Fat Tails Research Articles

Increasing or Diversifying Risk? Tail Correlations, Transmission Flows and Prices across Wind Power Areas

As wind power costs have declined, capacity has grown quickly, often times in adjacent areas. Price and volatility risk from wind power’s intermittency can be mitigated through geographic diversification and transmission. But wind power generation has a fat-tailed and right-skewed distribution. In this article we investigate how geographic diversification of wind power and the effect of wind power on market prices varies across the distribution of production. In a case study from Denmark and Sweden, we show that during tail-end production periods, correlations between areas increase substantially as does congestion in the transmission network. This leads to highly non-linear price effects. The marginal effect of wind power on the local prices is shown to be substantially higher at the 10th decile of wind power production. This has implications for valuation models of wind power projects and for operations of electricity markets with high penetrations of wind power.

Oar-miR-432 Regulates Fat Differentiation and Promotes the Expression of BMP2 in Ovine Preadipocytes.

The fat tail is a unique characteristic of sheep that represents energy reserves and is a complex adaptative mechanism of fat-tailed sheep to environmental stress. MicroRNA plays a significant role as regulators at the posttranscriptional level, but no studies have explained the molecular mechanisms of miRNA which regulate fat deposition in sheep tails. In this study, mRNA and miRNA analysis examined tail fat tissue from three Hu fat-tailed and three Tibetan thin-tailed sheep. After aligning to the reference sequences, 2,108 differentially expressed genes and 105 differential expression miRNAs were identified, including 1,247 up- and 861 downregulated genes and 43 up- and 62 downregulated miRNAs. Among these differentially expressed miRNAs, oar-miR-432 was one of the most downregulated miRNAs between Hu sheep and Tibetan sheep, and 712 genes were predicted to be targeted by oar-miR-432, 80 of which overlapped with DEGs. The Gene Ontology analysis on these genes showed that BMP2, LEP, GRK5, BMP7, and RORC were enriched in fat cell differentiation terms. The genes for BMP2 targeted by oar-miR-432 were examined using dual-luciferase assay. The oar-miR-432 mimic transfected into preadipocytes resulted in increased expression of BMP2. The marker gene PPAR-γ of fat differentiation had a lower expression than the negative control on days 0, 2, and 4 after induced differentiation. The decrease in the number of lipids in the oar-miR-432 mimic group detected by oil red O stain was also less than that in the negative control. This is the first study to reveal the fat mechanisms by which oar-miR-432 inhibits fat differentiation and promotes the expression of BMP2 in sheep tails.

On model robustness of the regime switching approach for pegged foreign exchange markets

We test the robustness of the regime switching model for pegged markets introduced by Drapeau et al. [How rational are the option prices of the Hong Kong dollar exchange rate? J. Derivatives, 2021, 28(3), 140–161]. In particular, there are two disputable underlying assumptions: (1) a Black and Scholes model with low volatility for the pre-depegging regime and (2) a thin tail distribution—Exponential type—for the time of the depegging. For the pre-depegging regime, we consider a bounded model within the peg—from Ingersoll and Rady. For the depegging time, we consider fat tail distributions more in line with catastrophic events—Pareto/Fréchet. We derive the option prices formula for each combination of these models. We then calibrate to option data from USD-HKD as well as EUR-CHF. In comparison to the benchmark model in Drapeau et al. [How rational are the option prices of the Hong Kong dollar exchange rate? J. Derivatives, 2021, 28(3), 140–161], it turns out that the relevant resulting characteristics—probability of a depegging before maturity, appreciation/depreciation at the depegging time as well as post-depegging volatility—are strongly robust in terms of model choice for this regime switching approach. However, from a term structure perspective, fat tail distributions fit the data significantly better and provide more rational depegging probabilities for short and long maturities.

Transcritical bifurcation of nonlinear electrostatic waves in a superthermal dusty plasma

The phase portraits and bifurcation properties of nonlinear dust ion-acoustic waves are studied in a complex plasma comprising cold dust particles, warm adiabatic ions, and κ-distributed electrons. A characteristic equation is obtained and solved numerically. The existence domain of fixed points and the stability of traveling wave solutions are discussed in the parameter space of Mach number M and dust concentration δ over a wide range of values of κ and ion temperature σ. It is shown that the motion dynamics of homoclinic orbits and nonlinear periodic orbits undergo a transcritical bifurcation at critical points of and , where two fixed points coalesce, and then switch their stabilities. We observe that at these bifurcation values with half-stable fixed points, the system supports a new analytical solitary wave solutions with much fatter tails than regular solitons. Furthermore, the existence domain of transcritical bifurcation parameters and transition between solitary and nonlinear periodic waves has been determined for different values of M and δ. It is found that the Mach number broadens the region prior to the bifurcation point, and enhances the onset of transition between modes, while the dust concentration has an opposite influence.

Time series estimation of the dynamic effects of disaster-type shocks

This paper provides three results for SVARs under the assumption that the primitive shocks are mutually independent. First, a framework is proposed to accommodate a disaster-type variable with infinite variance into a SVAR. We show that the least squares estimates of the SVAR are consistent but have non-standard asymptotics. Second, the disaster shock is identified as the component with the largest kurtosis. An estimator that is robust to infinite variance is used to recover the mutually independent components. Third, an independence test on the residuals pre-whitened by the Choleski decomposition is proposed to test the restrictions imposed on a SVAR. The test can be applied whether the data have fat or thin tails, and to over as well as exactly identified models. Three applications are considered. In the first, the independence test is used to shed light on the conflicting evidence regarding the role of uncertainty in economic fluctuations. In the second, disaster shocks are shown to have short term economic impact arising mostly from feedback dynamics. The third uses the framework to study the dynamic effects of economic shocks post-covid.

The network structure of global tax evasion evidence from the Panama papers

This paper builds on recent insights from network theory and on the rich dataset made available by the Panama Papers in order to investigate the micro-economic dynamics of tax-evasion. We model offshore financial entities documented in the Panama Papers as links between jurisdictions in the global network of tax evasion. A quantitative analysis shows that the resulting network, far from being a random collection of bilateral links, has key features of complex networks such as a core-periphery structure and a fat-tail degree distribution. We argue that these structural features imply that policy must adopt a systemic perspective to mitigate tax evasion. We offer three sets of insights from this perspective. First, we identify through centrality measures tax havens that ought to be priority policy targets. Second, we show that efficient tax treaties must contain exchange information clauses and link tax-havens to non-haven jurisdictions. Third, we show that the optimal deterrence strategies for a social-planner facing a strategic tax-evader in a Stackelberg competition can be characterized using the notion of Bonacich centrality.

Expression features of the ovine FTO gene and association between FTO polymorphism and tail fat deposition related-traits in Hu sheep

Fat mass and obesity associated (FTO) gene is a famous dominant predictor of obesity, and plays pivotal roles in the regulating fatty acid transport and fat metabolism. In the current study, the quantitative real-time PCR (qRT-PCR), DNA-pooled sequencing and KAspar assay were performed to detect the expression features of FTO and the polymorphisms of FTO associated with the tail fat weight related-traits of Hu sheep. The results indicated that the expression of FTO gene is widely expressed in the tissues tested, and the expression level of FTO in tail fat tissue was evidently higher compared with that in the other tissues. In addition, FTO showed the highest expression level in tail fat tissue at three months. The expression of FTO mRNA was lower in the large-tail fat group compared with that in the small-tail fat group in 6 months old. Subsequently, the polymorphism loci g. 23704451C > A detected in the FTO gene was confirmed to be significantly related to the tail length and the weight of tail fat. These results suggested that the polymorphism might be regarded as novel molecular marker for the breeding of small tail sheep.

Characterization of Taste Compounds and Sensory Evaluation of Soup Cooked with Sheep Tail Fat and Prickly Ash.

Sheep tail fat and prickly ash play an important role in improving the umami taste of mutton soup. In this work, the effects of prickly ash on key taste compounds in stewed sheep tail fat soup were investigated. Results showed that the taste intensity of sheep tail fat soup cooked with 0.2% prickly ash increased significantly. The concentration of organic acids and free amino acids in sheep tail fat soup significantly increased with the addition of prickly ash. The concentration of succinic acid (2.637 to 4.580 mg/g) and Thr (2.558 to 12.466 mg/g) increased the most among organic acids and amino acids, respectively. Spearman’s correlation analysis elucidated that seven taste compounds were positively correlated (correlation coefficient > 0.7) with the overall taste intensity of the soup sample including Thr, Asp, oxalic acid, lactic acid, citric acid, succinic acid, and ascorbic acid. Additional experiments and quantitative descriptive analysis further confirmed that Asp, lactic acid and citric acid were the key taste compounds to improve saltiness and umami taste in sheep tail fat soup with prickly ash.

Development and Application of a High-Resolution Melting Analysis with Unlabeled Probes for the Screening of Short-Tailed Sheep TBXT Heterozygotes.

Simple SummaryTBXT (c.333G > C; c.334G > T) has been identified as a molecular genetic marker in short-tailed sheep. This paper describes a high-resolution melting (HRM) analysis using unlabeled probes and asymmetric PCR for the detection of genetic variants of TBXT in short-tailed sheep populations. The detection results of this method are consistent with those of Sanger sequencing and can help farmers with marker-assisted breeding.The short-tailed phenotype has long been considered one of the best traits for population genetic improvement in sheep breeding. In short-tailed sheep, not only is tail fat eliminated but also the pubic area is exposed due to the lack of a tail covering, giving them an advantage in reproduction. Recent studies have shown that two linked mutations in sheep TBXT at nucleotides 333 and 334 are associated with the short-tailed phenotype. In the population of short-tailed sheep, several heterozygous mutants of this gene are found. In our research, we used high-resolution melting (HRM) to identify homozygous and heterozygous genotypes in a flock of short-tailed sheep and compared the results with those of Sanger sequencing, which were identical. This demonstrates that our established HRM method, a rapid and inexpensive genotyping method, can be used to identify homozygous and heterozygous individuals in short-tailed sheep flocks.

Disaster management in India’s construction industry during the Covid-19 pandemic

A biological disaster such as Covid-19 is unique in that, unlike other natural disasters, it does not engage the civil engineering community directly. Gaps in managing the pandemic exposed the lack of an institutional memory of handling pandemics, plus a lack of risk perception of ‘fat tail’ events. The impact on the construction sector was significant across the world, but different sections of the sector were affected differently. This paper documents and analyses these issues and concludes with a case study of how small and medium engineering practices endured the pandemic.

A fast regularisation of a Newtonian vortex equation

We consider equations of the form u_t = \nabla \cdot ( \gamma(u) \nabla \operatorname{N}(u)) , where \operatorname{N} is the Newtonian potential (inverse of the Laplacian) posed in the whole space \mathbb{R}^d , and \gamma(u) is the mobility. For linear mobility, \gamma(u)=u , the equation and some variations have been proposed as a model for superconductivity or superfluidity. In that case the theory leads to uniqueness of bounded weak solutions having the property of compact space support, and in particular there is a special solution in the form of a disk vortex of constant intensity in space u=c_1t^{-1} supported in a ball that spreads in time like c_2t^{1/d} , thus showing a discontinuous leading front. In this paper we propose the model with sublinear mobility \gamma(u)=u^\alpha , with 0<\alpha<1 , and prove that non-negative solutions recover positivity everywhere, and moreover display a fat tail at infinity. The model acts in many ways as a regularisation of the previous one. In particular, we find that the equivalent of the previous vortex is an explicit self-similar solution decaying in time like u=O(t^{-1/\alpha}) with a space tail with size u=O(|x|^{- d/(1-\alpha)}) . We restrict the analysis to radial solutions and construct solutions by the method of characteristics. We introduce the mass function, which solves an unusual variation of Burgers’ equation, and plays an important role in the analysis. We show well-posedness in the sense of viscosity solutions. We also construct numerical finite-difference convergent schemes.

Transcriptome Profiling of Developing Ovine Fat Tail Tissue Reveals an Important Role for MTFP1 in Regulation of Adipogenesis.

Fat-tail sheep exhibit a unique trait whereby substantial adipose tissue accumulates in the tail, a phenotype that is advantageous in many agroecological environments. In this study, we conducted histological assays, transcriptome analysis and functional assays to examine morphogenesis, characterize gene expression, and elucidate mechanisms that regulate fat tail development. We obtained the microstructure of tail before and after fat deposition, and demonstrated that measurable fat deposition occurred by the 80-day embryo (E80) stage, earlier than other tissues. Transcriptome profiling revealed 1,058 differentially expressed genes (DEGs) with six markedly different expression trends. GSEA enrichment and other downstream analyses showed important roles for genes and pathways involving in metabolism and that mitochondrial components were specifically overexpressed in the fat tail tissue of the 70-day embryo (E70). One hundred and eighty-three genes were further identified by leading edge gene analysis, among which, 17 genes have been reported in previous studies, including EEF1D, MTFP1, PPP1CA, PDGFD. Notably, the MTFP1 gene was highly correlated with the expression of other genes and with the highest enrichment score and gene expression change. Knockdown of MTFP1 in isolated adipose derived stem cells (ADSCs) inhibited cell proliferation and migration ability, besides, promoted the process of adipogenesis in vitro.

Generation of Realistic Synthetic Financial Time-series

Financial markets have always been a point of interest for automated systems. Due to their complex nature, financial algorithms and fintech frameworks require vast amounts of data to accurately respond to market fluctuations. This data availability is tied to the daily market evolution, so it is impossible to accelerate its acquisition. In this article, we discuss several solutions for augmenting financial datasets via synthesizing realistic time-series with the help of generative models. This problem is complex, since financial time series present very specific properties, e.g., fat-tail distribution, cross-correlation between different stocks, specific autocorrelation, cluster volatility and so on. In particular, we propose solutions for capturing cross-correlations between different stocks and for transitioning from fixed to variable length time-series without resorting to sequence modeling networks, and adapt various network architectures, e.g., fully connected and convolutional GANs, variational autoencoders, and generative moment matching networks. Finally, we tackle the problem of evaluating the quality of synthetic financial time-series. We introduce qualitative and quantitative metrics, along with a portfolio trend prediction framework that validates our generative models’ performance. We carry out experiments on real-world financial data extracted from the US stock market, proving the benefits of these techniques.

Transcriptome reveals key microRNAs involved in fat deposition between different tail sheep breeds.

MicroRNA (miRNA) is a kind of noncoding RNA whose function involved in various biological processes in neuronal maturation and adipocyte cells, such as differentiation, proliferation, development, apoptosis, and metabolism. Herein, miRNA-Seq was used to identify miRNAs in the tail fat tissue of Hu sheep (short-fat-tailed) and Tibetan sheep (short-thin-tailed). In this study, 155 differentially expression miRNAs (DE miRNAs) were identified, including 78 up-regulated and 77 down-regulated. Among these DE miRNAs, 17 miRNAs were reported and related with lipid metabolism. MiRanda and RNAhybrid software were used to predict the target genes of DE miRNAs, obtaining the number of targeting relationships is 38553. Target genes were enriched by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). 742 terms and 302 single pathways are enriched, including lipid metabolic process, response to lipid, cellular lipid catabolic process, lipid catabolic process, cellular lipid metabolic process, inositol lipid-mediated signaling, calcium channel activity, PI3K-Akt signaling pathway, MAPK signaling pathway, ECM-receptor interaction, AMPK signaling pathway, Wnt signaling pathway and TGF-beta signaling pathway. Notably, miR-379-5p was associated with tail fat deposition of sheep. Dual-Luciferase reporter assays showed miR-379-5p and HOXC9 had targeted relationship. The result of RT-qPCR showed that the expression trend of miR-379-5p and HOXC9 was opposite. miR-379-5p was down-regulated and highly expressed in tail adipose tissue of Tibetan sheep. HOXC9 was highly expressed in adipose tissue of Hu sheep. These results could provide a meaningful theoretical basis for studying the molecular mechanisms of sheep tail adipogenesis.

Revisiting the Copula-Based Trading Method Using the Laplace Marginal Distribution Function

Pairs trading under the copula approach is revisited in this paper. It is well known that financial returns arising from indices in markets may not follow the features of normal distribution and may exhibit asymmetry or fatter tails, in particular. Due to this, the Laplace distribution is employed in this work to fit the marginal distribution function, which will then be employed in a copula function. In fact, a multivariate copula function is constructed on two indices (based on the Laplace marginal distribution), enabling us to obtain the associated probabilities required for the process of pairs trade and creating an efficient tool for trading.

Inference in mixed causal and noncausal models with generalized Student’s t-distributions

The properties of Maximum Likelihood estimator in mixed causal and noncausal models with a generalized Student’s t error process are reviewed. Several known existing methods are typically not applicable in the heavy-tailed framework. To this end, a new approach to make inference on causal and noncausal parameters in finite sample sizes is proposed. It exploits the empirical variance of the generalized Student’s t, without the existence of population variance. Monte Carlo simulations show a good performance of the new variance construction for fat tail series. Finally, different existing approaches are compared using three empirical applications: the variation of daily COVID-19 deaths in Belgium, the monthly wheat prices, and the monthly inflation rate in Brazil.

Predictors of Excess Return in a Green Energy Equity Portfolio: Market Risk, Market Return, Value-at-Risk and or Expected Shortfall?

The rapid growth of electric vehicles, solar roofs, and wind power suggests that the potential growth in green equity investments is an emerging trend. Accordingly, this study measured the predictors of excess equity returns in a portfolio of global green energy producers, from 2010 to 2019. Fixed-effects panel data regressions of daily returns, followed by quantile regressions, were performed. There was some support for the explanation of green equity returns by market returns and market risk (beta), as indicated by the single-factor Capital Asset Pricing Model (CAPM), and the multifactor Fama–French Three-Factor and Fama–French Five-Factor Models. The most significant predictors of green equity returns were Value-at-Risk at a 95% confidence level, and Value-at-Risk at a 99% confidence level. Expected Shortfall was another extreme risk value measure. The importance of extreme value measures suggests the presence of fat-tailed leptokurtic distributions, whereby excess returns were explained by the risk of loss given adverse conditions, primarily at 95% confidence. We conclude that the proliferation of small firms and new entrants in the renewable energy sector has led to the explanation of returns by extreme values of risk.

Quantile Treatment Effect of Zinc Lozenges on Common Cold Duration: A Novel Approach to Analyze the Effect of Treatment on Illness Duration.

Calculation of the difference of means is the most common approach when analyzing treatment effects on continuous outcomes. Nevertheless, it is possible that the treatment has a different effect on patients who have a lower value of the outcome compared with patients who have a greater value of the outcome. The estimation of quantile treatment effects (QTEs) allows the analysis of treatment effects over the entire distribution of a continuous outcome, such as the duration of illness or the duration of hospital stay. Furthermore, most of these outcomes have asymmetric distributions with fat tails, and censored observations are not uncommon. These features can be accounted for in the analysis of the QTE. In this paper, we use the QTE approach to analyze the effect of zinc lozenges on common cold duration. We use the data set of the Mossad (1996) trial with zinc gluconate lozenges, and three data sets of trials with zinc acetate lozenges. In the Mossad (1996) trial, zinc gluconate lozenges shortened common cold duration on average by 4.0 days (95% CI 2.3–5.7 days). However, the QTE analysis indicates that 15- to 17-day colds were shortened by 8 days, and 2-day colds by just 1 day, for the group taking zinc lozenges. Thus, the overall 4.0-day average effect of zinc gluconate lozenges in the Mossad (1996) trial is inconsistent with our QTE findings for both short and long colds. Similar results were found in our QTE analysis of the pooled data sets of the three zinc acetate lozenge trials. The average effect of 2.7 days (95% CI 1.8–3.3 days) was inconsistent with the effects on short and long colds. The QTE approach may have broad usefulness for examining treatment effects on the duration of illness and hospital stay, and on other similar outcomes.

Hydrodynamics of horizontal heated buoyant jet in linearly stratified fluids

Horizontal buoyant jets in stratified fluids are investigated by employing a computational fluid dynamic model validated by experimental data. The characteristics of time mean flow, turbulence, and entrainment are quantified. We observed that turbulence parameters such as the turbulent kinetic energy, the turbulence dissipation rate, and turbulent viscosity attained their maximum values in the horizontal region. Here, the entrainment coefficient also reaches the maximum due to the instantaneous instability of the flow. The ascent region consists of the acceleration and deceleration stages due to the stratified ambience reversing the sign of buoyancy flux. In the acceleration ascent region, the entrainment coefficient stabilizes around 0.05. In the deceleration stage, the transition of the flow regime from plume- to jet-like regulates the entrainment. At the end of the ascent region, the jet reaches the maximum rise height (Hmax), which can be well predicted by a semiempirical function at a given Richardson number, buoyancy frequency, and Reynolds number. An enhancement of turbulent parameters is observed near the Hmax and could be attributed to overshooting and shearing between the up- and downflow. Analysis of density and velocity profiles shows the heavy fluids on the lower side of the jet core vertically separating from the center fluids, which drifted the velocity profile from a Gauss to a fat-tailed distribution and broke the self-similarity.

Mixing-demixing transition and void formation in quasi-2D binary mixtures on a sphere

Motivated by observations of the heterogeneous domain structure on the surface of cells and vesicles and by domain formation due to the adsorption of complex molecules onto composite membranes, we consider a minimal quasi-2D model to describe the structure of binary mixtures on the surface of a spherical particle. We study the effect of miscibility and adsorbing particle (AP) addition on the mixture structure. We define a new scalar quantity, the geodesic mixing parameter Ξ, through which we detail the effect of miscibility and the role of preferential affinity of APs with one of the two components of the mixture, distinguishing unambiguously between mixing and demixing solely induced by APs. Finally, by inspecting the distributions of void sizes, we show how void formation is ruled by miscibility and AP-mixture interactions, which control the transition from exponentially tailed to fat-tailed distributions.