Symmetric Variants of Logistic Smooth Transition Autoregressive Models: Monte Carlo Evidences

The Smooth Transition Autoregressive (STAR) models are becoming popular in modeling economic and financial time series. The asymmetric type of the model is the Logistic STAR (LSTAR) model, which is limited in its applications as a result of its asymmetric property, which makes it suitable for modelling specific macroeconomic time series. This study was designed to develop the Absolute Error LSTAR (AELSTAR) and Quadratic LSTAR (QLSTAR) models for improving symmetry and performance in terms of model fitness. Modified Teräsvirta’s Procedure (TP) and Escribano and Jordá\u27s Procedure (EJP) were used to test for nonlinearity in the series. The performance of the AELSTAR and QLSTAR models showed that TP and EJP realized time series with improved symmetry as indicated by the lower relative frequencies than that realized with the existing LSTAR model. The AELSTAR model performed better than QLSTAR model at higher nonlinearity, and the selection of both models showed evidence of asymptotic property. The AELSTAR and QLSTAR models showed improved symmetry over the existing asymmetric LSTAR model

On the Exponentiated Weibull Distribution for Modeling Wind Speed in South Western Nigeria

One of the bases for assessment of wind energy potential for a specified region is the probability distribution of wind speed. Thus, appropriate and adequate specification of the probability distribution of wind speed becomes increasingly important. Several distributions have been proposed for describing wind distribution. Among the most popular distributions is the Weibull whose choice is due to its flexibility. An exponentiated Weibull distribution is proposed as an alternative to model wind speed data with a view to comparing it with the existing Weibull distribution. Results indicate that the proposed distribution outperforms the existing Weibull distribution for modeling wind speed data in terms of minimum Akaike information criterion (AIC) and likelihood function. Thus, the exponentiated Weibull can be used as an alternative distribution that adequately describe the wind speed and thereby provide better representation of the potentials of wind energy

On the Beta-Nakagami Distribution

This study is focused on combining Nakagami distribution and beta distribution with a view to obtaining a distribution that is better than each of them individually in terms of the estimate of their characteristics and parsimonious in their parameters using the logit of beta (the link function of the Beta generalized distribution by Jones (2004)). The resulting model, beta Nakagami distribution is better in terms of its flexibility and shape. The statistical properties of the proposed distribution such as moments, moment generating function, the asymptotic behavior among others were investigated. Our findings showed that beta Nakagami apart from being flexible, has better representation of data than Nakagami distribution.  It therefore describes situations better than the Nakagami distribution

Specifying Asymmetric STAR models with Linear and Nonlinear GARCH Innovations: Monte Carlo Approach

Economic and finance time series are typically asymmetric and are expected to be modeled using asymmetrical nonlinear time series models. Smooth Transition Autoregressive (STAR) models: Logistic (LSTAR) and Exponential (ESTAR) are known to be asymmetric and symmetric respectively. Under non-normal and heteroscedastic innovations, the residuals of these models are estimated using Generalized Autoregressive Conditionally Heteroscedastic (GARCH) models with variants which include linear and nonlinear forms. The small sample properties of STAR-GARCH variants are yet to be established but these properties are investigated using Monte Carlo (MC) simulation. An MC investigation was conducted to investigate the performance of selections of STAR-GARCH models by classical nonlinear selection approaches. The ARCH(1) and GARCH(1,1) models were the linear GARCH specifications while the Logistic Smooth Transition-ARCH (LST-ARCH(1,1)), Logistic Smooth Transition- GARCH (LST-GARCH(1,1)) and Asymmetric Nonlinear Smooth Transition-GARCH (ANST-GARCH(1,1)) models were the nonlinear GARCH specifications. The nonlinearity parameter in the variance equations and Autoregressive (AR) parameters were varied along with different sample sizes. With the assumption of normality, the results showed that the selection of LSTAR models were actually affected by the structure of the innovations and this improved as sample size increased. Misspecification tests showed that these models cannot be misrepresented in the real sense

On Structural Breaks and Nonstationary Fractional Intergration in Time Series

The growth of an economy is determined largely by the growth of its Gross Domestic Product (GDP) over time. However, GDP and some economic series are characterized by nonstationarity, structural breaks and outliers. Many attempts have been made to analyze these economic series assuming unit root process even in the presence of changes in the mean level without considering possible fractional integration. This paper aims at examining the structural breaks and nonstationarity in the GDP series of some selected African countries with a view to determining the influence of structural breaks on the level of stationarity of these series. These series are found to be nonstationary with some evidence of long memory. They were found to experience one or more breaks over the years and this may be due to instability in the government and economic policies in the selected African countries. The measure of relative efficiency shows that autoregressive fractional integrated moving average (ARFIMA) models is better than the corresponding autoregressive integrated moving average (ARIMA) models for the series considered in this study. Keywords: fractional integration, gross domestic product, structural break

On the Impact of Inflation and Exchange Rate on Conditional Stock Market Volatility: A Re-Assessment

This paper studies the impact of inflation and exchange rate on conditional stock market volatility. Sentana’s QGARCH model is generalized to include the asymmetries in inflation and exchange rate that are not allowed in linear GARCH (p, q) model of Bollerslev (1986). Nonlinear specifications of QGARCH model then show the significant relationship of inflation and exchange rate to conditional stock market volatility

GDP Per Capita in Africa before the Global Financial Crisis: Persistence, Mean Reversion and Long Memory Features

This paper examined the long memory features of GDP per capita data before the global financial crisis, using a sample of 26 African countries. The study employed fractional integration and tested the stability of the differencing parameter across the sample period for each country. The results indicated that most of the countries’ GDP series were I(1) or higher. Evidence of mean reversion was observed in 10 countries where the disturbances were autocorrelated. There was strong evidence against mean reversion in the remaining 16 countries. The results also indicated that the fractional differencing parameter was stable in 17 countries, while the presence of structural breaks was investigated in the remaining 9 countries

GDP Per Capita in Africa before the Global Financial Crisis: Persistence, Mean Reversion and Long Memory Features

This paper examined the long memory features of GDP per capita data before the global financial crisis, using a sample of 26 African countries. The study employed fractional integration and tested the stability of the differencing parameter across the sample period for each country. The results indicated that most of the countries’ GDP series were I(1) or higher. Evidence of mean reversion was observed in 10 countries where the disturbances were autocorrelated. There was strong evidence against mean reversion in the remaining 16 countries. The results also indicated that the fractional differencing parameter was stable in 17 countries, while the presence of structural breaks was investigated in the remaining 9 countries

Market efficiency of Baltic stock markets : a fractional integration approach

We investigate financial market efficiency in the time series of four daily Baltic stock market indices, namely: Baltic Benchmark Gross Index (OMXBBGI), all share index of Tallin-Lithuanian (OMXT), all share index of Riga (OMXR) and all share index of Vilnius (OMXV), based on historical data from 1 January, 2000 to 22 January 2016. We use fractional integration methods to test the hypothesis of market efficiency. Realizing that long-memory estimation could be spurious in the presence of structural breaks, we identify bull and bear market phases from each of the time series. Applying the fractional integration approach, we find that the random walk hypothesis of market efficiency is generally rejected in the overall, and at two bull and one bear sub-samples of the four Baltic stock indices. The volatility at the bear markets of these stocks persists more than the volatility at the bull markets. Our results therefore provide evidence for weak form of market efficiency in the Baltic stock markets, with some exceptions. As a way of policy, the results are relevant to portfolio managers and policy makers in a number of ways.http://www.elsevier.com/locate/physa2019-12-01hj2018Economic

Carbapenem resistance expressed by Gram-negative bacilli isolated from a cohort of Libyan patients

Background and objectives: Carbapenem-resistant Enterobacteriaceae (CRE) and other Gram-negative bacteria are among the most common pathogens responsible for both community and hospital acquired infection. The global spread of cephalosporinases in Enterobacteriaceae has led to the increased use of carbapenems resulting in the emergence and rapid spread of CRE. This has become an alarming public health concern, yet the condition in Libya remains unclear. The aim of this study was to obtain a better understanding of CRE strains prevalent in Libyan patients by investigating their phenotypic characteristics and antibiograms. Methods: Gram-negative bacterial species were collected from Misrata Central Hospital, Misrata Cancer Centre and Privet Pathology Laboratories. Clinical samples and swabs were obtained from hospitalised and non-hospitalised patients and from mechanical ventilation and suction machines. Patients who had received antibiotic therapy for at least three days prior to the study were excluded. The identification and characterization of the isolated species were achieved using the growth characteristics on MacConkey and blood agar, spot tests and API 20E or API 20NE biochemical testing systems. Screening for carbapenem resistance was performed using the disk diffusion method with carbapenem 10 μg and cephalosporin 30 μg disks and minimum inhibitory concentrations (MIC) determined using the Sensititre Gram-negative Xtra plate format (GNX2F). All strains demonstrating resistance or reduced susceptibility to one of the four carbapenems were subjected to carbapenememase activity detection using the RAPIDEC CARBA NP test, Modified Hodge test and carbapenem inactivation methods. Results: A total of one hundred and forty isolates representing fourteen bacterial species were isolated from 140 non-duplicated specimens. Clinical specimens included urine samples (96/140, 68.57%), sputum (15/140, 10.71%), surgical wound swabs (18/140, 12.85%), foot swabs from diabetes mellitus (DM) patients (6/140, 4.29%), ear swabs (3/140, 2.14%) and wound swabs (2/140, 1.43%). Thirty-four (24.29%) isolates demonstrated resistance to at least one of the four carbapenems with Klebsiella pneumoniae representing 73.53% (25 isolates) of all carbapenem resistant species, followed by 8.82% for Pseudomonas aeruginosa (3 isolates), 5.88% for both Proteus mirabilis (2 isolates) and Escherichia coli (2 isolates) and 2.94% for both Citrobacter koseri (1 isolate) and Rahnella aquatilis (1 isolate). The other isolates were either susceptible or cephalosporinase producers. Conclusion: This study has revealed the high rate of carbapenem resistance amongst Libyan patients and emphasizes the crucial need for accurate screening, identification and susceptibility testing to prevent further spread of nosocomial and community acquired resistance. This may be achieved through the establishment of antibiotic stewardship programmes along with firm infection control practices.National Research Foundation of South Africa; Libyan GovernmentWeb of Scienc