Non-linear predictability in stock and bond returns: when and where is it exploitable?

We systematically examine the comparative predictive performance of a number of alternative linear and non-linear models for stock and bond returns in the G7 countries. Besides Markov switching, threshold autoregressive (TAR), and smooth transition autoregressive (STAR) regime switching (predictive) regression models, we also estimate univariate models in which conditional heteroskedasticity is captured through GARCH, TARCH and EGARCH models and ARCH-in mean effects appear in the conditional mean. Although we fail to find a consistent winner/out-performer across all countries and asset markets, it turns out that capturing non-linear effects is of extreme importance to improve forecasting performance. U.S. and U.K. asset return data are “special” in the sense that good predictive performance seems to loudly ask for models that capture non linear dynamics, especially of the Markov switching type. Although occasionally also stock and bond return forecasts for other G7 countries appear to benefit from non-linear modeling (especially of TAR and STAR type), data from France, Germany, and Italy express interesting predictive results on the basis of simpler benchmarks. U.S. and U.K. data are also the only two data sets in which we find statistically significant differences between forecasting models. Results appear to be remarkably stable over time, and robust to the specification of the loss function used in statistical evaluations as well as to the methodology employed to perform pairwise comparisons.Group of Seven countries ; Financial markets

Paving the way to acceptance of Galleria mellonella as a new model insect

First paragraph: The larva of the greater wax moth Galleria mellonella is an alternative host used commonly in studies of microbial infection and innate immunity. Indeed, this insect host is often used when quantifying or comparing the virulence of bacterial and fungal pathogens of vertebrates and it has been used successfully to establish the importance of microbial virulence factors and to determine the relative virulence of different isolates of the same species. The recent popularity of G. mellonella as an alternative host system stems from numerous benefits, including the ability to perform experiments at a range of temperatures including human body core temperature; the technical simplicity of establishing infections by various routes such as through feeding, topical application or injection; the convenient size of the insect, which means it is large enough to permit simple injection of inoculums or chemicals but small enough to require little space in the laboratory; the ability to assess the efficacy and toxicity of antimicrobial therapies; and the ease and reliability with which these insects can be sourced in their final instar stage from commercial suppliers. It has also found approval amongst many researchers due to the favourable reproducibility between experiments in the same laboratory. Nevertheless, relatively small variations in susceptibility to infection can occur between batches of larvae from the same supplier and such variation probably arises from factors such as age, size and nutritional status on receipt; conditions encountered during transit to the laboratory; and the presence of any underlying natural infections. These issues are largely uncontrollable when purchasing larvae from a commercial supplier but on reaching the laboratory standardised pre-experimentation storage conditions can improve reproducibility between studies. In recent years the Kavanagh group have raised awareness for the role of a number of variables during storage that require consideration to ensure optimal reproducibility when experimenting with this insect, and factors influencing G. mellonella susceptibility to infections include physical stress, incubation temperature and access to food. In this edition of Virulence, the Kavanagh group report that larvae become increasingly susceptible to infection by pathogens as laboratory storage time increases, highlighting the need to consider this parameter when using the G. mellonella model. Browne et al. elaborate further in the study and relate this observation to a reduction in the total abundance of haemocytes that function in immune defence against pathogens and changes in the relative flux of metabolic pathways. Interestingly, the number of haemocytes after 3 weeks of incubation was approximately half that compared to the population at one week, while qualitative changes in the relative abundance of the various types of haemocytes were also reported. Both these factors probably contribute to reduced immune capacity and thus increased susceptibility to infection.Output Type: Editoria

Does the macroeconomy predict UK asset returns in an nonlinear fashion? Comprehensive out-of-sample evidence

We perform a comprehensive examination of the recursive, comparative predictive performance of a number of linear and non-linear models for UK stock and bond returns. We estimate Markov switching, threshold autoregressive (TAR), and smooth transition autoregressive (STR) regime switching models, and a range of linear specifications in addition to univariate models in which conditional heteroskedasticity is captured by GARCH type specifications and in which predicted volatilities appear in the conditional mean. The results demonstrate that U.K. asset returns require non-linear dynamics be modeled. In particular, the evidence in favour of adopting a Markov switching framework is strong. Our results appear robust to the choice of sample period, changes in the adopted loss function and to the methodology employed to test the null hypothesis of equal predictive accuracy across competing models

Immersive 4D Interactive Visualization of Large-Scale Simulations

In dense clusters a bewildering variety of interactions between stars can be observed, ranging from simple encounters to collisions and other mass-transfer encounters. With faster and special-purpose computers like GRAPE, the amount of data per simulation is now exceeding 1TB. Visualization of such data has now become a complex 4D data-mining problem, combining space and time, and finding interesting events in these large datasets. We have recently starting using the virtual reality simulator, installed in the Hayden Planetarium in the American Museum for Natural History, to tackle some of these problem. This work (http://www.astro.umd.edu/nemo/amnh/) reports on our first ``observations'', modifications needed for our specific experiments, and perhaps field ideas for other fields in science which can benefit from such immersion. We also discuss how our normal analysis programs can be interfaced with this kind of visualization.Comment: 4 pages, 1 figure, ADASS-X conference proceeding

A copula model of wind turbine performance

The conventional means of assessing the performance of a wind turbine is through consideration of its power curve which provides the relationship between power output and measured wind speed. In this paper it is shown how the joint probability distribution of power and wind speed can be learned from data, rather than from examination of the implied function of the two variables. Such an approach incorporates measures of uncertainty into performance estimates, allows inter-plant performance comparison, and could be used to simulate plant operation via sampling. A preliminary model is formulated and fitted to operational data as an illustration

“Protect the women!” Trans‐exclusionary feminist issue framing and support for transgender rights

An increasingly salient policy innovation pursued by LGBT+ rights groups and socially liberal policy entrepreneurs is the right of trans people to bring their legally recorded sex in line with their lived gender by way of self‐identification. In response to these moves toward trans inclusion, a unique coalition of trans‐exclusionary (gender critical) feminists and traditionalist conservatives has emerged to challenge these reforms. This coalition of policy opponents, mirroring historical issue frames that present homosexuals as predatory sexual deviants, campaign on a salient issue frame that presents transgender individuals and the expansion of trans rights as an inimical threat to the security, safety, and welfare of (cisgender) women, particularly in single‐sex spaces. In this paper, we address two questions. First, we ask: do trans‐exclusionary “protect women” issue frames over the alleged threat of trans persons to (cis) women shape mass public opinion? Second, we ask: in a relatively LGBT+ friendly policy environment, who supports the right to self‐identification for trans individuals? We answer these questions via an original pre‐registered survey experiment embedded within the 2021 Scottish Election Study. We find that trans‐exclusionary issue frames appealing to (cis) women's safety significantly depress support for trans rights, particularly among women respondents. Highlighting these concerns is an effective means of increasing already robust opposition to reforms designed to improve the welfare of transgender individuals, which should be of concern for proponents of self‐identification policies