Fat Tails Research Articles

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.

Dynamic spillovers in higher moments and jumps across ETFs and economic and financial uncertainty factors in the context of successive shocks

Hedging is a particularly important tool in the Exchange Traded Fund (ETF) markets where market makers seek the best ways to mitigate the uncertainty of their exposures. This study relies on high frequency data to assess the spillover effects among ten US sector ETFs and various economic and financial uncertainty indexes based on realized volatility, realized higher moments as well as jumps under a relatively new spillover framework. Next, a time-varying parameter vector autoregression (TVP-VAR) model is used to examine the dynamic connectedness among ETFs and uncertainty factors volatilities while avoiding the sensitivity of spillover results to the choice of the rolling window. Our results showcase higher total connectedness between the different uncertainty indexes and ETFs, though with varying sensitivities. Notably, skewness and kurtosis can spread from one market to another, especially during times of market turbulence, reflecting the significant spillovers in higher-order moments. Interestingly, the market’s 30-day forward looking expectations of US stock market volatility (VIX) has stronger effect on the US sector equity ETFs than the expected 30-day volatility of returns on oil and gold. This analysis emphasizes the implications and contributions of assessing the spillover in higher-order moments covering volatility, skewness, and kurtosis to portfolio hedging and financial risk management. Overall, the results are of considerable practical interest for economic and market agents who are keen to understand market integration and systemic risk propagation to infer asymmetric or fat tail risk related to extreme or downside/upside risks.

Scale-dependent power law properties in hashtag usage time series of Weibo

We analyze the time series of hashtag numbers of social media data. We observe that the usage distribution of hashtags is characterized by a fat-tailed distribution with a size-dependent power law exponent and we find that there is a clear dependency between the growth rate distributions of hashtags and size of hashtags usage. We propose a generalized random multiplicative process model with a theory that explains the size dependency of the fat-tailed distribution. Numerical simulations show that our model reproduces these size-dependent properties nicely. We expect that our model is useful for understanding the mechanism of fat-tailed distributions in various fields of science and technology.

Сравнительная оценка мясной продуктивности молодняка овец при различных способах откорма

Purpose. Comparative analysis of meat productivity of rams of the Edilbaev breed during their grazing and fattening. Materials and Мethods. Scientific and production experience was carried out in the peasant farm Abdulkhalikov M.A. (Svetloyarsky district, Volgograd region) on two groups of rams of Edilbaev breed. The total number of animals participating in the experiment is 40. The formation of experimental groups was carried out according to the principle of analogues according to the methodology of A.I. Ovsyannikov (1976). The duration of the main experimental period was 120 days. The dynamics of live weight of rams was determined by measuring this indicator in each animal in the morning, before feeding, at the age of 4, 6 and 8 months. The rams were slaughtered (3 heads from each group) when the animals reached the age of 8 months. When studying meat productivity, we took into account: the weight of animals after fasting, the weight of the chilled carcass, the yield of the carcass, the weight and yield of internal fat, the fat tail weight and the yield of fat tail, slaughter weight, slaughter yield. All digital material obtained during the research was processed using statistical methods and Microsoft Excel software and determination Student-Fisher's reliability criterion of the difference. Results. Data on the dynamics of live weight at the age of 8 months indicate that the average live weight of fattening rams was 55.20 kg versus 50.80 kg for their peers in grazing. The difference in favor of fattening rams was 4.40 kg or 8.66% and was significant. Their superiority in absolute and average daily growth was 3.70 kg and 30.8 g, respectively. Over a period of 4 to 8 months, i.e. over 120 days of research, the average daily gain of fattening rams was 185.0 g versus 154.2 g for grazing rams of the same age. Fattening animals were superior to their peers in other slaughter indicators: in carcass weight - by 1.96 kg or 3.6% (P≤0.01), in internal fat weight - by 0.20 kg or 17.24 % (P≤0.01), in fat tail weight – by 0.60 kg or 18.30% (P≤0.05), by slaughter weight – by 3.93 kg or 14.41% (P≤0.01). At the same time, the slaughter yield for fattening rams was 58.10%, which is 1.90% higher than for grazing animals. According to morphological indicators, fattening rams are superior to their peers in fattening in terms of pulp weight by 2.08 kg or 12.17%. There was no significant difference in the mass of bone and connective tissue between animals of different groups. According to the meatiness index, grazing rams were inferior to their peers by 0.43 absolute values. Conclusion. Intensive fattening of young sheep of Edilbayev breed is a more effective method of fattening compared to grazing. The level of profitability of mutton production for fattening rams was 36.16% versus 13.47% for grazing rams of the same age. The difference in favor of fattening rams was 22.69%.

Measuring the degree of connection between currency futures: Empirical dive into higher moments

PurposeThe purpose of this study is to unfold the existing information channel in the higher moments of currency futures for different time horizons.Design/methodology/approachThe authors use a quasi-Bayesian local likelihood approach within a time-varying parameter vector autoregression (TVP-VAR) framework and a dynamic connectedness measure to study the volatility, skewness and kurtosis of most traded currency futures.FindingsThe authors’ results suggest a time-varying presence of dynamic connectedness within higher moments of currency futures. Most spillovers pertain to shorter time horizons. The authors find that in net terms, CHF, EUR and JPY are the most important contributors to the system, while the authors emphasize that the role of being a transmitter or a receiver varies for pairwise interactions and time windows.Originality/valueTo the best of the authors’ knowledge, this is the first study that looks upon the connectivity vis-á-vis uncertainty, asymmetry and fat tails in currency futures within a dynamic Bayesian paradigm. The authors extend the current literature by proposing new insights into asset distributions.

Methods for quantifying rain-splash dispersal of Neonectria ditissima conidia in apple canopies

Many microorganisms can be dispersed by rain-splash, whereby spores become suspended in water and are spread via droplets. The resulting dispersal gradient is dependent on several factors including rainfall intensity, the nature of the plant canopy and its effects on splash, deposition, redistribution (secondary splash) and filtering. Gradients of spore dispersal with distance are important for understanding epidemics, and the primary dispersal gradient can shape an epidemic for several pathogen generations. However, microorganisms are difficult to trap, identify and enumerate efficiently. This makes it difficult to study the spread and dispersal of pathogens to aid in biosecurity responses and management of epidemics. We used macroconidia of Neonectria ditissima, the causal organism of apple canker, to explore patterns of rain-splash dispersal in tree canopies. We investigated the use of a fluorescent tracer dye, PTSA (1,3,6,8-pyrenetetrasulfonic acid), as a surrogate to conidia capture during natural and artificial rain events, and lens tissue as ‘surrogate leaves’ to recapture tracer dye. Conidia and dye were released from central point sources 2.5 m above the ground and recaptured in passive rainwater traps or artificial ‘leaves’. Quantile regression and exponential models were used to explore variation and dispersal gradients derived for both conidia and dye, with and without tree canopy and with natural or artificial precipitation. Estimated dispersal gradients were steeper with a flatter tail when no tree canopy was present, whereas presence of tree canopy resulted in more variation and shallower predicted dispersal gradients, with fatter tails, predicting potential dispersal to further distances from the source. The majority of conidia and dye were recaptured at less than 1 m from the source, but small concentrations of spores were detected up to 3 m and dye more than 6 m. High variation in natural conditions requires further investigation to fully quantify natural dispersal gradients. Nevertheless, these results show the merit of tracer dye, artificial leaves, and quantile regression as tools to estimate potential dispersal patterns of N. ditissima and other rain-splash dispersed microorganisms, considering rain-splash factors in real canopies and natural situations for predicting inoculum dispersal.

Mixtures of factor analysers with censored responses and external covariates: An application to educational data from Peru.

Analysing data from educational tests allows governments to make decisions for improving the quality of life of individuals in a society. One of the key responsibilities of statisticians is to develop models that provide decision-makers with pertinent information about the latent process that educational tests seek to represent. Mixtures of factor analysers (MtFA) have emerged as a powerful device for model-based clustering and classification of high-dimensional data containing one or several groups of observations with fatter tails or anomalous outliers. This paper considers an extension of MtFA for robust clustering of censored data, referred to as the MtFAC model, by incorporating external covariates. The enhanced flexibility of including covariates in MtFAC enables cluster-specific multivariate regression analysis of dependent variables with censored responses arising from upper and/or lower detection limits of experimental equipment. An alternating expectation conditional maximization (AECM) algorithm is developed for maximum likelihood estimation of the proposed model. Two simulation experiments are conducted to examine the effectiveness of the techniques presented. Furthermore, the proposed methodology is applied to Peruvian data from the 2007 Early Grade Reading Assessment, and the results obtained from the analysis provide new insights regarding the reading skills of Peruvian students.

Polymorphisms of PLIN1 and MOGAT1 genes and their association with feed efficiency in Hu sheep

Feed cost accounts for a high proportion of sheep production, and improving sheep's utilization of feed will reduce production costs and improve economic benefits. The purpose of this study was to investigate the expression characteristics of PLIN1 and MOGAT1 genes and the relationship between their polymorphisms and feed efficiency traits in Hu sheep, and to find molecular Genetic marker that can be used in breeding. The expression levels of PLIN1 and MOGAT1 genes in various tissues were determined using quantitative real-time PCR (qRT-PCR). The results showed that PLIN1 and MOGAT1 genes were widely expressed in heart, liver, spleen, lungs, kidneys, rumen, duodenum, muscle, lymph, and tail fat. The PLIN1 gene had the highest expression level in in the tail fat compared to the other nine tissues. The expression levels of MOGAT1 gene in liver, tail fat, lung and heart was significantly higher than in kidney, muscle and lymph. The expression level of MOGAT1 was lowest in muscle compared to the other tissues (heart, liver, spleen, lung, rumen and tail fat). We recorded the body weight (BW80 and BW180) and feed intake (FI) information of 985 male Hu sheep at 80 and 180 days of age, and calculated the daily average feed intake (ADFI), average daily gain (ADG), and feed conversion rate (FCR) from 80 to 180 days of age. Two intronic mutations, g.18517910 A > G and g.224856118 G > C, were identified in PLIN1 and MOGAT1 genes by PCR amplification and Sanger sequencing. MassARRAY ® SNP detection technology was used to genotype the DNA of 985 Hu sheep and analyze its association with feed efficiency traits. The results showed that the SNP g.18517910 A > G was significantly associated with BW80, BW180, FI, ADFI and FCR (P < 0.05), while SNP g.2248561118 G > C was significantly associated with FCR (P < 0.05). Meanwhile, significant differences were also observed in different combinations of genotypes (P < 0.05). Therefore, these two polymorphic loci can serve as candidate molecular markers for improving feed utilization efficiency in Hu sheep.

STATISTICAL ANALYSIS BY WAVELET LEADERS REVEALS DIFFERENCES IN MULTI-FRACTAL CHARACTERISTICS OF STOCK PRICE AND RETURN SERIES IN TURKISH HIGH FREQUENCY DATA

The price and return time series are two distinct features of any financial asset. Hence, examining the evolution of multiscale characteristics of price and returns sequential data in time domain would be helpful in gaining a better understanding of the dynamical evolution mechanism of the financial asset as a complex system. In fact, this is important to understand their respective dynamics and to design their appropriate predictive models. The main purpose of the current work is to investigate the multiscale fractals of price and return high frequency data in Turkish stock market. In this regard, the wavelet leaders computational method is applied to each high frequency data to reveal its multi-fractal behavior. In particular, the method is applied to a large set of Turkish stocks and statistical results are performed to check for (i) presence of multi-fractals in price and return series and (ii) differences between prices and returns in terms of multi-fractals. Our statistical results show strong evidence that high frequency price and return data exhibit multi-fractal dynamics. In addition, they show evidence of distinct fractal characteristics on different scales between price and return series. Furthermore, our statistical results show evidence of differences in local fluctuation characteristics of price and return time series. Therefore, differences in local characteristics are useful to build specific predictive models for each type of data for better modeling and prediction to generate profits. Besides, we found evidence that both long-range correlations and fat-tail distributions contribute to the multifractality in Turkish stocks. This finding can be attributed to the major role played by international investors in increasing the volatility of Turkish stocks.

Does the big boss of coins—Bitcoin—protect a portfolio of new-generation cryptos? Evidence from memecoins, stablecoins, NFTs and DeFi

PurposeThe purpose of this research is to primarily understand how crypto traders can use the Bitcoin as a hedge or safe haven asset to reduce their losses from crypto trading. The study also aims to provide insights to crypto investors (portfolio managers) who wish to maintain a crypto portfolio for the medium term and can use the Bitcoin to minimize their losses. The findings of this research can also be used by policymakers and regulators for accommodating the Bitcoin as a medium of exchange, considering its safe haven nature.Design/methodology/approachThis study applies the cross-quantilogram (CQ) approach introduced by Han et al. (2016) to examine the safe-haven property of the Bitcoin against the other selected crypto assets. This method is robust for estimating bivariate volatility spillover between two markets given unusual distributions and extreme observations. The CQ method is capable of calculating the magnitude of the shock from one market to another under different quantiles. Additionally, this method is suitable for fat-tailed distributions. Finally, the method allows anticipating long lags to evaluate the strength of the relationship between two variables in terms of durations and directions simultaneously.FindingsThe Bitcoin acts as a weak safe haven asset for a majority of new crypto assets for the entire study period. These results hold even during greed and fear sentiments in the crypto market. The Bitcoin has the ability to protect crypto assets from sharp downturns in the crypto market and hence gives crypto traders some respite when trading in a highly volatile asset class.Originality/valueThis study is the first attempt to show how the Bitcoin can act as a true matriarch/patriarch for crypto assets and protect them during market turmoil. This study presents a clear and concise representation of this relationship via heatmaps constructed from CQ analysis, depicting the quantile dependence association between the Bitcoin and other crypto assets. The uniqueness of this study also lies in the fact that it assesses the protective properties of the Bitcoin not only for the entire sample period but also specifically during periods of greed and fear in the crypto market.

OPTIMAL HEDGE RATIO OF SUKUK AND ISLAMIC EQUITY: A NOVEL APPROACH

This research applies a novel model to compute a hedge ratio. Specifically, the model modifies volatility forecasts of an exponentially weighted moving average method to account for the fat-tailed distribution of returns. This simpler model aims to overcome the widely-known drawback of the complex GARCH models that a long daily return period is required to ensure the model’s convergence. The data are Islamic exchange-traded funds: SP Funds Dow Jones Global Sukuk ETF, Wahed FTSE USA Shariah ETF, and iShares MSCI EM Islamic UCITS ETF. Sukuk act as a diversifier over the turmoil period since they are positively correlated with Islamic equity and their volatility is less than that of Islamic equity. This work also implements widely-used methods such as Dynamic Equicorrelation-GARCH, GO-GARCH, asymmetric DCC-GARCH, naïve approach, and linear regression. Two forms of data splitting and a rolling-window analysis are carried out to reduce data mining bias. All models generate one-step ahead forecasts of hedge ratios. Applying wavelet-transformed returns and utility analysis incorporating third and fourth moments, the proposed models produce better performance than the competing models. The results remain the same irrespective of different hedging instruments (precious metals) and asset classes.

Ergodic properties of Brownian motion under stochastic resetting.

We study the ergodic properties of one-dimensional Brownian motion with resetting. Using generic classes of statistics of times between resets, we find respectively for thin- or fat-tailed distributions the normalized or non-normalized invariant density of this process. The former case corresponds to known results in the resetting literature and the latter to infinite ergodic theory. Two types of ergodic transitions are found in this system. The first is when the mean waiting time between resets diverges, when standard ergodic theory switches to infinite ergodic theory. The second is when the mean of the square root of time between resets diverges and the properties of the invariant density are drastically modified. We then find a fractional integral equationdescribing the density of particles. This finite time tool is particularly useful close to the ergodic transition where convergence to asymptotic limits is logarithmically slow. Our study implies rich ergodic behaviors for this nonequilibrium process which should hold far beyond the case of Brownian motion analyzed here.

Time-Varying Fractal Analysis of Exchange Rates

The foreign exchange (forex) market is a dynamic and complex financial arena where the exchange rates of various currency pairs fluctuate continuously. Among these currency pairs, EUR/TRY and USD/TRY hold significant economic relevance due to their roles in international trade and finance. In this study, we analyze the multifractality of hourly EUR/TRY and USD/TRY exchange rate data for the whole period, as well as its time-varying individual and cross correlations, spanning from May 31, 2018, to March 21, 2022. We employ multifractal detrended cross-correlation analysis (MF-DCCA) and multifractal detrended fluctuation analysis (MF-DFA) methodologies. The aim of studying multifractality in exchange rates is to comprehend and model the complex and intricate nature of price movements and dynamics of the EUR/TRY and USD/TRY exchange rates. In the analysis of the whole period, multifractality is detected in individual exchange rates and cross correlations. In the rolling window analysis, we demonstrated how multifractality and cross correlation multifractality change over time. Additionally, contributions of the sources of the multifractality are investigated in a time-varying framework. Multifractal nature of these exchange rates indicate that they exhibit complex and scale-dependent behaviors, which go beyond the traditional linear models. The existence of multifractality in EUR/TRY and USD/TRY exchange rates has significant implications for financial modeling, risk management, and trading strategies. It implies that standard linear models may not capture the full complexity of these markets, necessitating the development of more sophisticated models that account for multifractal properties.

A Comparison of Two Estrus Synchronization Protocols Utilizing Progesterone Supplement 24 Hours before CIDR-G Removal in Sheep

Two experiments investigated the effect of progesterone administration 24 h prior to intravaginal CIDR-G withdrawal using two protocols in two geographical locations and different breeds of sheep. Ewes in both experiments were administered with intravaginal CIDR-G either for 8 days (Expt. 1, n=36 thin tail mixed-breed ewes) in early April or for 12 days (Expt. 2, n=28 fat tail Awassi ewes) in late May. Half of the ewes in each experiment were assigned randomly one day before CIDR-G removal and given 25 mg P4 (P4-treated) and the second half were given saline solution and served as controls. Fertile rams were allowed with the ewes of both experiments immediately following CIDR-G removal (day0, 0h) and estrus was monitored at 6-h intervals for 4 days. Blood samples were collected for analysis P4 and LH levels. Estrus responses differed between the two experiments. P4 profiles during the period of CIDR-G insertion behaved the same way among ewes of both experiments, but levels differed (P &lt; 0.05) on day 0 in response to P4 supplement. The preovulatory LH surge was greater among groups treated with P4 supplement than those that did not. In both experiments, the percentage of ewes exhibiting estrus was greater (P &lt; 0.05) and intervals to estrus were longer (P &lt; 0.05) in P4-treated than control ewes. In the 12-day protocol in Expt. 2, ewes treated with P4 supplement produced greater (P &lt; 0.05) incidence of estrus, longer (P &lt; 0.05) intervals to onset of estrus and LH surge and had higher (P &lt; 0.01) magnitude of LH surge and pregnancy rate than controls and those of the 8-day protocol. In conclusion, P4 supplement 24 h prior to CIDR-G removal in a 12-day protocol can be used successfully to improve reproductive performance of ewes.