Foraging under conditions of short-term exploitative competition: The case of stock traders

Theory purports that animal foraging choices evolve to maximize returns, such as net energy intake. Empirical research in both human and nonhuman animals reveals that individuals often attend to the foraging choices of their competitors while making their own foraging choices. Due to the complications of gathering field data or constructing experiments, however, broad facts relating theoretically optimal and empirically realized foraging choices are only now emerging. Here, we analyze foraging choices of a cohort of professional day traders who must choose between trading the same stock multiple times in a row---patch exploitation---or switching to a different stock---patch exploration---with potentially higher returns. We measure the difference between a trader's resource intake and the competitors' expected intake within a short period of time---a difference we call short-term comparative returns. We find that traders' choices can be explained by foraging heuristics that maximize their daily short-term comparative returns. However, we find no one-best relationship between different trading choices and net income intake. This suggests that traders' choices can be short-term win oriented and, paradoxically, maybe maladaptive for absolute market returns

A discipline-wide investigation of the replicability of Psychology papers over the past two decades

Conjecture about the weak replicability in social sciences has made scholars eager to quantify the scale and scope of replication failure for a discipline. Yet small-scale manual replication methods alone are ill-suited to deal with this big data problem. Here, we conduct a discipline-wide replication census in science. Our sample (N = 14,126 papers) covers nearly all papers published in the six top-tier Psychology journals over the past 20 y. Using a validated machine learning model that estimates a paper's likelihood of replication, we found evidence that both supports and refutes speculations drawn from a relatively small sample of manual replications. First, we find that a single overall replication rate of Psychology poorly captures the varying degree of replicability among subfields. Second, we find that replication rates are strongly correlated with research methods in all subfields. Experiments replicate at a significantly lower rate than do non-experimental studies. Third, we find that authors' cumulative publication number and citation impact are positively related to the likelihood of replication, while other proxies of research quality and rigor, such as an author's university prestige and a paper's citations, are unrelated to replicability. Finally, contrary to the ideal that media attention should cover replicable research, we find that media attention is positively related to the likelihood of replication failure. Our assessments of the scale and scope of replicability are important next steps toward broadly resolving issues of replicability

Small-world networks and management science research: a review

This paper reviews the literature on small-world networks in social science and management. This relatively new area of research represents an unusual level of crossdisciplinary research within social science and between social science and the physical sciences. We review the findings of this emerging area with an eye to describing the underlying theory of small worlds, the technical apparatus, promising facts, and unsettled issues for future research

Common Organizing Mechanisms in Ecological and Socio-economic Networks

Previous work has shown that species interacting in an ecosystem and actors transacting in an economic context may have notable similarities in behavior. However, the specific mechanism that may underlie similarities in nature and human systems has not been analyzed. Building on stochastic food-web models, we propose a parsimonious bipartite-cooperation model that reproduces the key features of mutualistic networks - degree distribution, nestedness and modularity -- for both ecological networks and socio-economic networks. Our analysis uses two diverse networks. Mutually-beneficial interactions between plants and their pollinators, and cooperative economic exchanges between designers and their contractors. We find that these mutualistic networks share a key hierarchical ordering of their members, along with an exponential constraint in the number and type of partners they can cooperate with. We use our model to show that slight changes in the interaction constraints can produce either extremely nested or random structures, revealing that these constraints play a key role in the evolution of mutualistic networks. This could also encourage a new systematic approach to study the functional and structural properties of networks. The surprising correspondence across mutualistic networks suggests their broadly representativeness and their potential role in the productive organization of exchange systems, both ecological and social.Comment: In F. Reed-Tsochas and N. Johnson (eds.) Complex Systems and Interdisciplinary Sciences. London: World Scientific Publishing (in press