex (PPC) in the gain domain. Only avoidance motivation was found to be positively associated with functional connectivity between the medial prefrontal cortex (MPFC) and the posterior cingulate cortex (PCC) as well as between the MPFC and the insula in the loss domain. Our findings suggest that the relationships of approach-avoidance motivation and neural correlates yielded an asymmetrical pattern between the gain and loss domains in temporal discounting. Thus, we provide new insight into understanding gain-loss asymmetry in temporal discounting.

Inter- and intra-domain horizontal gene transfer, gain-loss asymmetry and positive selection mark the evolutionary history of the CBM14 family.

Protein-carbohydrate interactions are ubiquitous in nature and at the core of many physiological processes of profound importance to health and disease. Specificity in protein-carbohydrate interactions is conferred by carbohydrate-binding modules (CBMs) that can accurately discriminate among the multitude of saccharides found in nature, thus targeting proteins to their particular substrates. Family 14 carbohydrate-binding modules (CBM14s), more specifically, are short modules that bind explicitly to chitin, the second most abundant carbohydrate in nature. Although considerable effort has been placed in elucidating protein-carbohydrate interactions at the molecular level for biological and biotechnological applications, in contrast the evolutionary relationships among these modules are minimally understood. Using the CBM14 family as an example, here we describe one of the first global molecular evolutionary analyses of a CBM family across all domains of life, with an emphasis on its origin, taxonomic distribution and pattern of diversification as a result of gene and module duplication, and positive selection. Our genome-wide searches recovered an impressive number of CBM14s from diverse lineages across nearly all domains of life. However, their highly disseminated distribution in taxa outside the Opisthokonta group strongly suggests a later evolutionary origin and elevated rates of inter- and intra-domain horizontal gene transfer. Moreover, accelerated rates of asymmetric gains and losses reveal a dynamic mode of birth-and-death evolution, whereas positive selection acting on paralogous CBM14-containing proteins suggest changes in substrate specificity and an increase in the functional promiscuity of this ancient CBM family. The importance of these results is discussed.