Fat Tails Research Articles

Fat Tails, Flat Tails, and Willingness to Pay

Fat Tails, Flat Tails, and Willingness to Pay

Lipase-catalyzed interesterification of Sunite sheep tail fat and flaxseed oil provides a fat having a unique fatty acid content and favorable physicochemical and nutritional properties.

The aim of this study is to combine flaxseed oil (FO), rich in α-linolenic acid (ALA), with Sunite sheep tail fat (STF) through a lipase-catalyzed transesterification reaction, in order to produce an edible oil with a fatty acid ratio suitable for human needs. Initially, the optimal conditions for esterification were determined using the Box-Behnken design, with the measurement criterion being the content of ALA at the sn-2 position. The results indicated that the highest content of sn-2 ALA was obtained under the conditions of using 6.8 wt% Lipozyme®RMIM as the catalyst, a reaction temperature of 57°C, a reaction time of 3.3 h, and a substrate mass ratio of 5.6:4.4 for STF and FO. This led to the rapid breaking and recombining of molecular bonds, resulting in the interesterified fat (IF) with the highest content of ALA at the sn-2 position. Comparing STF and FO, IF exhibited excellent fatty acid composition and content. Furthermore, IF had a lower melting point and crystallization temperature compared to STF, and its solid fat content decreased with increasing temperature, completely melting at temperatures above 30°C. Thus, IF is a synthesized fat with excellent properties from both animal and vegetable sources.

Abstract 4138: Evaluation of breast triple-negative 4T1-derived tumor metastatic development in gender-different mouse

Abstract Background and Objective: Breast cancer in men is a rare and less-studied case, with therapeutic strategies predominantly relying on clinical treatment protocols established for women. To support the clinical treatment concept, Dr. Martin-Martinez's lab observed no differences in the time of orthotopic breast mammary fat pad tumor development, necrosis, or color change of tumor tissue between male and female mice. However, the clinical treatment readout, especially tumor metastasis, is different in men and women, and current models for breast cancer are inadequate due to the absence of metastases. It is necessary to evaluate the development of breast cancer 4T1-derived tumor metastasis in male and female mice. Method and Result: 4T1-Luc breast cancer cells were implanted in male and female Balb/c mice via various routes, including inguinal fat pad injection, tail vein injection, caudal artery injection, portal vein injection, and Intratibial Injection. Illuminance images showed no significant differences in tumor metastatic development between genders for inguinal fat pad, tail vein, and intratibial injections. However, following caudal artery injection, early-stage metastasis differed; male mice developed femoral head metastasis, while female mice developed lung metastasis. In the late stage, male mice displayed lung and femoral bone metastasis, while female mice primarily showed lung metastasis with barely bone metastasis. Conclusion: While both male and female mice showed similar primary breast tumor development, mouse gender affected tumor metastasis differently, particularly when tumor cells went through the caudal artery. Male mice presented earlier femoral head metastasis and less lung metastasis than female mice. Based on this work, sex hormones would affect both hormone-related and nonhormone-related tumor metastasis. To elucidate whether this phenomenon is caused by estrogen or androgen or to test if a drug has any beneficial effects, HD Biosciences provides established tumor metastatic cell-delivering platforms and over 1000 cancer cell lines for target validation and drug efficacy study. Citation Format: Chunhong Shao, Melanie He, Luke Tsung-Huang Tsai. Evaluation of breast triple-negative 4T1-derived tumor metastatic development in gender-different mouse [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4138.

Quasar Microlensing Statistics and Flux-ratio Anomalies in Lens Models

Precise lens modeling is a critical step in time delay studies of multiply imaged quasars, which are key for measuring some important cosmological parameters (especially H 0). However, lens models (in particular those semi-automatically generated) often show discrepancies with the observed flux ratios between the different quasar images. These flux-ratio anomalies are usually explained through differential effects between images (mainly microlensing) that alter the intrinsic magnification ratios predicted by the models. To check this hypothesis, we collect direct measurements of microlensing to obtain the histogram of microlensing magnifications. We compare this histogram with recently published model flux-ratio anomalies and conclude that they cannot be statistically explained by microlensing. The average value of the model anomalies (0.74 mag) significantly exceeds the mean impact of microlensing (0.33 mag). Moreover, the histogram of model anomalies presents a significant tail with high anomalies (∣Δm∣ ≥ 0.7 mag), which is completely unexpected from the statistics of microlensing observations. Microlensing simulations neither predict the high mean nor the fat tail of the histogram of model anomalies. We perform several statistical tests which exclude that microlensing can explain the observed flux-ratio anomalies (although Kolmogorov–Smirnov, which is less sensitive to the tail of the distributions, is not always conclusive). Thus, microlensing cannot statistically explain the bulk of flux-ratio anomalies, and models may explore different alternatives to try to reduce them. In particular, we propose to complement photometric observations with accurate flux ratios of the broad emission lines obtained from integral field spectroscopy to check and, ideally, constrain lens models.

Analysing the genetic diversity of three sheep breeds in Turkey and nearby countries using 50 K SNPs data

This study analysed the genetic diversity and population structure of eight sheep breeds in Turkey and nearby countries. Moderate genetic diversity was observed, with the Sakiz (SKZ) exhibiting the highest diversity based on heterozygosity and allelic richness (AR) values. Genetic distances revealed differentiation between the populations, with the most significant divergence between the Cyprus Fat Tail (CFT) and SKZ breeds. PCA demonstrated SKZ and Chios (CHI) clustering together, indicating genetic similarity. Karakas (KRS), Norduz (NDZ), Afshari (AFS), Moghani (MOG) and others showed overlap, reflecting genetic relationships. Ancestry analysis found that KRS was predominantly inherited from the second ancestral population, while SKZ and NDZ were primarily derived from the first and second ancestral lineages. This illustrated the populations’ diverse origins. Most genetic variation (96.84%) was within, not between, populations. The phi-statistic (PhiPT) indicated moderate differentiation overall. Phylogenetic analysis further demonstrated the genetic distinctiveness of the SKZ breed. ROH and FROH analyses showed that SKZ exhibited the highest homozygosity and inbreeding, while KRS displayed the lowest. This study elucidates these breeds’ genetic diversity, structure and relationships. Key findings include moderate diversity, evidence of differentiation between breeds, diverse ancestral origins and distinct ROH patterns. This provides insights into the population’s genetic characteristics and conservation requirements.

The effects of using sheep tail fat and cooking time on carboxymethyl-lysine formation and some quality characteristics of heat-treated sucuk.

The study's aim was to determine the effect of using sheep tail fat (STF) on carboxymethyl-lysine (CML) content and other properties of heat-treated sucuk (HTS), a type of semi-dry fermented sausage. Three mixtures were prepared: 100% beef fat (BF), 50% BF + 50% STF, and 100% STF. After production (fermentation, heat treatment, and drying), the samples were cooked at 180°C for 0, 1, 3, and 5 min to determine the effect of cooking time on CML, thiobarbituric acid reactive substance (TBARS), total sulfhydryl, and carbonyl contents. The lowest pH value (5.50) was observed in the presence of STF. The most oleic acid (46.02%) was observed in the 100% STF group. The score of taste and general acceptability decreased with increasing STF. Using STF had no significant effect on TBARS, total sulfhydryl, carbonyl, or CML content. These parameters were affected by cooking time. The mean CML content increased from 55.77 to 72.90 μg/g after 5 min of cooking. CML correlated more strongly with TBARS than sulfhydryl or carbonyl.

Vine copula‐based scenario tree generation approaches for portfolio optimization

AbstractThis paper presents an efficient heuristic to generate multi‐stage scenario trees for portfolio selection problems. In the case of two or more risky assets, investors need to account for the complex multivariate dependence among different assets. The dependence patterns have shown not only asymmetric and fat tails but also time‐varying, and the upper and lower tails have different effect on portfolio management. In this paper, we design a new scenario generation method by combining the GARCH‐type model and vine copula model to properly reflect these complex dependence patterns in multiple assets in a flexible way. A multi‐stage scenario tree is generated sequentially from this model by simultaneously utilizing the simulation and clustering methods. The scenarios' nodal probabilities are determined by solving an improved moment matching model, whose objective is to maintain the central moments and lower tails of the original distribution. The resulting scenario trees are then tested on a multi‐stage portfolio selection model. The experimental results prove the efficiency and advantages of our proposed scenario generation method over other existing models or methods and the positive influence of moment matching on our method.

Network topology mapping of chemical compounds space

We define bipartite and monopartite relational networks of chemical elements and compounds using two different datasets of inorganic chemical and material compounds, as well as study their topology. We discover that the connectivity between elements and compounds is distributed exponentially for materials, and with a fat tail for chemicals. Compounds networks show similar distribution of degrees, and feature a highly-connected club due to oxygen . Chemical compounds networks appear more modular than material ones, while the communities detected reveal different dominant elements specific to the topology. We successfully reproduce the connectivity of the empirical chemicals and materials networks by using a family of fitness models, where the fitness values are derived from the abundances of the elements in the aggregate compound data. Our results pave the way towards a relational network-based understanding of the inherent complexity of the vast chemical knowledge atlas, and our methodology can be applied to other systems with the ingredient-composite structure.

Feed additive “Amylocin” and its infl uence on the metabolism and productivity of the wether hogs of Kalmyk fat-rumped breed

The purpose of the work was to scientifically and production substantiate the possibility of using the new generation probiotic feed additive “Amilocin” in feeding young sheep of the meat-fat type of productivity and to study the effect of its various dosages on the metabolism, meat and wool productivity of wether hogs of Kalmyk fat-rumped breed. Under the conditions of the arid zone of Southern Russia, the possibility of using the probiotic feed additive “Amylocin” in the rations of young sheep of Kalmyk fat-rumped breed was experimentally substantiated. The optimal dose of its introduction into the ration of wether hogs, the effect on the digestibility and use of nutrients in the ration, growth energy, meat and wool productivity, hematological parameters, as well as on the eff ectiveness of use in rations have been established. It was established as a result of the research that among the various dosages of the probiotic feed additive “Amylocin” studied in rations, the optimal and eff ective dose was 10 g/head/day. The inclusion of the probiotic “Amylocin” in the optimal amount in the ration of wether hogs ensured their more stable and intensive growth by 8,1 %, and contributed to better formation of meat and wool productivity in animals by 10,9 and 9,0 %, respectively. The use of the probiotic feed additive “Amylocin” in the ration of the wether hogs in an amount of 10 g/head/day improved the morphological composition of the carcasses; the amount of meat in them signifi cantly increased by 11,2 % and the weight of the fat tail by 15,2 %. The use of the probiotic feed additive “Amylocin” in the rations of wether hogs of Kalmyk fat-rumped breed in optimal dosages was economically beneficial, which helped reduce feed intakes by 15,2 % and generate additional profit in the amount of 355,9 rubles from each realized head.

Trace mineral concentration of forages in connection with sheep dietary requirements

This paper describes the trace and ultra-trace mineral concentration in different forages utilized by sheep (Kajli and Fat tail) in the rangelands of Chakwal district, Punjab, Pakistan. The concentrations of Se, Mo, Zn, Mn, Cu, and Co were assessed using spectrophotometric methods after the digestion of forage samples. The dominant forage species consumed by sheep were Buxus pappillosa, Prosopis juliflora, Ficus palmata, Acacia modesta, Trichodesma indica, Olea permiginea, Lantana camara, Justicia adhatoda, Morus nigra, and Ipomoea carnea. The overall mean concentration of Co (1.27±0.24 mg/Kg of DM), Zn (35.14±1.28 mg/Kg of DM), and Cu (28.06±1.29 mg/Kg of DM) in forages were higher than the requirements for lactating ewes, while the concentration of Se was within the normal range. Molybdenum (0.030±0.004 mg/Kg of DM) and Mn (29.69±1.61 mg/Kg of DM) concentrations were lower than dietary requirements for sheep. In different administrative divisions (tehsils) like Chakwal, Talagang, Choa Saidan Shah, and Kalar Kahar of Chakwal district, the trace minerals Zn, Mn, and Co, showed non-significant variation, whereas Se, Mo, and Cu showed substantial variation. In conclusion, rangeland forages contained a sufficient concentration of most trace minerals (Co, Cu, Se, Zn) to meet the requirements of grazing sheep in the study district. However, Mn and Mo supplementation seems to be essential to maintain the optimal production capabilities of sheep in this area.

Explaining the Stylized Facts of Foreign Exchange Markets with a Simple Agent-based Version of Paul de Grauwe’s Chaotic Exchange Rate Model

AbstractWe propose a simple agent-based version of Paul de Grauwe’s chaotic exchange rate model. In particular, we assume that each speculator follows his own technical and fundamental trading rule. Moreover, a speculator’s choice between these two trading philosophies depends on his individual assessment of current market circumstances. Our agent-based model setup is able to explain a number of important stylized facts of foreign exchange markets, including bubbles and crashes, excess volatility, fat-tailed return distributions, serially uncorrelated returns and volatility clustering. A stability and bifurcation analysis of its deterministic skeleton provides us with useful insights that foster our understanding of exchange rate dynamics.

Blockchain ETFs and the cryptocurrency and Nasdaq markets: Multifractal and asymmetric cross-correlations

Blockchain exchange-traded funds (ETFs) are nascent products in the financial industry. A limited literature focuses on the multifractal analysis of some conventional ETFs, but the multifractal behaviour of the blockchain ETF market has not been studied. In this paper, we investigate the multifractal and asymmetric cross-correlation features between blockchain ETFs and the cryptocurrency and Nasdaq markets. Multifractality exists in the cross-correlations between blockchain ETFs and the cryptocurrency and Nasdaq markets. There is a higher persistence in the cross-correlation behaviours between blockchain ETFs and cryptocurrencies in the uptrend, whereas the persistence between blockchain ETFs and Nasdaq is more pronounced in the downtrend. On one hand, this suggests that large fluctuations in the cryptocurrency markets lead to large fluctuations in blockchain ETF markets. On the other hand, large fluctuations in the Nasdaq index lead to small fluctuations in blockchain ETF markets. These results reflect stronger ties between blockchain ETFs and cryptocurrencies compared to blockchain ETFs and the Nasdaq index. Such heterogeneous behaviour in the cross-correlation structure provides insights for short-term investment, hedging strategies, and market efficiency. Further analysis shows that long-range cross-correlation and fat-tail distributions are sources of multifractality.

ASYMMETRIC GARCH-TYPE AND HALF-LIFE VOLATILITY MODELLING IN EXCHANGE RATES OF EURASIAN ECONOMIC UNION MEMBERS

The variability in the price of a financial asset is called volatility and is often measured with a standard deviation. Empirical studies have shown that many financial asset returns exhibit fat tails (leptokurtosis) and are often characterized by volatility clustering and asymmetry. The aim of this study is to determine the asymmetric GARCH-type modeling of the exchange rates of Belarus, Armenia, Kazakhstan, Kyrgyzstan, and Russia, which constitute the Eurasian Economic Union as of January 1, 2015, as well as to determine the return time to the mean after the shocks. The return series obtained over the daily closing prices of the exchange rates of the countries in question between December 31, 2018 and June 30, 2023 were analyzed using the EGARCH method and the return to mean were calculated.

Modelling the industrial production of electric and gas utilities through the CIR3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$CIR^3$$\\end{document} model

This work aims to extend previous research on how a trifactorial stochastic model, which we call CIR3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$CIR^3$$\\end{document}, can be turned into a forecasting tool for energy time series. In particular, in this work, we intend to predict changes in the industrial production of electric and gas utilities. The model accounts for several stylized facts such as the mean reversion of both the process and its volatility to a short-run mean, non-normality, autocorrelation, cluster volatility and fat tails. In addition to that, we provide two theoretical results which are of particular importance in modelling and simulations. The first is the proof of existence and uniqueness of the solution to the SDEs system that describes the model. The second theoretical result is to convert, by the means of Lamperti transformations, the correlated system into an uncorrelated one. The forecasting performance is tested against an ARIMA-GARCH and a nonlinear regression model (NRM).

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.