Fat Tails Research Articles

Bio‐based lamb tail fat phase change material with enhanced thermal properties by incorporation of cyclophosphazene additives

AbstractAmong organic phase‐change materials (PCM), paraffin is commonly used, but it is not environmentally friendly due to its petrochemical origin. For efficient utilization of solar or thermal energy, new PCM are needed, or it is necessary to improve the thermal properties of existing materials. Therefore, the utilization of renewable alternatives such as lamb's tail fat as a latent heat storage material is of particular importance for the evaluation of bio‐based waste oils. In this study, new PCM were developed by using different concentrations of cyclophosphazene derivatives as an additive to the starting lamb tail fat (LTF) material. According to the results, doping the LTF with 1% and 2% hexa(N,N‐dibutyl‐4‐aminophenoxy)cyclotriphosphazene (HBACP) the heat of fusion is significantly improved, while the 1% hexa(2‐ethylhexyloxy)cyclotriphosphazene (HEHCP) doping decreased the heat of fusion. In a comparison of various doped PCM, it was found that the tail fat doped with 1% HBACP had a heat of fusion of 166.6 kJ/kg, but a lower specific heat capacity and thermal conductivity than that doped with 2% HBACP. On the other hand, 1% HEHCP had the lowest thermal conductivity but a higher specific heat capacity than 1% HBACP. In addition, it was found that the PCM developed by incorporating HBACP could be operated as a cooling fluid for photovoltaic modules or as a working fluid in concentrated solar energy systems due to the higher heat of fusion value of 1% HBACP and the higher specific heat capacity of 2% HBACP, which consists of lamb's tail fat.

Disposition effect and its outcome on endogenous price fluctuations

AbstractWe have developed a financial market model that incorporates the Disposition Effect, which refers to traders’ tendency to avoid realizing losses. Specifically, our model replicates several stylized facts commonly observed in financial markets, such as fat tails and volatility clustering. These market characteristics can be attributed to the Disposition Effect, especially when the trading behavior of agents aligns with the findings of Ben-David and Hirshleifer (Rev Financ Stud 25(8):2485–2532, 2012). To demonstrate this, we examine two versions of the model: one where a class of agents exhibits a high degree of Disposition Effect and another where traders are not influenced by it. By comparing the simulated time series generated by both versions, we find that the one with agents affected by the Disposition Effect better replicates the features observed in real financial markets. This holds true for both the deterministic and stochastic versions of the model.

Enrichment of C17:0-rich saturated fatty acids from sheep tail fat for adjuvant therapy of non-small-cell lung cancer.

The online version contains supplementary material available at 10.1007/s10068-023-01504-w.

The Emergence of the Normal Distribution in Deterministic Chaotic Maps.

The central limit theorem states that, in the limits of a large number of terms, an appropriately scaled sum of independent random variables yields another random variable whose probability distribution tends to attain a stable distribution. The condition of independence, however, only holds in real systems as an approximation. To extend the theorem to more general situations, previous studies have derived a version of the central limit theorem that also holds for variables that are not independent. Here, we present numerical results that characterize how convergence is attained when the variables being summed are deterministically related to one another through the recurrent application of an ergodic mapping. In all the explored cases, the convergence to the limit distribution is slower than for random sampling. Yet, the speed at which convergence is attained varies substantially from system to system, and these variations imply differences in the way information about the deterministic nature of the dynamics is progressively lost as the number of summands increases. Some of the identified factors in shaping the convergence process are the strength of mixing induced by the mapping and the shape of the marginal distribution of each variable, most particularly, the presence of divergences or fat tails.

Fractional advection diffusion asymmetry equation, derivation, solution and application

The non-Markovian continuous-time random walk model, featuring fat-tailed waiting times and narrow distributed displacements with a non-zero mean, is a well studied model for anomalous diffusion. Using an analytical approach, we recently demonstrated how a fractional space advection diffusion asymmetry equation, usually associated with Markovian Lévy flights, describes the spreading of a packet of particles. Since we use Gaussian statistics for jump lengths though fat-tailed distribution of waiting times, the appearance of fractional space derivatives in the kinetic equation demands explanations provided in this manuscript. As applications we analyse the spreading of tracers in two dimensions, breakthrough curves investigated in the field of contamination spreading in hydrology and first passage time statistics. We present a subordination scheme valid for the case when the mean waiting time is finite and the variance diverges, which is related to Lévy statistics for the number of renewals in the process.

Application of Copula Methods in Financial Risk Management: Case of the Zimbabwe Stock Exchange and the Victoria Falls Stock Exchange.

In order to minimize risks and create a safe investing environment, financial risk management is becoming more and more crucial for individuals, financial organizations, and even entire nations. Accurately assessing financial risks and using that information to inform wise investment choices can give an investor a competitive edge as well as significant returns. In actuality, real-world financial variables limit the ability to estimate financial risks. On the other hand, a wealth of data indicates that financial variables typically have asymmetric dependency, skewness, and fat tails. In three ways, the conventional approaches to financial risk management based on normally distributed hypotheses are put to the test by these stylized characteristics of financial variables. First, the univariate normal distribution or other elliptical distributions are unable to adequately fit the distribution of the univariate variable. Second, despite their straightforward tractability, multivariate variables’ extra kurtosis and skewness are not captured by their normal distribution. As a result, the dependence risks associated with multivariate financial variables may be underestimated. Finally, when the joint distribution of various variables is non-elliptical, linear correlation which is typically employed to characterize the dependence of various variables in traditional portfolio risk management is likewise insufficient. This research uses a promising technique based on copulas in conjunction with GARCH and realized volatility models to examine the risks associated with multivariate financial variables in order to address these issues. The multivariate distributions are constructed using copulas in conjunction with GARCH and Realized Volatility models which are then utilized to evaluate portfolio risks in financial market. The findings demonstrate that copula-based models outperform conventional models in fitting financial data. Second, a variety of marginal models have a notable impact on the value at risk of the portfolio, including the GARCH and realized volatility models. Lastly, both the dependence structure and the marginal distribution exhibit notable skewness. Consequently, compared to the normal or Student-t distribution, the skewed Student-t distribution fits some datasets better.

Insight into the current genomic diversity, conservation status and population structure of Tunisian Barbarine sheep breed.

Local livestock breeds play a crucial role in global biodiversity, connecting natural and human-influenced environments and contributing significantly to ecosystem services. While commercial breeds dominate industrial systems, local livestock breeds in developing countries, like Barbarine sheep in Tunisia, are vital for food security and community maintenance. The Tunisian Barbarine sheep, known for its adaptability and distinctive fat-tailed morphology, faces challenges due to historical crossbreeding. In this study, the Illumina Ovine SNP50K BeadChip array was used to perform a genome-wide characterization of Tunisian Barbarine sheep to investigate its genetic diversity, the genome structure, and the relationship within the context of Mediterranean breeds. The results show moderate genetic diversity and low inbreeding. Runs of Homozygosity analysis find genomic regions linked to important traits, including fat tail characteristics. Genomic relationship analysis shows proximity to Algerian thin-tailed breeds, suggesting crossbreeding impacts. Admixture analysis reveals unique genetic patterns, emphasizing the Tunisian Barbarine's identity within the Mediterranean context and its closeness to African breeds. Current results represent a starting point for the creation of monitoring and conservation plans. In summary, despite genetic dilution due to crossbreeding, the identification of genomic regions offers crucial insights for conservation. The study confirms the importance of preserving unique genetic characteristics of local breeds, particularly in the face of ongoing crossbreeding practices and environmental challenges. These findings contribute valuable insights for the sustainable management of this unique genetic reservoir, supporting local economies and preserving sheep species biodiversity.

Efficiency of grazing for adult culled sheep in the southern regions of Kyrgyzstan

This article provides an analysis of the fattening of adult cull ewes of the Gissar and Gissar-Kyrgyz breeds, and provides research results. In Kyrgyzstan, sheep meat, especially fat-tailed sheep, is very popular among the local population. It is important to note that a breeding system is used there, which is based on year-round transhumance and pasture keeping of sheep. This allows you to achieve several goals: firstly, to produce relatively inexpensive products; secondly, to effectively use mountain and foothill pastures for grazing sheep; and, finally, to ensure the production of environmentally friendly lamb meat and fat tail fat for traditional medicine. Sheep feeding plays an important role in increasing the volume and improving the quality of lamb production. In solving the problems of increasing meat production in the Kyrgyz Republic, the leading place belongs to sheep breeds for meat and fat production. Fattailed sheep have high meat and fat productivity and early maturity. These qualities make them valuable for replenishing meat resources and ensuring high meat and fat qualities.

FEATURES OF MODELING INVESTMENT PORTFOLIO RISKS UNDER CRISIS CONDITIONS

The main goal of investment activity is to minimize the level of investment risk while finding the optimal balance between return and risk. This process involves accounting for probabilistic factors that arise from the inherent uncertainty in financial activities. Investors are constantly faced with the challenge of managing these risks, particularly in the context of financial markets that exhibit significant volatility and unpredictability. In this regard, the search for models that allow for accurate risk assessment and management is a key aspect of modern portfolio theory. Currently, one of the most widely used models for solving the portfolio optimization problem is the Harry Markowitz model, often referred to as Modern Portfolio Theory (MPT). The Markowitz portfolio optimization model seeks to achieve two possible outcomes: either by minimizing the variance (or risk) of the portfolio's return at a given level of expected return, or by maximizing the expected return at a given level of variance (risk). Despite the obvious advantages of the Markowitz model, such as its widespread applicability and relative ease of implementation in practice, it has several notable limitations. One key drawback is that the model uses variance as a measure of risk, which treats deviations from the expected return symmetrically. This means that both positive (upward) and negative (downward) deviations are considered equally risky, which contradicts the typical investor's view, as they are more concerned with downside risk rather than upside potential. Another limitation of the Markowitz model is the assumption of normally distributed asset returns. In reality, financial markets do not always conform to this assumption. Extreme returns, often referred to as "fat tails," tend to occur more frequently than what would be predicted by a normal distribution. In response to these limitations, there has been growing interest in the development of alternative models that can more accurately capture the complexities of financial markets. One such approach is the use of stochastic models that take into account the time-varying nature of asset volatility and the impact of extreme events. These models seek to minimize portfolio investment risk by incorporating more realistic assumptions about market behavior, including the presence of volatility clustering and non-normal return distributions. The article presented is focused on a stochastic model aimed at minimizing portfolio investment risk. This model addresses some of the shortcomings of the traditional Markowitz framework by better accounting for the unpredictable and often turbulent nature of financial markets. In particular, it has been shown that systematic risk factors play a dominant role in shaping the expected return of an investment portfolio, especially in economies undergoing transition or transformation.

Robust k -Means-Type Clustering for Noisy Data.

Data clustering is a fundamental machine learning task that seeks to categorize a dataset into homogeneous groups. However, real data usually contain noise, which poses significant challenges to clustering algorithms. In this article, motivated by how the k -means algorithm is derived from a Gaussian mixture model (GMM), we propose a robust k -means-type algorithm, named k -means-type clustering based on t -distribution (KMTD), by assuming that the data points are drawn from a special multivariate t -mixture model (TMM). Compared to the Gaussian distribution, the t -distribution has a fatter tail. The proposed algorithm is more robust to noise. Like the k -means algorithm, the proposed algorithm is simpler than those based on a full TMM. Both synthetic and actual data are used to illustrate the proposed algorithm's performance and efficiency. The experimental results demonstrated that the proposed algorithm operates more quickly than other sophisticated algorithms and, in most cases, achieves higher accuracy than the other algorithms.

Quantitative and Qualitative Characteristic of Thin and Fat Tailed Sheep

This study aims to determine the Quantitative and Qualitative Characteristic of Thin and Fat Tail Sheep. The study starts from August 2023 until December 2023 in PT Juara Agroniaga Sejahtera, Jepangrejo Village, Blora City District, Blora Regency. The material used in this study was 39 Thin-tailed Sheep and 28 Fat-tailed Sheep aged 1-2 years. The variables measured where Quantitative data were body height (BH), body length (BL), chest circumference (CC), body weight (BW), and Qualitative data were fur color and horn. Data were analyzed using the Pearson correlation, and regression method. The results of this study showed that the correlation between body height (BH), body length (BL), chest circumference (CC) with body weight (BW) in DET and DEG were 0.62, 0.71, 0.72, 0.27, 0.69, 0.65 respectively. The results of this study showed that the regression between body height (BH), body length (BL), chest circumference (CC) with body weight (BW) in DET and DEG were BW = -14.03 + 0.71 BH; BW = -15.45 + 0.74 BL; BW = -21.95 + 0.65 CC and BW = 8.69 + 0.33 BH; BW = -6.76 ± 0.59 BL; BW = -19.43 ± 0.65 CC respectively. The results of this study showed that the dominant wool color pattern of DET is single white, 74.36% white, 15.38% black, and 5.13% brown and DEG is single white, 67.86% white, 14.29% black, and 7.14% brown. DET was 2.56% with horn then 97.44% without horn and DEG is 100% without horn.

Inheritance of the Fat Tail Parameters in the Rams and Ewes Offsprings with Different Sizes of the Fat Tail

Inheritance of the Fat Tail Parameters in the Rams and Ewes Offsprings with Different Sizes of the Fat Tail

Option pricing revisited: The role of price volatility and dynamics

The analysis of option pricing in derivative markets has commonly relied on the Black-Scholes model. This paper presents a conceptual and empirical analysis of option pricing with a focus on the validity of key assumptions embedded in the Black-Scholes model. Going beyond questioning the lognormality assumption, we investigate the role played by two assumptions made about the nature of price dynamics: quantile-specific departures from a unit root process, and the role of quantile-specific drift. Our analysis relies on a Quantile Autoregression (QAR) model that provides a flexible representation of the price distribution and its dynamics. Applied to the soybean futures market, we examine the validity of assumptions made in the Black-Scholes model along with their implications for option pricing. We document that price dynamics involve different responses in the tails of the distribution: overreaction and local instability in the upper tail, and underreaction in the lower tail. Investigating the implications of our QAR analysis for option pricing, we find that failing to capture local instability in the upper tail is more serious than failing to capture “fat tails” in the price distribution. We also find that the most serious problem with the Black-Scholes model arises in its representation of price dynamics in the lower tail.

Spatiotemporal Variation and Long-Range Correlation of Groundwater Levels in Odessa, Ukraine

Increasing groundwater levels (GWLs) may become one of the most serious issues for the city of Odessa, Ukraine. This study investigated the spatial distribution characteristics and multifractal scaling behaviour of the groundwater-level/-depth fluctuations for a Quaternary aquifer in the city of Odessa using a geostatistical approach and multifractal detrended fluctuation analysis (MF-DFA). These two methods were applied to monthly GWL fluctuation time series from 1970 to 2020 to monitor 72 hydrogeological wells situated in different parts of the city of Odessa. The spatial distribution of the GWLs revealed an overall trend of decline and recovery from 1970 to 2020 in the study area, except for most of the southern region, where a persistent recovery of the groundwater depth was observed. The MF-DFA results suggest that the dynamics of the GWL fluctuations have multifractal characteristics in the Odessa area. In addition, both long-range correlations and fat-tail probability distribution contribute to the multifractality. However, long-range correlations among the fluctuations made a major contribution to the observed multifractality of the GWL fluctuation time series. The generalised Hurst exponents show a wide range of change (0.20 < h(q) < 2.85), indicating the sensitivity of the GWL fluctuations to changes in small-scale factors and large-scale factors. Regarding the long-range correlations of the GWL depths, the Hurst exponents (q = 2) demonstrated the positive persistence of groundwater-depth recovery in the southern region and the persistence of groundwater-depth variation in the other regions of the study area. The dynamic changes in the GWL depths in the Odessa area may be influenced by both natural and anthropogenic factors.

Identification of AGO2 and PLEC genes polymorphisms in Hu sheep and their relationship with body size traits

The body size traits are major traits in livestock, which intuitively displays the development of the animal’s bones and muscles. This study used PCR amplification, Sanger sequencing, KASPar genotyping, and quantitative real-time reverse transcription PCR (qRT-PCR) to analyze the Single-nucleotide polymorphism and expression characteristics of Argonaute RISC catalytic component 2 (AGO2) and Plectin (PLEC) genes in Hu sheep. Two intron mutations were found in Hu sheep, which were AGO2 g.51700 A > C and PLEC g.23157 C > T, respectively. Through association analysis of two mutation sites and body size traits, it was found that AGO2 g.51700 A > C mainly affects the chest and cannon circumference of Hu sheep of while PLEC g.23157 C mainly affects body height and body length. The combined genotypes of AGO2 and PLEC genes with body size traits showed SNPs at the AGO2 g.51700 A > C and PLEC g.23157 C > T loci significantly improved the body size traits of Hu sheep. In addition, the AGO2 gene has the highest expression levels in the heart, rumen, and tail fat, and the PLEC gene is highly expressed in the heart. These two loci can provide new research ideas for improving the body size traits of Hu sheep.

Влияние пребиотических добавок на состав и свойства курдючного жира баранчиков калмыцкой породы

Purpose. Study of the influence of prebiotic feed additives on the physicochemical parameters of fat-tail fat of Kalmyk breed rams. Materials and Methods. When fattening animals using lactulose-containing additives in their diets, the generally accepted VIJ method was used, and the phyco-chemical properties and composition of fat-tail fat were carried out in certified laboratories according to the methods provided for by GOSTs. The resulting digital material was processed using the statistical package Microsoft Excel, and the reliability of the data was checked using the Student's criterium. Results. Feeding prebiotic additives “Laktuvet-1” and “LaktuSuper” to fattening rams affected the melting point of fat-tail fat of both 4- and 7-month-old animals. A decrease in the melting temperature of fat was recorded in experimental group I by 0.14 and 0.26°C (P≤0.05), in experimental group II – by 0.21 and 0.32°C (P≤0.01) compared with the control group. The iodine number of fat significantly increased in animals of the experimental groups of 4 months of age by 0.39 (P≤0.05) and 0.51 (P≤0.05), of 7 months of age – by 0.58 (P≤0.05). 01) and 0.76 (P≤0.01) compared to the control group. In the fat-tail fat of 4-month-old rams, compared with the control, the content of unsaturated fatty acids increased in experimental group I by 1.72% (P≤0.05), essential fatty acids in experimental group II – by 2.26% (P≤0.01), the total level of saturated fatty acids decreased in both experimental groups. At the age of 7-month rams in experimental groups I and II, among monounsaturated fatty acids, a significant difference compared to the control was obtained only in the content of oleic acid in fat-tail fat, which was 0.34 (P≤0.05) and 0.42% (P≤0.01). The amount of unsaturated fatty acids significantly exceeded this indicator in the control group by 0.53 (P≤0.01) and 0.83% (P≤0.01). The decrease in the amount of saturated fatty acids in the experimental groups was ensured by a significant decrease in the content of palmitic acid in fat-tail fat by 0.31 (P≤0.05) and 0.44% (P≤0.01) and stearic acid by 0.20 (P≤0.05) and 0.27% (P≤0.05) compared to control. Conclusion. The feed additives “Lactuvet-1” and “LactuSuper” had an effective effect on the composition and physicochemical properties of fat-tail fat of fattening rams. The active substances of prebiotic additives helped to reduce the melting point and improve the chemical and fatty acid composition of tail fat.

Advances in nowcasting economic activity: The role of heterogeneous dynamics and fat tails

A key question for households, firms, and policy makers is: how is the economy doing now? This paper develops a Bayesian dynamic factor model that allows for nonlinearities, heterogeneous lead–lag patterns and fat tails in macroeconomic data. Explicitly modeling these features changes the way that different indicators contribute to the real-time assessment of the state of the economy, and substantially improves the out-of-sample performance of this class of models. In a formal evaluation, our nowcasting framework beats benchmark econometric models and professional forecasters at predicting US GDP growth in real time.

Expectation and Optimal Allocations in Existential Contests of Finite, Heavy-Tail-Distributed Outcomes

Financial time series and other human-driven, non-natural processes are known to exhibit fat-tailed outcome distributions. That is, such processes demonstrate a greater tendency for extreme outcomes than the normal distribution or other natural distributional processes would predict. We examine the mathematical expectation, or simply “expectation”, traditionally the probability-weighted outcome, regarded since the seventeenth century as the mathematical definition of “expectation”. However, when considering the “expectation” of an individual confronted with a finite sequence of outcomes, particularly existential outcomes (e.g., a trader with a limited time to perform or lose his position in a trading operation), we find this individual “expects” the median terminal outcome over those finite trials, with the classical seventeenth-century definition being the asymptotic limit as trials increase. Since such finite-sequence “expectations” often differ in values from the classic one, so do the optimal allocations (e.g., growth-optimal). We examine these for fat-tailed distributions. The focus is on implementation, and the techniques described can be applied to all distributional forms. We make no assertion that the empirical data for any financial time series comports to the generalized hyperbolic distribution (GHD), which we will use as a proxy of any heavy-tailed distribution herein. Rather, we have selected the GHD to highlight the process for determining expectation and other important time-dependent metrics in existential contests, using the GHD as a generic proxy for the specific distributional form an implementor of the presented technique might ascribe to the empirical data.

Equity Price Dynamics under Shocks: In Distress or Short Squeeze

This paper proposes a simple bounded stochastic motion to model equity price dynamics under shocks. The stochastic process has a quasi-bounded boundary which can be breached if the probability leakage condition is met. The quasi-boundedness of the process at the boundary can thus provide an indicator of the possible risk of equities under price shocks or in distress. Empirical calibration of the model parameters of the proposed process for equities can be performed easily due to the availability of an analytically tractable probability density function which generates fat-tailed distributions consistent with empirical observations. The volatility and mean-reversion of the S&P500 dynamics calibrated by the process are positively and negatively co-integrated, respectively, with the VIX index representing the level of market distress. The process captures the high likelihood of Hertz’s default about two months earlier, using only information until that point, and before the firm filed for Chapter 11 bankruptcy in May 2020 as a result of the COVID-19 pandemic. Empirical calibration of the process for GameStop’s stock price shows that the short squeeze in the stock occurred when the condition for breaching the upper boundary was met on 14 January 2021, i.e., about two weeks before major short-sellers closed out their positions with significant losses. The trading volume of the stock was positively co-integrated with the probability leakage ratio.

Growth Respons of Javanese Fat Tail Sheep (DEG) on Probiotic Supplementation in Diet with Different Nitrogen Source

The growth performance of ruminant animals depend mainly on the quantity and quality of the feed provided. In feedlot systems, the ruminant diet consists of roughages, which are in most cases preserved as native grass or hay, and concentrate feeds as Nitrogen sources. To meet their nutritional requirements and achieve the expected growth performance, these animals must be provided with adequately balanced diets. The aim of present study was to investigate the effect of probiotic supplementation in diet with different nitrogen sources on growth performance of Javanese Fat Tail Lambs. The study was conducted experimently using 48 male lambs 6-7 month of age and average body weight 18,7±2,6 kg. The probiotic tested was EM-4, a probiotic containing Lactobacillus sp, Streptomices sp. and Sacharomyces cerevisiae, with tested levels were: zero (R0, control), 0.5 ml (R1), 1.0 ml (R2), and 1.5 ml (R3) per head per day. Two types of diets were prepared, each composed of 70% native grass and 30% concentrate with different nitrogen source, both formulated to be isoprotein and isoenergy. The experimental lambs were divided into 8 groups of 6 lambs each group, each placed randomly in 48 similar individual cages. Experimental diets were given twice a day in equal portions at 08.30 in the morning and at 16.30 in the afternoon. The amount of remaining feed was measured every day at 06.00 am. Each lamb was weighed once a week for a 120-day experimental period. Data were analyzed using ANOVA according to Randomized Block Design, and further tested by the Least Significant Difference Test. The results showed that probiotic supplementation in diet had no effect (P>0.05) on Dry Matter Intake (DMI), but could increase (P<0.05) Daily Weight Gain (PBBH), Growth Rate (LP), and reduced the Feed Conversion Rate (FCR), both in the lambs fed diet with nitrogen source from Turi (Sesbania grandiflora) leaf meal (R1) and Tofu Dreg (R2). The DEG fed R1 showed a 7.7% higher PBBH than those of fed R2. The probiotic supplementation on R1 and R2 gave the optimum effect on PBBH and FCR at the supplementation level of 1.5 ml/head/day.