AIM: Psychiatric symptoms are often accompanied by impairments in decision-making to attain rewards and avoid losses. However, due to the complex nature of mental disorders (e.g., high comorbidity), symptoms that are specifically associated with deficits in decision-making remain unidentified. Furthermore, the influence of psychiatric symptoms on computations underpinning reward-seeking and loss-avoidance decision-making remains elusive. Here, we aim to address these issues by leveraging a large-scale online experiment and computational modeling. METHODS: In the online experiment, we recruited 1900 non-diagnostic participants from the general population. They performed either a reward-seeking or loss-avoidance decision-making task, and subsequently completed questionnaires about psychiatric symptoms. RESULTS: We found that one trans-diagnostic dimension of psychiatric symptoms related to compulsive behavior and intrusive thought (CIT) was negatively correlated with overall decision-making performance in both the reward-seeking and loss-avoidance tasks. A deeper analysis further revealed that, in both tasks, the CIT psychiatric dimension was associated with lower preference for the options that recently led to better outcomes (i.e. reward or no-loss). On the other hand, in the reward-seeking task only, the CIT dimension was associated with lower preference for recently unchosen options. CONCLUSION: These findings suggest that psychiatric symptoms influence the two types of decision-making, reward-seeking and loss-avoidance, through both common and distinct computational processes.

Ecstatic epilepsy is a rare form of focal epilepsy in which the aura (beginning of the seizures) consists of a blissful state of mental clarity/feeling of certainty. Such a state has also been described as a "religious" or mystical experience. While this form of epilepsy has long been recognized as a temporal lobe epilepsy, we have accumulated evidence converging toward the location of the symptomatogenic zone in the dorsal anterior insula during the 10 last years. The neurocognitive hypothesis for the genesis of a mental clarity is the suppression of the interoceptive prediction errors and of the unexpected surprise associated with any incoming internal or external signal, usually processed by the dorsal anterior insula. This mimics a perfect prediction of the world and induces a feeling of certainty. The ecstatic epilepsy is thus an amazing model for the role of anterior insula in uncertainty and surprise.

We consider Theory of Mind (ToM), the ability to correctly predict the intentions of others. To an important degree, good ToM function requires abstraction from one's own particular circumstances. Here, we posit that such abstraction can be transferred successfully to other, non-social contexts. We consider the disposition effect, which is a pervasive cognitive bias whereby investors, including professionals, improperly take their personal trading history into account when deciding on investments. We design an intervention policy whereby we attempt to transfer good ToM function, subconsciously, to personal investment decisions. In a within-subject repeated-intervention laboratory experiment, we record how the disposition effect is reduced by a very significant 85%, but only for those with high scores on the social-cognitive dimension of ToM function. No such transfer is observed in subjects who score well only on the social-perceptual dimension of ToM function. Our findings open up a promising way to exploit cognitive talent in one domain in order to alleviate cognitive deficiencies elsewhere.

Changes in risk-taking behaviour based on interim performance are examined in high-stakes competition. A real options framework is used to provide a richer characterisation of risk-taking behaviour than examined in extant studies. This framework is applied to an examination of ball-by-ball data from 1207 cricket matches. Consistent with modelled expectations, risk taking is found to increase (decrease) at a decreasing rate following below par (above par) interim performance. This result is especially strong in situations where the resources remaining are low, a result predicted by the real options model.

This paper introduces four metrics for quantifying the adequacy of retirement savings, taking into account all major sources of retirement income. We then apply them to projections of expected future retirement income streams of a representative sample of the Australian population aged 40 and above. We find that omitting one or more pillars of savings significantly biases estimates of retirement savings adequacy. We also find that the four metrics are only weakly correlated with key commonly used indicators of financial well‐being, in particular current income and net worth. Our analysis also points to several shortcomings of the widely used income replacement ratio as an indicator of savings adequacy.

We examine the short‐term response to recommendation changes on the Australian Securities Exchange, a central limit order market. In both central limit order markets and dealer‐driven markets, clients may reward the recommending broker with increased trade volumes. But a central limit order market does not have mandatory market makers and hence provides greater opportunity to free ride. We find evidence supporting the hypothesis that recommending brokers are rewarded with higher trade volumes and brokerage commission. Consistent with the tipping hypothesis, these rewards are concentrated in the period shortly before the release. There is no evidence of free riding.

This paper examines the impacts of M&A advisors’ industry expertise on firms’ choice of advisors in mergers and acquisitions. We show that an investment bank's expertise in merger parties’ industries increases its likelihood of being chosen as an advisor, especially when the acquisition is more complex, and when a firm in M&A has less information about the merger counterparty. However, due to the concerns about information leakage to industry rivals through M&A advisors, acquirers are reluctant to share advisors with rival firms in the same industry, and they are more likely to switch to new advisors if their former advisors have advisory relationship with their industry rivals. In addition, we document that advisors with more industry expertise earn higher advisory fees and increase the likelihood of deal completion.

This article is motivated by uncertainty in experimental determinations of the gravitational constant, G, and numerous anomalies of up to 0.5 percent in Newtonian gravitational force on bodies within the solar system. The analysis sheds new light through six natural experiments within the solar system, which draw on published reports and astrophysical databases, and involve laboratory determinations of G, orbital dynamics of the planets and the moons of Earth and Mars, and non-gravitational acceleration (NGA) of ‘Oumuamua and comets. In each case, values are known for all variables in Newton’s Law F=G·M·mR2, except for the gravitational constant, G. Analyses determine the gravitational constant’s observed value, G^, which—across the six settings—varies with the mass of the smaller, moving body, m, so that G^=G×0.998+0.00016×lnm. While further work is required, this examination shows a scale-related Newtonian gravity effect at scales from benchtop to Solar System, which contributes to the understanding of symmetry in gravity and has possible implications for Newton’s Laws, dark matter, and formation of structure in the universe.

Over the last 15 years, a revolution has been taking place in neuroscience, whereby models and methods of economics have led to deeper insights into the neurobiological foundations of human decision-making. These have revealed a number of widespread mis-conceptions, among others, about the role of emotions. Furthermore, the findings suggest that a purely behavior-based approach to studying decisions may miss crucial features of human choice long appreciated in biology, such as Pavlovian approach. The findings could help economists formalize elusive concepts such as intuition, as I show here for financial "trading intuition."

Belief updating entails the incorporation of new information about the environment into internal models of the world. Bayesian inference is the statistically optimal strategy for performing belief updating in the presence of uncertainty. An important open question is whether the use of cognitive strategies that implement Bayesian inference is dependent upon motivational state and, if so, how this is reflected in electrophysiological signatures of belief updating in the brain. Here, we recorded the EEG of participants performing a simple reward learning task with both monetary and nonmonetary instructive feedback conditions. Our aim was to distinguish the influence of the rewarding properties of feedback on belief updating from the information content of the feedback itself. A Bayesian updating model allowed us to quantify different aspects of belief updating across trials, including the size of belief updates and the uncertainty of beliefs. Faster learning rates were observed in the monetary feedback condition compared to the instructive feedback condition, while belief updates were generally larger, and belief uncertainty smaller, with monetary compared to instructive feedback. Larger amplitudes in the monetary feedback condition were found for three ERP components: the P3a, the feedback-related negativity, and the late positive potential. These findings suggest that motivational state influences inference strategies in reward learning, and this is reflected in the electrophysiological correlates of belief updating.

This article explains why short-term bank deposits, made on behalf of members by institutional superannuation funds, receive a substantially lower interest rate than deposits made directly by individuals and self-managed super funds. We estimate the potential negative effect on the ultimate retirement savings of those members. We show how extending the Financial Claims Scheme to provide coverage to such deposits on a ‘look through’ basis would remove that inequity and should, in principle, remove the rationale for the payment of lower interest rates. We consider the political arguments against extending the scheme and argue that these are of limited merit.

This paper proposes an intuitive rationale for late bidding in online venues. The expected surplus from bidding on subsequent auctions for equivalent items creates an option value to losing the current auction. This option is dynamic due to the stochastic arrival of new auctions and early bids on later-closing auctions. We demonstrate that late bidding can be optimal given the decentralised and heterogeneous nature of online auctions, in which the option value is exogenous to an individual bidder’s actions. Late bidding precludes the bidder from being locked into a suboptimal bid as her opportunity set evolves.

Using a novel measure of own-investor secrecy, we find that non-disclosure to a fund's own investors, unlike non-disclosure to the public, does not signal hedge fund skill. Own-investor secretive funds do not significantly outperform transparent funds through an up market, and they significantly underperform their (sub)strategy-matched peers through the down market of the Global Financial Crisis. These results are robust to using factor models and controls for fund illiquidity, complexity, concentration, size, and leverage. These patterns are consistent with funds loading on option-like risks, and additional tests show that secretive funds are exposed to risks akin to put-option writing. Measures of skill proposed by prior research also do not suggest secretive funds possess superior skill. Through the up-market portion of our sample, secretive funds have lower ow-to-performance sensitivity, even controlling for illiquidity, suggesting that investors view secretive and transparent funds differently.

CEOs (chief executive officers) are paid more if they outperform other firms in their blockholders’ portfolios. For every percentage point by which their own firm's return exceeds the return of the largest blockholder's basket of investments in a year, their compensation increases by over $9,800. Once we benchmark to this portfolio, industry returns and own firm returns are of little importance. When the firm is a larger portion of the blockholder's portfolio and when the blockholder is experienced, the reward for outperforming the blockholder's portfolio is greater. Our results are robust to alternate industry classifications and definitions of blockholders.

There have been claims that British capital was not well deployed in Victorian Britain. There was, allegedly, a lack of support for new and dynamic companies in comparison to the situation in Germany and the US. We find no evidence to support these claims. The London Stock Exchange welcomed young, old, domestic, and foreign firms. It provided funds to firms in old, existing industries as well as patenting firms in ‘new‐tech’ industries at similar costs of capital. If investors did show a preference for older and foreign firms, it was because those firms offered investors better long‐run performance. In addition, we show some evidence that investors who worked in the same industry and lived close to the firm going public were allotted more shares in high‐quality initial public offerings.

We search for a definition of the downside risk premium analogous to the Pratt–Arrow definition of the risk premium. However, even in the local analysis difficulties arise. To overcome these, we propose a definition based on the difference between two gambles. Further, a global analysis reveals that higher‐order terms affect the downside risk premium and these cannot be ignored. We show that all five measures of the intensity of downside risk aversion that have been suggested are invalid in the case of the global analysis.

Business succession is one of the primary management challenges for family firms. However, many family firms fail at this task because of financial issues. Although a vast number of studies have investigated the succession process, research thus far has failed to determine how and why family firms select particular forms of financing for succession-related expenditures. Accordingly, this study conceptually and empirically investigates succession financing. We introduce a conceptual framework that investigates the reasons behind an owner-manager’s intent to use debt for succession financing. Specifically, our model accounts for general and succession-related personal factors. However, we also include a set of firm-specific financing behavioral controls in our research. The empirical results are derived from a sample of 187 German family firms, and the results highlight financial knowledge, attitudes, succession experience, and succession planning as significant determinants of the owner-managers’ debt usage intentions. The implications and avenues for future research are discussed.

Career choices affect not only our financial status but also our future well-being. When making these choices, individuals evaluate their willingness to obtain a job (i.e., job values), primarily driven by simulation of future pay and interest. Despite the importance of these decisions, their underlying neural mechanisms remain unclear. In this study, we examined the neural representation of pay and interest. Forty students were presented with 80 job names and asked to evaluate their job values while undergoing functional magnetic resonance imaging (fMRI). Following fMRI, participants rated the jobs in terms of pay and interest. The fMRI data revealed that the ventromedial prefrontal cortex (vmPFC) was associated with job value representation, and the ventral and dorsal regions of the posterior cingulate cortex (PCC) were associated with pay and interest representations, respectively. These findings suggest that the neural computations underlying job valuation conform to a multi-attribute decision-making framework, with overall value signals represented in the vmPFC and the attribute values (i.e., pay and interest) represented in specific regions outside the vmPFC, in the PCC. Furthermore, anatomically distinct representations of pay and interest in the PCC may reflect the differing roles of the two subregions in future simulations.

The first macroscopic object observed to have come from outside the solar system slipped back out of sight in early 2018. 1I/2017 U1 ‘Oumuamua offered a unique opportunity to test understanding of gravity, planetary formation and galactic structure against a true outlier, and astronomical teams from around the globe rushed to study it. Observations lasted several months and generated a tsunami of scientific (and popular) literature. The brief window available to study ‘Oumuamua created crisis-like conditions, and this paper makes a comparative study of techniques used by cosmologists against those used by financial economists in qualitatively similar situations where data conflict with the current paradigm. Analyses of ‘Oumuamua were marked by adherence to existing paradigms and techniques and by confidence in results from self and others. Some, though, over-reached by turning uncertain findings into graphic, detailed depictions of ‘Oumuamua and making unsubstantiated suggestions, including that it was an alien investigator. Using a specific instance to test cosmology’s research strategy against approaches used by economics researchers in comparable circumstances is an example of reverse econophysics that highlights the benefits of an extra-disciplinary lens.

Intertemporal choice involves deciding between smaller, sooner and larger, later rewards. People tend to prefer smaller rewards that are available earlier to larger rewards available later, a phenomenon referred to as temporal or delay discounting. Despite its ubiquity in human and non-human animals, temporal discounting is subject to considerable individual differences. Here, we provide a critical narrative review of this literature and make suggestions for future work. We conclude that temporal discounting is associated with key socio-economic and health-related variables. Regarding personality, large-scale studies have found steeper temporal discounting to be associated with higher levels of self-reported impulsivity and extraversion; however, effect sizes are small. Temporal discounting correlates negatively with future-oriented cognitive styles and inhibitory control, again with small effect sizes. There are consistent associations between steeper temporal discounting and lower intelligence, with effect sizes exceeding those of personality or cognitive variables, although socio-demographic moderator variables may play a role. Neuroimaging evidence of brain structural and functional correlates is not yet consistent, neither with regards to areas nor directions of effects. Finally, following early candidate gene studies, recent GWAS approaches have revealed the molecular genetic architecture of temporal discounting to be more complex than initially thought. Overall, the study of individual differences in temporal discounting is a maturing field that has produced some replicable findings. Effect sizes are small-to-medium, necessitating future hypothesis-driven work that prioritizes large samples with adequate power calculations. More research is also needed regarding the neural origins of individual differences in temporal discounting as well as the mediating neural mechanisms of associations of temporal discounting with personality and cognitive variables.

BACKGROUND: Reliable information on the incidence of induced abortion in India is lacking. Official statistics and national surveys provide incomplete coverage. Since the early 2000s, medication abortion has become increasingly available, improving the way women obtain abortions. The aim of this study was to estimate the national incidence of abortion and unintended pregnancy for 2015. METHODS: National abortion incidence was estimated through three separate components: abortions (medication and surgical) in facilities (including private sector, public sector, and non-governmental organisations [NGOs]); medication abortions outside facilities; and abortions outside of facilities and with methods other than medication abortion. Facility-based abortions were estimated from the 2015 Health Facilities Survey of 4001 public and private health facilities in six Indian states (Assam, Bihar, Gujarat, Madhya Pradesh, Tamil Nadu, and Uttar Pradesh) and from NGO clinic data. National medication abortion drug sales and distribution data were obtained from IMS Health and six principal NGOs (DKT International, Marie Stopes International, Population Services International, World Health Partners, Parivar Seva Santha, and Janani). We estimated the total number of abortions that are not medication abortions and are not obtained in a health facility setting through an indirect technique based on findings from community-based study findings in two states in 2009, with adjustments to account for the rapid increase in use of medication abortion since 2009. The total number of women of reproductive age and livebirth data were obtained from UN population data, and the proportion of births from unplanned pregnancies and data on contraceptive use and need were obtained from the 2015-16 National Family Health Survey-4. FINDINGS: We estimate that 15·6 million abortions (14·1 million-17·3 million) occurred in India in 2015. The abortion rate was 47·0 abortions (42·2-52·1) per 1000 women aged 15-49 years. 3·4 million abortions (22%) were obtained in health facilities, 11·5 million (73%) abortions were medication abortions done outside of health facilities, and 0·8 million (5%) abortions were done outside of health facilities using methods other than medication abortion. Overall, 12·7 million (81%) abortions were medication abortions, 2·2 million (14%) abortions were surgical, and 0·8 million (5%) abortions were done through other methods that were probably unsafe. We estimated 48·1 million pregnancies, a rate of 144·7 pregnancies per 1000 women aged 15-49 years, and a rate of 70·1 unintended pregnancies per 1000 women aged 15-49 years. Abortions accounted for one third of all pregnancies, and nearly half of pregnancies were unintended. INTERPRETATION: Health facilities can have a greater role in abortion service provision and provide quality care, including post-abortion contraception. Interventions are needed to expand access to abortion services through better equipping existing facilities, ensuring adequate and continuous supplies of medication abortion drugs, and by increasing the number of trained providers. In view of how many women rely on self-administration of medication abortion drugs, interventions are needed to provide women with accurate information on these drugs and follow-up care when needed. Research is needed to test interventions that improve knowledge and practice in providing medication abortion, and the Indian Government at the national and state level needs to prioritise improving policies and practice to increase access to comprehensive abortion care and quality contraceptive services that prevent unintended pregnancy. FUNDING: Government of UK Department for International Development (until 2015), the David and Lucile Packard Foundation, the John D. and Catherine T. MacArthur Foundation, and the Ford Foundation.

Unintended pregnancy accounts for more than 40% of the total pregnancies worldwide. An Unintended pregnancy can have serious implications on women and their families. With more than one-fourth of the children in India born out of unintended pregnancies such pregnancies are considered to be one of the major public health concerns today. The present study is aimed at determining major predictors of unintended pregnancy among currently pregnant ever-married women in India. The present study has used National Family Health Survey (NFHS) data, conducted by the International Institute for Population Sciences (IIPS), Mumbai, to show the trend, pattern and determinants of mistimed and unwanted pregnancies. Bivariate and multinomial logistic regression model have been used with the help of Stata 13 software. The results show that the likelihood of a mistimed pregnancy is more prevalent among young women whereas the prevalence of unwanted pregnancy is observed more among the women aged 35 years or more. The results also show that the risk of experiencing mistimed pregnancy decreases if the woman belongs to 'other' castes and has higher education. The likelihood of unwanted pregnancy decreases among married women aged 18 years and above, those women having higher education, some autonomy and access to any mode of mass communication. Knowledge of these predictors of mistimed and unwanted pregnancy will be helpful in identifying the most vulnerable group and prioritize the intervention strategies of the reproductive health programmes for the population in need.

BACKGROUND: In India, malaria is not uniformly distributed. Chhattisgarh is a highly malarious state where both Plasmodium falciparum and Plasmodium vivax are prevalent with a preponderance of P. falciparum. Malaria in pregnancy (MIP), especially when caused by P. falciparum, poses substantial risk to the mother and foetus by increasing the risk of foetal death, prematurity, low birth weight (LBW), and maternal anaemia. These risks vary between areas with stable and unstable transmission. The specific objectives of this study were to determine the prevalence of malaria, its association with maternal and birth outcomes, and use of anti-malarial preventive measures for development of evidence based interventions to reduce the burden of MIP. METHODS: A cross-sectional study of pregnant women presenting to antenatal clinics (ANC) or delivery units (DU), or hospitalized for non-obstetric illness was conducted over 12 months in high (Bastar) and low (Rajnandgaon) transmission districts in Chhattisgarh state. Intensity of transmission was defined on the basis of slide positivity rates with a high proportion due to P. falciparum. In each district, a rural and an urban health facility was selected. RESULTS: Prevalence of peripheral parasitaemia was low: 1.3% (35/2696) among women at ANCs and 1.9% at DUs (19/1025). Peripheral parasitaemia was significantly more common in Bastar (2.8%) than in Rajnandgaon (0.1%) (p < 0.0001). On multivariate analysis of ANC participants, residence in Bastar district (stable malaria transmission) was strongly associated with peripheral parasitaemia (adjusted OR [aOR] 43.4; 95% CI, 5.6-335.2). Additional covariates associated with parasitaemia were moderate anaemia (aOR 3.7; 95% CI 1.8-7.7), fever within the past week (aOR 3.2; 95% CI 1.2-8.6), and lack of formal education (aOR 4.6; 95% CI 2.0-10.7). Similarly, analysis of DU participants revealed that moderate anaemia (aOR 2.5; 95% CI 1.1-5.4) and fever within the past week (aOR 5.8; 95% CI 2.4-13.9) were strongly associated with peripheral and/or placental parasitaemia. Malaria-related admissions were more frequent among pregnant women in Bastar, the district with greater malaria prevalence (51% vs. 11%, p < 0.0001). CONCLUSIONS: Given the overall low prevalence of malaria, a strategy of enhanced anti-vector measures coupled with intermittent screening and targeted treatment during pregnancy should be considered for preventing malaria-associated morbidity in central India.

Up to a third of patients undergoing coronary angiography for angina-like chest pain are found to have normal coronary arteries and a substantial proportion of these individuals continue to consult and even attend emergency departments. Initially, these patients are usually seen by cardiologists but with accumulating evidence that the pain might have a gastrointestinal origin, it may be more appropriate for them to be cared for by the gastroenterologist once a cardiological cause has been excluded. This review covers the assessment and management of this challenging condition, which includes a combination of education, reassurance, and pharmacotherapy. For the more refractory cases, behavioral treatments, such as cognitive behavioral therapy or hypnotherapy, may have to be considered.

In traditional Reinforcement Learning (RL), agents learn to optimize actions in a dynamic context based on recursive estimation of expected values. We show that this form of machine learning fails when rewards (returns) are affected by tail risk, i.e., leptokurtosis. Here, we adapt a recent extension of RL, called distributional RL (disRL), and introduce estimation efficiency, while properly adjusting for differential impact of outliers on the two terms of the RL prediction error in the updating equations. We show that the resulting “efficient distributional RL” (e-disRL) learns much faster, and is robust once it settles on a policy. Our paper also provides a brief, nontechnical overview of machine learning, focusing on RL.

Our preferences are influenced by the opinions of others. The past human neuroimaging studies on social conformity have identified a network of brain regions related to social conformity that includes the posterior medial frontal cortex (pMFC), anterior insula, and striatum. Since these brain regions are also known to play important roles in reinforcement learning (i.e., processing prediction error), it was previously hypothesized that social conformity and reinforcement learning have a common neural mechanism. However, although this view is currently widely accepted, these two processes have never been directly compared; therefore, the extent to which they shared a common neural mechanism had remained unclear. This study aimed to formally test the hypothesis. The same group of participants (n = 25) performed social conformity and reinforcement learning tasks inside a functional magnetic resonance imaging (fMRI) scanner. Univariate fMRI data analyses revealed activation overlaps in the pMFC and bilateral insula between social conflict and unsigned prediction error and in the striatum between social conflict and signed prediction error. We further conducted multivoxel pattern analysis (MVPA) for more direct evidence of a shared neural mechanism. MVPA did not reveal any evidence to support the hypothesis in any of these regions but found that activation patterns between social conflict and prediction error in these regions were largely distinct. Taken together, the present study provides no clear evidence of a common neural mechanism between social conformity and reinforcement learning.

How natural selection can promote cooperative or altruistic behavior is a fundamental question in biological and social sciences. One of the persuasive mechanisms is "indirect reciprocity," working through reputation: cooperative behavior can prevail because the behavior builds the donor's good reputation and then s/he receives some reciprocal benefits from someone else in the community. However, an important piece missed in the previous studies is that the reputation-building process requires substantial cognitive abilities such as communication skills, potentially causing a loss of biological fitness. Here, by mathematical analyses and individual-based computer simulations, we show that natural selection never favors indirect reciprocal cooperation in the presence of the cost of reputation building, regardless of the cost-to-benefit ratio of cooperation or moral assessment rules (social norms). Our results highlight the importance of considering the cost of high-level cognitive abilities in studies of the evolution of humans' and animals' social behavior.

Free will is widely considered a foundational component of Western moral and legal codes, and yet current conceptions of free will are widely thought to fit uncomfortably with much research in psychology and neuroscience. Recent research investigating the consequences of laypeople’s free will beliefs (FWBs) for everyday moral behavior suggests that stronger FWBs are associated with various desirable moral characteristics (e.g., greater helpfulness, less dishonesty). These findings have sparked concern regarding the potential for moral degeneration throughout society as science promotes a view of human behavior that is widely perceived to undermine the notion of free will. We report four studies (combined N = 921) originally concerned with possible mediators and/or moderators of the abovementioned associations. Unexpectedly, we found no association between FWBs and moral behavior. Our findings suggest that the FWB–moral behavior association (and accompanying concerns regarding decreases in FWBs causing moral degeneration) may be overstated.

For making decisions in everyday life we often have first to infer the set of environmental features that are relevant for the current task. Here we investigated the computational mechanisms underlying the evolution of beliefs about the relevance of environmental features in a dynamical and noisy environment. For this purpose we designed a probabilistic Wisconsin card sorting task (WCST) with belief solicitation, in which subjects were presented with stimuli composed of multiple visual features. At each moment in time a particular feature was relevant for obtaining reward, and participants had to infer which feature was relevant and report their beliefs accordingly. To test the hypothesis that attentional focus modulates the belief update process, we derived and fitted several probabilistic and non-probabilistic behavioral models, which either incorporate a dynamical model of attentional focus, in the form of a hierarchical winner-take-all neuronal network, or a diffusive model, without attention-like features. We used Bayesian model selection to identify the most likely generative model of subjects' behavior and found that attention-like features in the behavioral model are essential for explaining subjects' responses. Furthermore, we demonstrate a method for integrating both connectionist and Bayesian models of decision making within a single framework that allowed us to infer hidden belief processes of human subjects.

Disappointment, the emotion experienced when faced to reward prediction errors (RPEs), considerably impacts decision making (DM). Individuals tend to modify their behavior in an often unpredictable way just to avoid experiencing negative emotions. Despite its importance, disappointment remains much less studied than regret and its impact on upcoming decisions largely unexplored. Here, we adapted the Trust Game to effectively elicit, quantify, and isolate disappointment by relying on the formal definition provided by Bell's in economics. We evaluated the effects of experienced disappointment and elation on future cooperation and trust as well as the rationality and utility of the different behavioral and neural mechanisms used to cope with disappointment. All participants in our game trusted less and particularly expected less from unknown opponents as a result of disappointing outcomes in the previous trial but not necessarily after elation indicating that behavioral consequences of positive and negative RPEs are not the same. A large variance in the tolerance to disappointment was observed across subjects, with some participants needing only a small disappointment to impulsively bias their subsequent decisions. As revealed by high-density EEG recordings the most tolerant individuals - who thought twice before making a decision and earned more money - relied on different neural generators to contend with neutral and unexpected outcomes. This study thus provides some support to the idea that different neural systems underlie reflexive and reflective decisions within the same individuals as predicted by the dual-system theory of social judgment and DM.

Temporal preferences of animals and humans often exhibit inconsistencies, whereby an earlier, smaller reward may be preferred when it occurs immediately but not when it is delayed. Such choices reflect hyperbolic discounting of future rewards, rather than the exponential discounting required for temporal consistency. Simultaneously, however, evidence has emerged that suggests that animals and humans have an internal representation of time that often differs from the calendar time used in detection of temporal inconsistencies. Here, we prove that temporal inconsistencies emerge if fixed durations in calendar time are experienced as positively related (positive quadrant dependent). Hence, what are time-consistent choices within the time framework of the decision maker appear as time-inconsistent to an outsider who analyzes choices in calendar time. As the biological clock becomes more variable, the fit of the hyperbolic discounting model improves. A recent alternative explanation for temporal choice inconsistencies builds on persistent under-estimation of the length of distant time intervals. By increasing the expected speed of our stochastic biological clock for time farther into the future, we can emulate this explanation. Ours is therefore an encompassing theoretical framework that predicts context-dependent degrees of intertemporal choice inconsistencies, to the extent that context can generate changes in autocorrelation, variability, and expected speed of the biological clock. Our finding should lead to novel experiments that will clarify the role of time perception in impulsivity, with critical implications for, among others, our understanding of aging, drug abuse, and pathological gambling.

Large-scale human interaction through, for example, financial markets causes ceaseless random changes in outcome variability, producing frequent and salient outliers that render the outcome distribution more peaked than the Gaussian distribution, and with longer tails. Here, we study how humans cope with this evolutionary novel leptokurtic noise, focusing on the neurobiological mechanisms that allow the brain, 1) to recognize the outliers as noise and 2) to regulate the control necessary for adaptive response. We used functional magnetic resonance imaging, while participants tracked a target whose movements were affected by leptokurtic noise. After initial overreaction and insufficient subsequent correction, participants improved performance significantly. Yet, persistently long reaction times pointed to continued need for vigilance and control. We ran a contrasting treatment where outliers reflected permanent moves of the target, as in traditional mean-shift paradigms. Importantly, outliers were equally frequent and salient. There, control was superior and reaction time was faster. We present a novel reinforcement learning model that fits observed choices better than the Bayes-optimal model. Only anterior insula discriminated between the 2 types of outliers. In both treatments, outliers initially activated an extensive bottom-up attention and belief network, followed by sustained engagement of the fronto-parietal control network.

BACKGROUND: Niemann-Pick Type C disease (NPC), is an autosomal recessive neurovisceral disorder of lipid metabolism. One characteristic feature of NPC is a vertical supranuclear gaze palsy particularly affecting saccades. However, horizontal saccades are also impaired and as a consequence a parameter related to horizontal peak saccadic velocity was used as an outcome measure in the clinical trial of miglustat, the first drug approved in several jurisdictions for the treatment of NPC. As NPC-related neuropathology is widespread in the brain we examined a wider range of horizontal saccade parameters and to determine whether these showed treatment-related improvement and, if so, if this was maintained over time. METHODS: Nine adult NPC patients participated in the study; 8 were treated with miglustat for periods between 33 and 61 months. Data were available for 2 patients before their treatment commenced and 1 patient was untreated. Tasks included reflexive saccades, antisaccades and self-paced saccades, with eye movements recorded by an infrared reflectance eye tracker. Parameters analysed were reflexive saccade gain and latency, asymptotic peak saccadic velocity, HSEM-α (the slope of the peak duration-amplitude regression line), antisaccade error percentage, self-paced saccade count and time between refixations on the self-paced task. Data were analysed by plotting the change from baseline as a proportion of the baseline value at each test time and, where multiple data values were available at each session, by linear mixed effects (LME) analysis. RESULTS: Examination of change plots suggested some modest sustained improvement in gain, no consistent changes in asymptotic peak velocity or HSEM-α, deterioration in the already poor antisaccade error rate and sustained improvement in self-paced saccade rate. LME analysis showed statistically significant improvement in gain and the interval between self-paced saccades, with differences over time between treated and untreated patients. CONCLUSIONS: Both qualitative examination of change scores and statistical evaluation with LME analysis support the idea that some saccadic parameters are robust indicators of efficacy, and that the variability observed across measures may indicate locally different effects of neurodegeneration and of drug actions.

The acknowledged importance of uncertainty in economic decision making has stimulated the search for neural signals that could influence learning and inform decision mechanisms. Current views distinguish two forms of uncertainty, namely risk and ambiguity, depending on whether the probability distributions of outcomes are known or unknown. Behavioural neurophysiological studies on dopamine neurons revealed a risk signal, which covaried with the standard deviation or variance of the magnitude of juice rewards and occurred separately from reward value coding. Human imaging studies identified similarly distinct risk signals for monetary rewards in the striatum and orbitofrontal cortex (OFC), thus fulfilling a requirement for the mean variance approach of economic decision theory. The orbitofrontal risk signal covaried with individual risk attitudes, possibly explaining individual differences in risk perception and risky decision making. Ambiguous gambles with incomplete probabilistic information induced stronger brain signals than risky gambles in OFC and amygdala, suggesting that the brain's reward system signals the partial lack of information. The brain can use the uncertainty signals to assess the uncertainty of rewards, influence learning, modulate the value of uncertain rewards and make appropriate behavioural choices between only partly known options.

Contemporary computational accounts of instrumental conditioning have emphasized a role for a model-based system in which values are computed with reference to a rich model of the structure of the world, and a model-free system in which values are updated without encoding such structure. Much less studied is the possibility of a similar distinction operating at the level of Pavlovian conditioning. In the present study, we scanned human participants while they participated in a Pavlovian conditioning task with a simple structure while measuring activity in the human amygdala using a high-resolution fMRI protocol. After fitting a model-based algorithm and a variety of model-free algorithms to the fMRI data, we found evidence for the superiority of a model-based algorithm in accounting for activity in the amygdala compared to the model-free counterparts. These findings support an important role for model-based algorithms in describing the processes underpinning Pavlovian conditioning, as well as providing evidence of a role for the human amygdala in model-based inference.

Little is known about how humans solve the exploitation/exploration trade-off. In particular, the evidence for uncertainty-driven exploration is mixed. The current study proposes a novel hypothesis of exploration that helps reconcile prior findings that may seem contradictory at first. According to this hypothesis, uncertainty-driven exploration involves a dilemma between two motives: (i) to speed up learning about the unknown, which may beget novel reward opportunities; (ii) to avoid the unknown because it is potentially dangerous. We provide evidence for our hypothesis using both behavioral and simulated data, and briefly point to recent evidence that the brain differentiates between these two motives.

The neuroscience of human decision-making has focused on localizing brain activity correlating with decision variables and choice, most commonly using functional MRI (fMRI). Poor temporal resolution means these studies are agnostic in relation to how decisions unfold in time. Consequently, here we address the temporal evolution of neural activity related to encoding of risk using magnetoencephalography (MEG), and show modulations of electromagnetic power in posterior parietal and dorsomedial prefrontal cortex (DMPFC) which scale with both variance and skewness in a lottery, detectable within 500 ms following stimulus presentation. Electromagnetic responses in somatosensory cortex following this risk encoding predict subsequent choices. Furthermore, within anterior insula we observed early and late effects of subject-specific risk preferences, suggestive of a role in both risk assessment and risk anticipation during choice. The observation that cortical activity tracks specific and independent components of risk from early time-points in a decision-making task supports the hypothesis that specialized brain circuitry underpins risk perception.

Recently, evidence has emerged that humans approach learning using Bayesian updating rather than (model-free) reinforcement algorithms in a six-arm restless bandit problem. Here, we investigate what this implies for human appreciation of uncertainty. In our task, a Bayesian learner distinguishes three equally salient levels of uncertainty. First, the Bayesian perceives irreducible uncertainty or risk: even knowing the payoff probabilities of a given arm, the outcome remains uncertain. Second, there is (parameter) estimation uncertainty or ambiguity: payoff probabilities are unknown and need to be estimated. Third, the outcome probabilities of the arms change: the sudden jumps are referred to as unexpected uncertainty. We document how the three levels of uncertainty evolved during the course of our experiment and how it affected the learning rate. We then zoom in on estimation uncertainty, which has been suggested to be a driving force in exploration, in spite of evidence of widespread aversion to ambiguity. Our data corroborate the latter. We discuss neural evidence that foreshadowed the ability of humans to distinguish between the three levels of uncertainty. Finally, we investigate the boundaries of human capacity to implement Bayesian learning. We repeat the experiment with different instructions, reflecting varying levels of structural uncertainty. Under this fourth notion of uncertainty, choices were no better explained by Bayesian updating than by (model-free) reinforcement learning. Exit questionnaires revealed that participants remained unaware of the presence of unexpected uncertainty and failed to acquire the right model with which to implement Bayesian updating.

Few finance theories consider the influence of "skewness" (or large and asymmetric but unlikely outcomes) on financial choice. We investigated the impact of skewed gambles on subjects' neural activity, self-reported affective responses, and subsequent preferences using functional magnetic resonance imaging (FMRI). Neurally, skewed gambles elicited more anterior insula activation than symmetric gambles equated for expected value and variance, and positively skewed gambles also specifically elicited more nucleus accumbens (NAcc) activation than negatively skewed gambles. Affectively, positively skewed gambles elicited more positive arousal and negatively skewed gambles elicited more negative arousal than symmetric gambles equated for expected value and variance. Subjects also preferred positively skewed gambles more, but negatively skewed gambles less than symmetric gambles of equal expected value. Individual differences in both NAcc activity and positive arousal predicted preferences for positively skewed gambles. These findings support an anticipatory affect account in which statistical properties of gambles--including skewness--can influence neural activity, affective responses, and ultimately, choice.

In an uncertain environment, probabilities are key to predicting future events and making adaptive choices. However, little is known about how humans learn such probabilities and where and how they are encoded in the brain, especially when they concern more than two outcomes. During functional magnetic resonance imaging (fMRI), young adults learned the probabilities of uncertain stimuli through repetitive sampling. Stimuli represented payoffs and participants had to predict their occurrence to maximize their earnings. Choices indicated loss and risk aversion but unbiased estimation of probabilities. BOLD response in medial prefrontal cortex and angular gyri increased linearly with the probability of the currently observed stimulus, untainted by its value. Connectivity analyses during rest and task revealed that these regions belonged to the default mode network. The activation of past outcomes in memory is evoked as a possible mechanism to explain the engagement of the default mode network in probability learning. A BOLD response relating to value was detected only at decision time, mainly in striatum. It is concluded that activity in inferior parietal and medial prefrontal cortex reflects the amount of evidence accumulated in favor of competing and uncertain outcomes.

The ability to infer intentions of other agents, called theory of mind (ToM), confers strong advantages for individuals in social situations. Here, we show that ToM can also be maladaptive when people interact with complex modern institutions like financial markets. We tested participants who were investing in an experimental bubble market, a situation in which the price of an asset is much higher than its underlying fundamental value. We describe a mechanism by which social signals computed in the dorsomedial prefrontal cortex affect value computations in ventromedial prefrontal cortex, thereby increasing an individual's propensity to 'ride' financial bubbles and lose money. These regions compute a financial metric that signals variations in order flow intensity, prompting inference about other traders' intentions. Our results suggest that incorporating inferences about the intentions of others when making value judgments in a complex financial market could lead to the formation of market bubbles.

Extant research shows that stock returns of investable firms are highly sensitive to foreign market and global information shocks, suggesting that having foreign investors might insulate investable firms from shocks to local fundamentals. Examining 24 emerging markets, we find that both investable and non-investable firms are sensitive to local monetary policy shocks. This allays the concern that emerging-market opening reduces the efficacy of local monetary policy. We also find that in 11 countries (46% of our country-sample), investable firms are more sensitive to local shocks than non-investable firms. Differences in leverage, stock liquidity, size, domestic product-market exposure, or industry cyclicality do not drive this finding.

Tax-driven Off-Market Buybacks (TOMBs) have been used by large Australian companies to distribute cash and stream franking (tax) credits to low-tax-rate shareholders. While small in number, the amounts are significant, involving an estimated cost to government tax revenue in 2018 of around $2 billion. This paper reviews the current and historical evolution of the regulation and taxation of TOMBs and argues that there are fundamental problems with corporate use of TOMBs. These include inequitable treatment of shareholders, government tax revenue costs, inconsistency with good principles of taxation, arbitrary tax determinations and practices which are difficult to justify. Since corporates can distribute cash to shareholders using other, quite standard, capital management techniques, we argue that a social cost-benefit analysis leads to the conclusion that TOMBs should be prohibited.

“Tiered” depositor (or deposit insurer) preference as exists in Australia and has been recently introduced in the EU and UK calls into question the merits of ex ante fees for explicit, limited deposit insurance under such arrangements. This paper illustrates how, under such arrangements, the “fair price” of deposit insurance and risks to the deposit insurer are reduced to near zero unless virtually all bank non-equity funding is insured deposits. It is also argued that other regulatory changes affecting bank liability structures and resolution arrangements reinforce that effect, while introduction of “resolution funds” calls into question the rationale for a separate deposit insurance fund. While increased use of collateralised financing complicates resolution arrangements and raises other risks for financial stability, its impact on a “fair price” for deposit insurance under tiered preference is minimal.

Many financial products and securities marketed to retail investors involve design features that can make it difficult to understand the risk and return characteristics involved. This paper examines one such security, Convertible Preference Step Up Units (CPUs), issued in Australia by the US Masters Residential Property Fund (URF) at the end of 2017. It argues that an apparently relatively simple design masks significant complexity which would make risk assessment and fair pricing well beyond the capabilities of retail investors. Despite that, analysis of the security design and disclosure documents suggests that it would not fall foul of the financial product banning powers recommended for the Australian Securities and Investment Commission by the 2014 Australian Financial System Inquiry and in draft legislation as at mid 2018. This highlights the difficulties for effective financial consumer protection resulting from the mismatch between financial literacy levels and financial product design.

The microstructure literature comprises a rich set of papers that seek to understand pricing dynamics at a granular level, commonly exploring the joint dynamics of bids, asks and last sale prices. Its focus is on identifying innovations in prices and separating permanent price impacts from transient effects. Hasbrouck (1995) provides a tool that has been extensively utilized in the literature to examine these dynamics in many different market contexts over the last two decades.1 However, the evolution of markets over this period, most notably the exponential growth in the volume of data and the increasing importance of trading speed has made the application of Hasbrouck’s (1995) method and other related tools discussed in Hasbrouck (2018) more computationally and econometrically challenging. Hasbrouck (2018) offers a new approach to help overcome these challenges. In this comment, we briefly describe the evolution of markets and detail the challenges that these changes create for microstructure researchers and highlight the solution that Hasbrouck (2018) offers for these problems. We survey the literature that uses linear multivariate time-series models to understand high-frequency markets. We focus on three examples from the literature to discuss how estimation constraints have affected their modelling choices, describe the potential drawbacks of these choices and how Hasbrouck’s (2018) method can alleviate these constraints. We deliberately select papers that cover different asset classes: cash equities, fixed income and equity options. We hope that our discussion will help provide guidance about the costs and benefits of different modelling choices for future researchers confronted with a variety of methods to answer related research questions. We conclude by considering the implications of Hasbrouck’s 2018 paper for the current policy debate on market data costs.

Abstract We provide evidence on market structure and the cost of raising capital by examining changes in market structure in U.S. equity markets. Only the Order Handling Rules (OHR) of the Nasdaq, the one reform that reduced institutional trading costs, lowered the cost of raising capital. Using a difference-in-differences framework relative to the New York Stock Exchange (NYSE) that exploits the OHR’s staggered implementation, we find that the OHR reduced the underpricing of seasoned equity offerings by 1–2 percentage points compared with a pre-OHR average of 3.6%. The effect is the largest in stocks with the largest reduction in institutional trading costs after the OHR.

An acquisition of a company involved in socially undesirable activities can have important value implications. On the one hand, stocks in sin industries can be undervalued, and positive wealth effects might be created through risk sharing and a halo effect. On the other hand, acquiring sin stocks could increase litigation risk and the chance of product boycotts, and could hurt relations with employees and other stakeholders. Moreover, many investors avoid investments in sin stocks by applying negative screening. This article empirically establishes that shareholders of acquirer firms on average discount sin acquisitions. The negative wealth effects are stronger in countries with a greater focus on corporate social responsibility and for deals that are more likely to receive public attention. The article concludes that the costs of “sin” are considerable.

We use meta-analysis to review studies on announcement effects associated with seasoned equity offerings. Our sample includes 199 studies from 38 leading finance journals and Social Sciences Research Network working papers. The studies cover different countries, but the US is particularly well-represented with 131 studies. We find a statistically significant mean cumulative abnormal return of -0.98%. Abnormal returns are more negative for equity issues by US companies and for non-US rights issues and are less negative for private placements. In addition, wealth effects are more negative when the proceeds are used for debt reduction, when the SEO is issued shortly after IPO, and for issues by nondividend-paying companies and industrial companies. We identify important avenues for future research.

In this article, we show that exogenous director distraction affects board monitoring intensity and leads to a higher level of inactivity by management. We construct a firm-level director “distraction” measure by exploiting shocks to unrelated industries in which directors have additional directorships. Directors attend significantly fewer board meetings when they are distracted. Firms with distracted board members tend to be inactive and experience a significant decline in firm value. Overall, this article highlights the impact of limited director attention on the effectiveness of corporate governance and the importance of directors in keeping management active.

The maturities of newly issued convertible bonds vary substantially over time. Firm-specific determinants of maturity from the straight debt literature are relevant for convertible bonds. However, the growth of the convertible arbitrage industry and the role of convertible arbitrage hedge funds have changed the importance of firm characteristics in the convertible bond market. Recently issued convertible bonds come with particularly short maturities that serve as substitutes for call provisions. This substitution implies that backdoor-equity and sequential-financing rationales for issuing callable convertible bonds are also applicable for non-callable convertibles with shorter maturities.

The objective of this paper is to examine the likely consequences of the RC on future Australian financial sector development.

The capacity for strategic thinking about the payoff-relevant actions of conspecifics is not well understood across species. We use game theory to make predictions about choices and temporal dynamics in three abstract competitive situations with chimpanzee participants. Frequencies of chimpanzee choices are extremely close to equilibrium (accurate-guessing) predictions, and shift as payoffs change, just as equilibrium theory predicts. The chimpanzee choices are also closer to the equilibrium prediction, and more responsive to past history and payoff changes, than two samples of human choices from experiments in which humans were also initially uninformed about opponent payoffs and could not communicate verbally. The results are consistent with a tentative interpretation of game theory as explaining evolved behavior, with the additional hypothesis that chimpanzees may retain or practice a specialized capacity to adjust strategy choice during competition to perform at least as well as, or better than, humans have.

In inverse reinforcement learning an observer infers the reward distribution available for actions in the environment solely through observing the actions implemented by another agent. To address whether this computational process is implemented in the human brain, participants underwent fMRI while learning about slot machines yielding hidden preferred and non-preferred food outcomes with varying probabilities, through observing the repeated slot choices of agents with similar and dissimilar food preferences. Using formal model comparison, we found that participants implemented inverse RL as opposed to a simple imitation strategy, in which the actions of the other agent are copied instead of inferring the underlying reward structure of the decision problem. Our computational fMRI analysis revealed that anterior dorsomedial prefrontal cortex encoded inferences about action-values within the value space of the agent as opposed to that of the observer, demonstrating that inverse RL is an abstract cognitive process divorceable from the values and concerns of the observer him/herself.