Incorporating stochastic volatility and long memory into geometric Brownian motion model to forecast performance of Standard and Poor's 500 index

It is known in the financial world that the index price reveals the performance of economic progress and financial stability. Therefore, the future direction of index prices is a priority of investors. This empirical study investigated the effect of incorporating memory and stochastic volatility into geometric Brownian motion (GBM) by forecasting the future index price of S&P 500. To conduct this investigation, a comparison study was implemented between twelve models; six models without memory (GBM) and six models with memory (GFBM) under two different assumptions of volatility; constant, which were computed by three methods, and stochastic volatility, obeying three deterministic functions. The results showed that the best performance model was for GFBM under a stochastic volatility assumption using the identity deterministic function $\sigma \left({Y}_{t}\right) = {Y}_{t}$, according to the smallest values of mean square error (MSE) and mean average percentage error (MAPE). This revealed the direct positive effect of incorporating memory and stochastic volatility into GBM to forecast index prices, and thus can be applied in a real financial environment. Furthermore, the findings showed invalidity of the models with exponential deterministic function $\sigma \left({Y}_{t}\right) = {e}^{{Y}_{t}}$ in forecasting index prices according to huge values of MAPE and MSE

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

A first update on mapping the human genetic architecture of COVID-19

peer reviewe

Subordination and Superordination Properties for Certain Family of Analytic Functions Associated with Mittag–Leffler Function

We obtain new outcomes of analytic functions linked with operator Hα,βη,k(f) defined by Mittag–Leffler function. Moreover, new theorems of differential sandwich-type are obtained

A Family of Analytic and Bi-Univalent Functions Associated with Srivastava-Attiya Operator

In this paper, we investigate a new family of normalized analytic functions and bi-univalent functions associated with the Srivastava–Attiya operator. We use the Faber polynomial expansion to estimate the bounds for the general coefficients |an| of this family. The bounds values for the initial Taylor–Maclaurin coefficients of the functions in this family are also established

A Family of Analytic and Bi-Univalent Functions Associated with Srivastava-Attiya Operator

In this paper, we investigate a new family of normalized analytic functions and bi-univalent functions associated with the Srivastava–Attiya operator. We use the Faber polynomial expansion to estimate the bounds for the general coefficients |an| of this family. The bounds values for the initial Taylor–Maclaurin coefficients of the functions in this family are also established

Transient Analysis of Markovian Queueing System with Balking and Reneging Subject to Catastrophes and Server Failures

In this paper, we present an analysis of the transient and steady states of the infinite Markovian queueing system where both reneging and balking are defined and the system may be entered under catastrophes and server failures repair. Moreover, some other special cases are shown as special case of our new result

Empirical E-Bayesian estimation of hierarchical poisson and gamma model using scaled squared error loss function

The hierarchical models have not only a major concern with developing computational schemes but also assist in inferring the multi-parameter problems. The E-Bayesian is the expected Bayesian estimation that can be found by taking the integrals of Bayesian estimator using a hyper-prior with respect to the hyper-parameters. This study introduces the empirical E-Bayesian estimation that is coalesced with hierarchical modeling which prior to this has not been investigated. The scaled squared error loss function (SELF) has been used to estimate the parameter of Hierarchical Poisson-Gamma (HPG) model using empirical E-Bayesian estimation. The empirical E-Posterior risk is considered to be the evaluation standard. In addition, the consistency along with the asymptotic normality of the posterior distribution have been discussed. Furthermore, the empirical Bayes method is used to estimate the values of hyper-parameters via Maximum Likelihood (ML) method. The Monte Carlo simulation is executed to assess the precision of proposed estimators and a real-data application has been analyzed for illustration and comparison purposes

Quantum Correlation via Skew Information and Bell Function Beyond Entanglement in a Two-Qubit Heisenberg XYZ Model: Effect of the Phase Damping

In this paper, we analyze the dynamics of non-local correlations (NLCs) in an anisotropic two-qubit Heisenberg XYZ model under the effect of the phase damping. An analytical solution is obtained by applying a method based on the eigenstates and the eigenvalues of the Hamiltonian. It is observed that the generated NLCs are controlled by the Dzyaloshinskii–Moriya interaction, the purity indicator, the interaction with the environment, and the anisotropy. Furthermore, it is found that the quantum correlations, as well as the sudden death and sudden birth phenomena, depend on the considered physical parameters. In particular, the system presents a special correlation: the skew-information correlation. The log-negativity and the uncertainty-induced non-locality exhibit the sudden-change behavior. The purity of the initial states plays a crucial role on the generated nonlocal correlations. These correlations are sensitive to the DM interaction, anisotropy, and phase damping

Computational Framework of the SVIR Epidemic Model with a Non-Linear Saturation Incidence Rate

In this study, we developed an autonomous non-linear epidemic model for the transmission dynamics of susceptible, vaccinated, infected, and recovered individuals (SVIR model) with non-linear saturation incidence and vaccination rates. The non-linear saturation incidence rate significantly reduces the death ratio of infected individuals by increasing human immunity. We discuss a detailed explanation of the model equilibrium, its basic reproduction number R0, local stability, and global stability. The disease-free equilibrium is observed to be stable if R01, while the endemic equilibrium exists and the disease exists permanently in the population if R0>1. To approximate the solution of the model, the well-known Runge–Kutta (RK4) methodology is utilized. The implications of numerous parameters on the population dynamics of susceptible, vaccinated, infected, and recovered individuals are addressed. We discovered that increasing the value of the disease-included death rate ψ has a negative impact on those affected, while it has a positive impact on other populations. Furthermore, the value of interaction between vaccinated and infected λ2 has a decreasing impact on vulnerable and vaccinated people, while increasing in other populations. On the other hand, the model is solved using Euler and Euler-modified techniques, and the results are compared numerically and graphically. The quantitative computations demonstrate that the RK4 method provides very precise solutions compared to the other approaches. The results show that the suggested SVIR model that approximates the solution method is accurate and useful