Thick Tails Research Articles

Application of Asymmetric-GARCH Type Models to The Kenyan Exchange Rates

Modelling and forecasting the volatility of a financial time series has become essential in many economic and financial applications like portfolio optimization and risk management. The symmetric-GARCH type models can capture volatility and leptokurtosis. However, the models fail to capture leverage effects, volatility clustering, and the thick tail property of high-frequency financial time series. The main objective of this study was to apply the asymmetric-GARCH type models to Kenyan exchange to overcome the shortcomings of symmetric-GARCH type models. The study compared the asymmetric Conditional Heteroskedasticity class of models: EGARCH, TGARCH, APARCH, GJR-GARCH, and IGARCH. Secondary data on the exchange rate from January 1993 to June 2021 were obtained from the Central Bank of Kenya website. The best fit model is determined based on parsimony of the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Log-Likelihood criterion, and minimisation of prediction production errors (Mean error [ME] and Root Mean Absolute error [RMAE]). The optimal variance equation for the exchange rates data was APARCH (1,1) - ARMA (3,0) model with a skewed normal distribution (AIC = -4.6871, BIC = -4.5860). Volatility clustering was present in exchange rate data with evidence of the leverage effect. Estimated Kenya’s exchange rate volatility narrows over time, indicating sustained exchange rate stability.

Instrumented column testing on long-term consolidation and desiccation behaviour of coal tailings under natural weather conditions

AbstractThe sedimentation, consolidation and desiccation behaviour of sub-aerially deposited tailings in tailings storage facilities, despite occurring simultaneously and being essential to maximise tailings dry density and dewatering efficiency, are usually analysed in laboratories using distinctive testing equipment, which is unable to reveal their interactions. A large instrumented column was constructed to test the three processes of tailings in a single apparatus, capable of monitoring the changes in the hydrological parameters of coal tailings with depth and surface settlement under natural weather conditions. The column was initially filled with coal tailings slurry and exposed to natural weather for two years, during which five wetting–drying periods were identified. The monitored results indicate that exposing the slurry tailings for one month would lead to the formation of an unsaturated tailings layer with a thickness of 150 mm, likely representing the optimised tailings deposition cycle and thickness, respectively, under the given tailings characteristics and semi-arid climates. Settlement mainly occurred after major rainfall events due to the collapse of cracks and cavities formed during the preceding desiccation. The maximum thickness of the unsaturated tailings increased over the first four periods as the predominant desiccation and settlement strengthened the evaporative capillary forces, despite it decreasing greatly in the last period due to insufficient desiccation. An empirical model was proposed to consecutively estimate the surface moisture content of deformable tailings and validated by achieving a good agreement in the water mass estimated by two methods during wetting–drying cycles.

Likelihood Based Inference and Bias Reduction in the Modified Skew-t-Normal Distribution

In this paper, likelihood-based inference and bias correction based on Firth’s approach are developed in the modified skew-t-normal (MStN) distribution. The latter model exhibits a greater flexibility than the modified skew-normal (MSN) distribution since it is able to model heavily skewed data and thick tails. In addition, the tails are controlled by the shape parameter and the degrees of freedom. We provide the density of this new distribution and present some of its more important properties including a general expression for the moments. The Fisher’s information matrix together with the observed matrix associated with the log-likelihood are also given. Furthermore, the non-singularity of the Fisher’s information matrix for the MStN model is demonstrated when the shape parameter is zero. As the MStN model presents an inferential problem in the shape parameter, Firth’s method for bias reduction was applied for the scalar case and for the location and scale case.

Financial time series classification method based on low‐frequency approximate representation

AbstractAiming at the mode mixing problems of high frequency information caused by fluctuation agglomeration and pointed peak thick tail of financial time series, a time series classification method based on low frequency approximate representation is proposed. The steps are as follows. Firstly, complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) was used to decompose the time series into a series of modal components and residual terms, and the permutation entropy of the modal components and residual terms was calculated. And the permutation entropy was clustered into two categories by Fisher's optimal segmentation method. Then, according to the clustering results of permutation entropy, the corresponding modal components and residual terms were integrated into high frequency information and low frequency information, so as to realize the adaptive extraction of low frequency information. Secondly, distance matrices were obtained by Euclidean distance (ED) or dynamic time warping (DTW) for low frequency information, and then the nearest neighbor 1‐NN algorithm was used to classify time series.

Phenotypic Characterization of Indigenous Sheep Breeds in Saudi Arabia

Saudi’s farm animal genetic resources have a particular role to play in managing the rural environment and assisting in maintaining wild biological diversity. Our indigenous livestock breeds are of great economic, social and cultural importance. The presence of livestock is a very positive feature for many who live in, work in or visit the countryside and livestock farming is frequently a core activity on which whole communities depend. The Kingdom has a rich and diverse population of livestock breeds sheep, goats, poultry, horses & Camel most of it are at risk. The conservation and sustainable use of genetic resources for food and agriculture is a widely supported international objective contributing to efforts to eliminate global poverty and achieve world food security.
 
 The data of the present study were collected form Noemi, Najdi and Hari breeds raised in Najd (96, 108, and 90 animals, respectively) Qassim region. Eight body measurements were studied, Wither heights (WH), Rum heights (RH), Body length (BL), Head length (HL), Heart girth (HG), Muzzle diameter (MD), Cannon circumference (CC) and Cannon length (CL). Noemi is taking the second size breed of the sheep breeds in Saudi Arabia. Hari is the smallest breed of sheep breeds in Saudi Arabia and it is the main breed in Hejaz and Asir regions which belong to the sheep with coarse hair and thick tail strain. The results of the present study on these breeds showed that Najdi breed has the biggest sizes in all body measurements 10.9% and 11.4% bigger than Noemi and Hari, Approximate respectively. By the other way in comparing Noemi’s breed with Hari breed, Noemi having the biggest sizes (10.5% Approximate) in all body measurements than Hari. Three categories of ages were presents in this study, eight, eighteen and forty-eight months. The first category eight months showed the smallest size in all body measurements by 11.2% in compare with eighteen months. No big differences were showed among eighteen and forty-eight months the different around 2% in favor of forty-eight category. 
 
 In addition, the effect of sex was significant, male always have biggest body measurements in compare with female. The results showed that male have around 10.9% more in all studied measurements more than female. All the fixed effect (effect of: Age, Breed and Sex) are significant on all body measurements traits expect Cannon circumference (CC) trait. The correlations coefficients among all studied traits were moderate to high and highly significant. The highest correlation coefficient was found between RH and WH traits (0.872), and the lowest one was found between CC and HG traits (0.214).

Macroeconomic downside risk and the effect of monetary policy

This study examines the dynamic effects of different types of monetary policy instruments on macroeconomic downside risks using SV-TVP-VAR Model. That is, we expand the predictive information set to fit the distribution of China's economic growth rate and then evaluate China's macroeconomic downside risks directly by measuring the probability of economic downturns. We find that extreme crises make the economic growth distributions show low peaks and thick tails, and increase macroeconomic downside risks. Quantitative monetary policy can effectively mitigate macroeconomic downside risks in the short term. Price-based monetary policy plays a role in curbing excessive economic prosperity and reducing macroeconomic downside risks in the medium term, and its regulatory effect is more sustainable.

Modelling exchange rate volatility under jump process and application analysis

<abstract> <p>Exchange rate is an important part of financial markets. Our analysis finds that the fluctuations of exchange rates have several obvious features, such as spikes, thick tails, fluctuation aggregations and asymmetry. Based on this, we build novel GARCH class model by introducing a jumping process to describe the dynamics of their fluctuations. Our empirical results show that the models with jump factors can better characterize the agglomeration and thick tail characteristics of these return fluctuations than the models without jump factors. In particular, the model with double exponential jumps can fully handle and capture the fluctuation characteristics of the returns. Our findings will be useful for individuals and governments to predict exchange rate fluctuations, provide reference for the effective management of exchange rate risk in China, and further improve the financial risk management mechanism.</p> </abstract>

Modeling RMB Exchange Rate Volatility – Application of GARCH Family Models

The exchange rate risk caused by the two-way fluctuation of the RMB exchange rate will bring many effects. The volatility of the foreign exchange market is the most common feature of the financial market. Therefore, the research on the volatility of the RMB exchange rate is of great significance in economic and financial aspects. Through statistical analysis of the RMB exchange rate data, an ARMA model was established to eliminate the auto-correlation of the sequence, and the GARCH family model was combined to fit the data. Comparing different distribution hypotheses, the EGARCH model under the GED distribution determined by the information criterion can match well the financial time series peak and thick tail characteristics. That the RMB exchange rate has agglomeration volatility and leverage effect is also shown, and provides relevant suggestions for preventing RMB exchange rate risks.

Covid-19’un Dünya Finans Piyasaları Üzerindeki Etkisini Belirlemeye Yönelik Bir Analiz

Bu çalışmada, tüm dünyayı etkisine alarak küresel bir salgın haline gelen koronavirüsün, Dünya’nın farklı bölgelerinde bulunan ABD, Almanya, Çin, Japonya, Mısır ve Türkiye’deki borsa endekslerinin volatilitesinde ve likiditelerinde herhangi bir değişiklik oluşturup oluşturmadığı tespit edilmeye çalışılmıştır. Bu çerçevede ABD’de DOW30 Endeksi, Almanya’da DAX Endeksi, Çin’de SSE Bileşik Şangay Endeksi, Japonya’da NİKKEİ 225 Endeksi, Mısır’da EGX30 Endeksi ve Türkiye’de BIST100 Endeksleri üzerinde koronavirüs salgınının etkileri araştırılmıştır. Çalışmanın analiz sonuçları ve yorumlar ilgili ülkelerle sınırlı olup çalışmanın kısıtını oluşturmuştur. Söz konusu ülkeler, gelişmiş ve gelişmekte olan ülkeler arasından ve coğrafi konum açısından içinde bulunduğu bölgeyi temsiliyet gücü yüksek finansal piyasalar olduğu kabul edilerek analize seçilmiştir. Araştırma kapsamında incelenen her ülkede Dünya Sağlık Örgütü (DSÖ)’nün açıkladığı ilk vakanın görüldüğü tarih baz alınmıştır. Her ülke için ilk vakanın görüldüğü tarihten 18 Kasım 2020 tarihine kadarki dönem için veri seti hazırlanmıştır. Pandemi öncesi ve sonrası farklılaşmayı belirleyebilmek için aynı sayıdaki veri kadar pandemi öncesi dönem veri seti de oluşturulmuştur. Böylece pandemi öncesi ve sonrası dönem için bir farklılaşmanın olup olmadığı tespit edilmeye çalışılmıştır. Endekslere ilişkin getiri ve likidite serileri koşullu varyans modellerinden GARCH(1,1) ile tahmin edilmiş ve COVID-19 sonrasında ilgili borsa endekslerinin volatilite ve likiditesinde değişmelerin olduğu gözlemlenmiştir. Araştırmaya konu ülke borsa endekslerin hepsinin getiri serilerinin klasik finansal zaman serilerinde gözlemlenen kalın kuyruk ve çarpıklık özellikleri tespit edilmiştir. Ayrıca volatilite kümelenmeleri gözlemlenmiştir.

A deductible comparison of cost per-loss, cost per-payment event, loss elimination ratio under exponentially and lognormally distributed severities

The maximum amount of losses retained by the insured under deductible policy modifications is usually set as part of the terms of the policy conditions. The objective of this study are to (i) estimate mean losses of an insured risk by means of the operational behavior of density function with deductible modifications and (ii) compare the mean severities under exponentially and log-normally distributed arbitrary policy in a cost per loss and cost per payment contingencies. The results show that despite the established fact in literature that log-normal severity distribution has a thicker tail than the exponential distribution, its cost per loss payment is correspondingly lower than the corresponding values of the exponential mean loss. Computational evidence over the trend of the change in the loss eliminated in the domain for which deductible has been defined revealed that the cost per loss amount is less than the cost per payment amount in the two models. The method can be used to estimate aggregate claims as the deductible level increases for every scheme holder and such that the estimated claims could be compared with the hypothetical observed claims which can be arrived at by applying the hypothetical deductible value to the background losses.

Monte-Carlo Stimulation for European Rainbow Call Options BASED on Meta and NEM’s Case Study

Recently, investors have paid great attention to the metaverse sector and the investing instruments for metaverse. Metaverse has become the most popular investment sector since 2021. Due to the rapid development of the industry, coupled with the social instability, it is critical to search for the appropriate investment. Previous literature proposed many advantages of the rainbow options and the expected growth of the metaverse industry. However, there is currently a lack of research on the combination of metaverse assets and the rainbow options. Based on this, this paper chooses the stocks of the metaverse enterprise META and the gold enterprise NEM as the safe-haven asset to construct a two-color European rainbow call options and chooses yahoo Finance's transaction data and excel and python as analysis software. The rainbow options return is given by Monte Carlo simulation method, and complete sensitivity analysis of the four parameters. At the end, the pros cons of rainbow options are compared. Besides three findings are obtained, including that options have cost advantages, could gain return from the market volatility by changing the portfolio, and have sharp peaks and thick tails in the distribution.

A study of stock returns based on ARMA-GARCH model: Taking the CSI 300 Index as an example

This paper selects the daily return data of CSI 300 index from January 2, 2014 to September 30, 2020 to study the characteristics of CSI 300 index return volatility. An ARMA(3,3) model was fitted to the daily log returns of the CSI 300 index using R software, and the ARCH effect was found to exist. The returns were then fitted with an ARMA(3,3)-GARCH(1,1) model, the model fitting effect was tested, and finally the short-term returns of the CSI 300 index were predicted. The results of the empirical analysis show that the CSI 300 index return series has characteristics such as non-normal distributivity, spikes and thick tails, and aggregation.

A GNSS Aided Calibration Method for DVL Error Based on the Optimal-REQUEST

The calibration of scale factor and installation errors plays an essential role to improve the accuracy of integrated navigation system of strap-down inertial navigation system (SINS) and Doppler velocity log (DVL). The DVL measurements will be affected by complex underwater environment, which may affect the calibration results. To solve the above problems, a Global Navigation Satellite System (GNSS) aided separate calibration method for DVL error is proposed in this article. First, an iterative method based on adaptive weight is proposed to calculate the scale factor. Second, a vector observation model is established and the method optimal-REQUEST is introduced to calculate the misalignment angles. In order to improve the estimation accuracy, a vector reconstruction method based on robust filtering is designed according to the measurement variation characteristics of parameter model to reduce the influence of thick tail noise. Finally, the simulation and Yangzi River experiments are conducted to evaluate the feasibility of the proposed DVL calibration method. Experimental results show that the proposed method has a good effect on the calibration of DVL error when DVL measurements are disturbed by noise. Compared to the combined calibration method based on state estimation, iterative method has no need to establish the system noise model, and the estimation result is relatively stable. The river results show that the proposed method is efficient and the positioning result has been greatly improved after calibration.

Morphological abnormalities in the Chilean Eagle ray Myliobatis chilensis (Myliobatiformes: Myliobatidae) off the Peruvian coast, Southeast Pacific

Records about morphological abnormalities in rays of the genus Myliobatis are scarce worldwide. In the present study, three specimens exhibiting different malformations were identified during the monitoring of the reproductive biology of the Chilean eagle ray Myliobatis chilensis, conducted from 2017 to 2018 in the fishing port of Salaverry (northern Peru). The identified specimens included: (i) a female with split pectoral fins, (ii) a male with an unfused-to-the-head pectoral fin, and (iii) a female with a short and thick tail. Here we report and discuss the implications and likely causes of these first three cases of morphological abnormalities in M. chilensis from the western Pacific.

Fourier변환을 갖는 Tempered Stable Lévy 프로세스(6모수 CGMY 모형)에 의한 옵션가격결정

In the real world, products in the stock market do not generally follow a normal distribution, but are known to follow a fat-tail distribution with high kurtosis and thick tails of skewness. Therefore, the purpose of this study is to analyze option pricing using a distribution in which random variables follow a stable and independent distribution and well represent the properties of the actual distribution. At this time, for the empirical analysis data, 252 daily KOSPI200 closing price indexes were used from November 15, 2019 to November 20, 2020. Call Options(Put options) were set as OTM(ITM) and ITM (OTM) and analyzed.
 In the research methodology of this paper, option pricing was performed by the CTS (or CGMY) model assuming a Tempered Stable Distribution that is capable of Furier transformation. In addition, the Black-Scholes model assuming a normal distribution and Fourier transformation, and the Fourier transformation were performed. The option pricing model using the Merton Diffusion Process and Variance-Gamma process was compared and analyzed.

Is gold still a safe haven for stock markets? New insights through the tail thickness of portfolio return distributions

This study examines the safe-haven property of gold during two deep financial crashes: the global financial crisis (GFC) and the coronavirus disease 2019 (COVID-19) pandemic. Applying extreme value theory, we analyze the tail behavior of the returns of 46 stock indices sorted by geographic location and level of market development and then investigate these portfolios with various gold allocations. We focus on changes in the tail thickness of the portfolio return distribution as an effect of an increased gold allocation. The COVID-19 crisis exhibited heavier lower tails of the stock indices than the GFC. During the GFC, gold enabled heavy Fréchet-type tails to change into thin Gumbel-type tails, whereas during the COVID-19 crash, the tails remained heavy, even after hedging. Thus, gold acted as a safe-haven asset, significantly decreasing extreme downside risk during the GFC, but the same result cannot be confirmed for the COVID-19 pandemic.

The effect of lipid composition on the dynamics of tau fibrils.

Knowledge of the interaction of the tau fibrils with the cell membrane is critical for the understanding of the underlying tauopathy pathogenesis. Lipid composition is found to affect the conformational ensemble of the tau fibrils. Using coarse-grained and all-atom molecular dynamics simulations we have shown the effect of the lipid composition in modulating the tau structure and dynamics. Molecular dynamics simulations show that tau proteins interact differentially with the zwitterionic compared to the charged lipid membranes. The negatively charged POPG lipid membranes increase the binding propensity of the tau fibrils. The addition of cholesterol is also found to modify the tau binding to the membrane. The binding of tau fibril leads to the concomitant loss of the β-sheet structures across the tau residues alongside the change in the membrane properties (like area per lipid, bilayer thickness, and order parameter of the lipid tails) over the pure bilayers.

A Study on the Hedging Function of Gold in the Light of Economic Policy Uncertainty.

This paper focuses on the empirical analysis of the closing price of gold, the SSE Index, and the China Economic Policy Uncertainty Index by means of a GARCH model to study the main characteristics of their movements. The series of gold closing price returns are analysed for linkage using the current mainstream VAR model, so as to analyse and compare the hedging function of gold. The article selects the closing price of gold, the SSE Index, and the China News-Based EPU from June 2005 to June 2019 as the sample series for the study. The background of the study and the theoretical knowledge of VAR and GARCH models are first introduced, and then, the GARCH family model and statistical analysis methods are used to derive the respective movements of the log returns of gold closing price, SSE index log returns, and China News-Based EPU log volatilities. The results show that the movements of the closing price of gold, the SSE Index, and the China News-Based EPU have the characteristics of financial assets in general, such as spikes and thick tails, agglomeration, and leverage effects. For the empirical study of the linkage between the three, this paper first considers only three variables, namely gold closing price, SSE index, and EPU. In order to investigate whether there is a co-integration relationship between them, a vector autoregressive model is established, followed by the corresponding impulse response analysis and variance decomposition. The analysis of the linkage between the closing price of gold, the SSE index, and the EPU concluded that changes in the EPU had a greater impact on the changes in the closing price of gold, while changes in the SSE index had a smaller impact on the changes in the closing price of gold. Finally, the conclusion of this article is some advice to investors on gold investment.

Research on Parameter Estimation and Prediction of Sports Financial Market Volatility Model

At present, the utility function of the financial system in the sports industry has not been brought into full play. Volatility reflects the uncertainty of asset price changes and plays an important role in asset pricing, portfolio, risk management, and asset allocation. Volatility has the characteristics of thick tail, leverage, market linkage, long memory, and aggregation. There are differences between different markets and countries. Therefore, according to the complex characteristics of volatility, this paper uses the feature-oriented research method to study several volatility prediction models, namely, random volatility model, realized volatility model, and multivariate volatility model. In order to promote capital formation and alleviate the financing constraints of sports finance, it provides reference value for reducing transaction costs, improving the quality and efficiency of sports industry, and realizing sustainable and rapid development.

Characterisation of Ditylenchus paraoncogenus n. sp. (Nematoda: Anguinidae), a new stem nematode parasitising tumble thistle

Summary During a survey, three populations of a new stem nematode were isolated from galls on the shoots of tumble thistle (Gundelia tournefortii) plants in Fars province, Iran, and identified. Ditylenchus paraoncogenus n. sp. is described based on morphometric and morphological characters. It is characterised by having long-sized females, 1252 (943-1628) μm long, narrow lateral fields with six incisures, rather developed stylet 9.9 (9.0-11.3) μm long with round knobs, usually elongate and offset from intestine basal pharyngeal bulb, oocytes in two rows in distal part of ovary, V = 83.3 (80.3-86.2), post-vulval uterine sac 68.1 (46.9-86.1)% of vulva to anus distance long, bursa covering 63.2 (33.3-74.4)% of tail length, spicules 24.7 (21.0-27.9) μm long with minute processes at the base of its manubrium and anteriorly pointed cuticle parts within the lamina, and thick conical tail, usually with a pointed terminus. In addition, the ITS and 18S rDNA sequences of 17 populations of D. destructor, D. dipsaci, D. medicaginis, D. myceliophagus, D. paraoncogenus n. sp., Ditylenchus sp. and Nothotylenchus geraerti plus one population of Anguinidae sp. were analysed. The results showed a close relationship between D. paraoncogenus n. sp. and the stem nematodes D. oncogenus, D. gigas, D. weischeri and D. dipsaci. Ditylenchus species were divided into two clades, one clade comprising stem nematodes and gall-forming nematodes of the family Anguinidae, and the other clade containing fungivorous species. Observations showed that the second-stage juvenile is the dormant stage of D. paraoncogenus n. sp. and can survive in anhydrobiotic condition for at least 4 years.