Herding in the bad times: The 2008 and COVID-19 crises

The objective of this paper is to analyze the imitation behavior of investors in especially convulsed periods, such as the 2008 financial crisis and the recent global pandemic, both of which could affect investors'' emotions and behavior, although both have different characteristics and might have different implications. The cross-sectional dispersion of returns is used to measure the level of herding in the markets of Spain and Portugal, using a survivorship-bias-free dataset of daily stock returns during the period January 2000–May 2021, in turn divided into several sub-periods classified as pre-2008 crisis, 2008 crisis, post-2008 crisis, Covid-19 and post Covid-19. Additionally, the existence is studied of differences between days of positive and negative returns, or between days of high volatility compared to the rest, and whether the cross-sectional dispersion of returns in one market is affected by the cross-sectional dispersion of returns in the other market. The results indicate that herding appears with greater intensity in periods prior to the crisis, disappearing during the financial crisis and reappearing, although with less intensity, after it, while it is not generally detected in Covid-19 times. However, herding behavior can be observed in the market during the pandemic on high volatility days

In situ visualization of large-scale turbulence simulations in Nek5000 with ParaView Catalyst

In situ visualization on high-performance computing systems allows us to analyze simulation results that would otherwise be impossible, given the size of the simulation data sets and offline post-processing execution time. We develop an in situ adaptor for Paraview Catalyst and Nek5000, a massively parallel Fortran and C code for computational fluid dynamics. We perform a strong scalability test up to 2048 cores on KTH’s Beskow Cray XC40 supercomputer and assess in situ visualization’s impact on the Nek5000 performance. In our study case, a high-fidelity simulation of turbulent flow, we observe that in situ operations significantly limit the strong scalability of the code, reducing the relative parallel efficiency to only ≈ 21 % on 2048 cores (the relative efficiency of Nek5000 without in situ operations is ≈ 99 %). Through profiling with Arm MAP, we identified a bottleneck in the image composition step (that uses the Radix-kr algorithm) where a majority of the time is spent on MPI communication. We also identified an imbalance of in situ processing time between rank 0 and all other ranks. In our case, better scaling and load-balancing in the parallel image composition would considerably improve the performance of Nek5000 with in situ capabilities. In general, the result of this study highlights the technical challenges posed by the integration of high-performance simulation codes and data-analysis libraries and their practical use in complex cases, even when efficient algorithms already exist for a certain application scenario

CarrotDiverse : understanding variation in a wild relative of carrot

Genebanks and other ex situ collections have a significant role in the conservation, management and use of crop genetic diversity, including that of crop wild relatives. Efficient management and use depends on insight into the patterning and distribution of genetic diversity as well as obtaining baseline information on phenotypic characters and traits. Wild carrot (Daucus carota L.) is the closest wild relative of cultivated carrot (Daucus carota L. subsp. sativus (Hoffm.) Arcang.), and is a potential source of useful traits for crop improvement. There are over 900 accessions of D. carota described as wild in European genebanks, however associated phenotypic and genotypic characterization data are sparse. The influence of environment on phenotype is also not well understood in this taxon, meaning that it is difficult to ascertain how data collected at different locations can be compiled and collated. We present initial results of CarrotDiverse, a collaborative project in which wild D. carota accessions are undergoing detailed phenotypic and morphological characterization in parallel at three sites of varying latitude across Europe located in Portugal, France and Sweden. This will allow us to understand which traits are affected by environmental variables. Basic phenotypic information is being collected on a further 150 accessions. Furthermore, resistance screening to Alternaria species and polyacetylene profiling will be included in the evaluation. A Genotyping by Sequencing approach will be used to generate knowledge about genetic background and trait associations. The project will result in a significant data set which will facilitate the use of crop wild relatives in carrot breeding and improvement

A proposed framework for the systematic review and integrated assessment (SYRINA) of endocrine disrupting chemicals

Background - The issue of endocrine disrupting chemicals (EDCs) is receiving wide attention from both the scientific and regulatory communities. Recent analyses of the EDC literature have been criticized for failing to use transparent and objective approaches to draw conclusions about the strength of evidence linking EDC exposures to adverse health or environmental outcomes. Systematic review methodologies are ideal for addressing this issue as they provide transparent and consistent approaches to study selection and evaluation. Objective methods are needed for integrating the multiple streams of evidence (epidemiology, wildlife, laboratory animal, in vitro, and in silico data) that are relevant in assessing EDCs. Methods - We have developed a framework for the systematic review and integrated assessment (SYRINA) of EDC studies. The framework was designed for use with the International Program on Chemical Safety (IPCS) and World Health Organization (WHO) definition of an EDC, which requires appraisal of evidence regarding 1) association between exposure and an adverse effect, 2) association between exposure and endocrine disrupting activity, and 3) a plausible link between the adverse effect and the endocrine disrupting activity. Results - Building from existing methodologies for evaluating and synthesizing evidence, the SYRINA framework includes seven steps: 1) Formulate the problem; 2) Develop the review protocol; 3) Identify relevant evidence; 4) Evaluate evidence from individual studies; 5) Summarize and evaluate each stream of evidence; 6) Integrate evidence across all streams; 7) Draw conclusions, make recommendations, and evaluate uncertainties. The proposed method is tailored to the IPCS/WHO definition of an EDC but offers flexibility for use in the context of other definitions of EDCs. Conclusions - When using the SYRINA framework, the overall objective is to provide the evidence base needed to support decision making, including any action to avoid/minimise potential adverse effects of exposures. This framework allows for the evaluation and synthesis of evidence from multiple evidence streams. Finally, a decision regarding regulatory action is not only dependent on the strength of evidence, but also the consequences of action/inaction, e.g. limited or weak evidence may be sufficient to justify action if consequences are serious or irreversible.The workshops that supported the writing of this manuscript were funded by the Swedish Foundation for Strategic Environmental Research “Mistra”. LNV was funded by Award Number K22ES025811 from the National Institute of Environmental Health Sciences of the National Institutes of Health. TJW was funded by The Clarence Heller Foundation (A123547), the Passport Foundation, the Forsythia Foundation, the National Institute of Environmental Health Sciences (grants ES018135 and ESO22841), and U.S. EPA STAR grants (RD83467801 and RD83543301). JT was funded by the Academy of Finland and Sigrid Juselius. UH was funded by the Danish EPA. KAK was funded by the Canada Research Chairs program grant number 950–230607

Cross-Market Herding: Do ‘Herds’ Herd with Each Other?

Although herding constitutes one of the most widely researched behavioral trading patterns internationally, the possibility of cross-market herding has remained largely underexplored in the literature. Our study provides a detailed empirical investigation of this issue in the context of ten Asia-Pacific markets for the February 1995–March 2022 window. We find that all ten markets’ “herds” project significant relationships with each other, with causality being identified within a minority of those relationships. These results are robust when controlling for financial crises (Asian; global financial; global pandemic) and US market returns

A Functional Approach to Monitor and Recognize Patterns of Daily Traffic Profiles

Functional Data Analysis (FDA) is a collection of statistical techniques for the analysis of information on curves or functions. This paper presents a new methodology for analyzing the daily traffic flow profiles based on the employment of FDA. A daily traffic profile corresponds to a single datum rather than a large set of traffic counts. This insight provides ideal information for strategic decision-making regarding road expansion, control, and other long-term decisions. Using Functional Principal Component Analysis the data are projected into a low dimensional space: the space of the first functional principal components. Each curve is represented by their vector of scores on this basis. The principal component scores are used for clustering and also to identify outliers (meaning that there was a bad performance in the recording of data or special circumstances affected the traffic) and to monitor the traffic profile by multivariate control charts. This paper introduces this new methodology and illustrates good results by using 1-min traffic data from the I-94 Freeway in the Twin Cities, Minnesota (U.S.) metroplex ranging from 2004 to 2011

CarrotDiverse: understanding variation in a wild relative of carrot

International audienceGenebanks and other ex situ collections have a significant role in the conservation, management and use of crop genetic diversity, including that of crop wild relatives. Efficient management and use depends on insight into the patterning and distribution of genetic diversity as well as obtaining baseline information on phenotypic characters and traits. Wild carrot (Daucus carota L.) is the closest wild relative of cultivated carrot (Daucus carota L. subsp. sativus (Hoffm.) Arcang.), and is a potential source of useful traits for crop improvement. There are over 900 accessions of D. carota described as wild in European genebanks, however associated phenotypic and genotypic characterization data are sparse. The influence of environment on phenotype is also not well understood in this taxon, meaning that it is difficult to ascertain how data collected at different locations can be compiled and collated. We present initial results of CarrotDiverse, a collaborative project in which wild D. carota accessions are undergoing detailed phenotypic and morphological characterization in parallel at three sites of varying latitude across Europe located in Portugal, France and Sweden. This will allow us to understand which traits are affected by environmental variables. Basic phenotypic information is being collected on a further 150 accessions. Furthermore, resistance screening to Alternaria species and polyacetylene profiling will be included in the evaluation. A Genotyping by Sequencing approach will be used to generate knowledge about genetic background and trait associations. The project will result in a significant data set which will facilitate the use of crop wild relatives in carrot breeding and improvement

A synthesis of the environmental response of the North and South Atlantic Sub-Tropical Gyres during two decades of AMT

Anthropogenically-induced global warming is expected to decrease primary productivity in the subtropical oceans by strengthening stratification of the water column and reducing the flux of nutrients from deep-waters to the sunlit surface layers. Identification of such changes is hindered by a paucity of long-term, spatially-resolved, biological time-series data at the basin scale. This paper exploits Atlantic Meridional Transect (AMT) data on physical and biogeochemical properties (1995–2014) in synergy with a wide range of remote-sensing (RS) observations from ocean colour, Sea Surface Temperature (SST), Sea Surface Salinity (SSS) and altimetry (surface currents), combined with different modelling approaches (both empirical and a coupled 1-D Ecosystem model), to produce a synthesis of the seasonal functioning of the North and South Atlantic Sub-Tropical Gyres (STGs), and assess their response to longer-term changes in climate. We explore definitive characteristics of the STGs using data of physical (SST, SSS and peripheral current systems) and biogeochemical variables (chlorophyll and nitrate), with inherent criteria (permanent thermal stratification and oligotrophy), and define the gyre boundary from a sharp gradient in these physical and biogeochemical properties. From RS data, the seasonal cycles for the period 1998–2012 show significant relationships between physical properties (SST and PAR) and gyre area. In contrast to expectations, the surface layer chlorophyll concentration from RS data (CHL) shows an upward trend for the mean values in both subtropical gyres. Furthermore, trends in physical properties (SST, PAR, gyre area) differ between the North and South STGs, suggesting the processes responsible for an upward trend in CHL may vary between gyres. There are significant anomalies in CHL and SST that are associated with El Niño events. These conclusions are drawn cautiously considering the short length of the time-series (1998–2012), emphasising the need to sustain spatially-extensive surveys such as AMT and integrate such observations with models, autonomous observations and RS data, to help address fundamental questions about how our planet is responding to climate change. A small number of dedicated AMT cruises in the keystone months of January and July would complement our understanding of seasonal cycles in the STGs