Essays on international financial markets interdependence

This thesis consists of five chapters. Chapter one showcases the analysis of the three empirical studies presented in this thesis. Chapter two provides broad literature review. Chapter three investigates the transmission of information between developed and developing countries. In particular, foreign exchange market’s return and volatility spillovers channel. A fundamental question is whether the magnitude of return and volatility spillovers is bidirectional between developed and developing countries. In this chapter, I investigate the “static and dynamic” return and volatility spillovers transmission across developed and developing countries. Quoted against the U.S. dollar, I study twenty-three global currencies over 2005 – 2016. Focusing on the spillover index methodology, the generalised VAR framework is employed. The findings indicate no evidence of bidirectional return and volatility spillovers between developed and developing countries. However, a unidirectional volatility spillover from developed to developing countries is highlighted. Furthermore, the findings also document significant bidirectional volatility spillover within the European region (Eurozone and non-Eurozone currencies) with the British Pound (GBP) and the Euro (EUR) as the most significant transmitters of volatility. The findings reiterate the prominence of volatility spillover to financial regulators.Chapter four contributes to the out-of-sample’s stock returns forecasting problem and investigates both its econometric underpinnings and predictability. According to Welch and Goyal (2008) there is little or zero evidence of the effectiveness of both (in-sample and out-of-sample) models in predicting equity returns. Thus, using daily data, this chapter examines whether the U.S. S&P stock exchange follow a random walk process, which required by market efficiency. We use a model-comparison approach, which compares an ex-post forecasts from a naïve model against those obtained from numerous alternative models such as ARIMA models, random walk without drift and Simple exponential smoothing.Chapter five assesses the dynamic behaviour of credit and house prices in advanced modern economies over the last three decades. The analysis is based on the GMM panel VAR, and Fixed-effects estimated using annual data for the G7 countries over the period 1980-2017. Thus, the empirical analysis of this chapter attempts to offer some contribution to the contemporaneous issues affecting the macroeconomic performance by investigating the dynamic behaviour of credit, house prices, GDP, consumption, and loans to the private sector. The main finding here is the strong link between the dynamic behaviour of the aforementioned variables in advanced modern economies. Finally, chapter six concludes and discusses the research implications and future study

HLA-DRB1 shared epitope genotyping using the revised classification and its association with circulating autoantibodies, acute phase reactants, cytokines and clinical indices of disease activity in a cohort of South African rheumatoid arthritis patients

INTRODUCTION: The revised shared epitope (SE) concept in rheumatoid arthritis (RA) is based on the presence (S) or absence (X) of the SE RAA amino acid motif at positions 72 to 74 of the third hypervariable region of the various human leucocyte antigen (HLA)-DRB1 alleles. The purpose of this study was to investigate SE subtypes on the basis of the American College of Rheumatology 1987 revised criteria for the classification of RA in a cohort of South African RA patients (n = 143) and their association with clinical and circulating biomarkers of disease activity (autoantibodies, acute phase reactants and cytokines). METHODS: Genomic DNA was analysed using high-resolution recombinant sequence-specific oligonucleotide PCR typing of the HLA-DRB1 allele. Subtypes of the SE were classified according to the amino acids at positions 72 to 74 for the RAA sequence, and further sub-divided according to the amino acids at positions 70 and 71, which either contribute to (S2, S3P), or negate (S1, S3D) RA susceptibility. Disease activity was assessed on the basis of (1) Disease Activity Score in 28 joints using C-reactive protein (CRP), (2) rheumatoid factor (RF), (3) CRP and (4) serum amyloid A by nephelometry, anticyclic citrullinated peptide antibodies (aCCP) by an immunofluorometric procedure, and cytokines by multiplex bead array technology. RESULTS: Of the 143 RA patients, 81 (57%) were homozygous (SS) and 50 (35%) were heterozygous (SX) for the SE alleles with significant overexpression of S2 and S3P (respective odds ratios (ORs) 5.3 and 5.8; P < 0.0001), and 12 (8%) were classified as no SE allele (XX). Both the SS and SX groups showed a strong association with aCCP positivity (OR = 10.2 and P = 0.0010, OR = 9.2 and P = 0.0028, respectively) relative to the XX group. Clinical scores and concentrations of the other biomarkers of disease activity (RF, CRP and T helper cell type 1 (Th1), Th2, macrophage and fibroblast cytokines) were also generally higher in the SS group than in the SX and XX groups. CONCLUSIONS: RA susceptibility alleles investigated according to revised criteria for the classification of RA were significantly increased in South African RA patients and strongly associated with aCCP in particular as well as with circulating cytokines and disease severity.The Connective Tissue Diseases Research Fund, University of the Witwatersrandhttp://arthritis-research.com/content/13/5/R16

Artificial intelligence-driven intrusion detection in software-defined wireless sensor networks : towards secure IoT-enabled healthcare systems

Wireless Sensor Networks (WSNs) are increasingly deployed in Internet of Things (IoT) systems for applications such as smart transportation, telemedicine, smart health monitoring and fall detection systems for the elderly people. Given that huge amount of data, vital and critical information can be exchanged between the different parts of a WSN, good management and protection schemes are needed to ensure an efficient and secure operation of the WSN. To ensure an efficient management of WSNs, the Software-Defined Wireless Sensor Network (SDWSN) paradigm has been recently introduced in the literature. In the same vein, Intrusion Detection Systems, have been used in the literature to safeguard the security of SDWSN-based IoTs. In this paper, three popular Artificial Intelligence techniques (Decision Tree, Naïve Bayes, and Deep Artificial Neural Network) are trained to be deployed as anomaly detectors in IDSs. It is shown that an IDS using the Decision Tree-based anomaly detector yields the best performances metrics both in the binary classification and in the multinomial classification. Additionally, it was found that an IDS using the Naïve Bayes-based anomaly detector was only adapted for binary classification of intrusions in low memory capacity SDWSN-based IoT (e.g., wearable fitness tracker). Moreover, new state-of-the-art accuracy (binary classification) and F-scores (multinomial classification) were achieved by introducing an end-to-end feature engineering scheme aimed at obtaining 118 features from the 41 features of the Network Security Laboratory-Knowledge Discovery in Databases (NSL-KDD) dataset. The state-of-the-art accuracy was pushed to 0.999777 using the Decision Tree-based anomaly detector. Finally, it was found that the Deep Artificial Neural Network should be expected to become the next default anomaly detector in the light of its current performance metrics and the increasing abundance of training data.This research was supported by the Council for Scientific and Industrial Research, Pretoria, South Africa, through the Smart Networks collaboration initiative and IoT-Factory Program (Funded by the Department of Science and Innovation (DSI), South Africa).The Council for Scientific and Industrial Research, Pretoria, South Africa, through the Smart Networks collaboration initiative and IoT-Factory Program (Funded by the Department of Science and Innovation (DSI), South Africa).https://www.mdpi.com/journal/ijerphElectrical, Electronic and Computer Engineerin

Case-mix and the use of control charts in monitoring mortality rates after coronary artery bypass

BACKGROUND: There is debate about the role of crude mortality rates and case-mix adjusted mortality rates in monitoring the outcomes of treatment. In the context of quality improvement a key purpose of monitoring is to identify special cause variation as this type of variation should be investigated to identify possible causes. This paper investigates agreement between the identification of special cause variation in risk adjusted and observed hospital specific mortality rates after coronary artery bypass grafting in New York hospitals. METHODS: Coronary artery bypass grafting mortality rates between 1994 and 2003 were obtained from the New York State Department of Health's cardiovascular reports for 41 hospitals. Cross-sectional control charts of crude (observed) and risk adjusted mortality rates were produced for each year. Special cause variation was defined as a data point beyond the 99.9% probability limits: hospitals showing special cause variation were identified for each year. Longitudinal control charts of crude (observed) and risk adjusted mortality rates were produced for each hospital with data for all ten years (n = 27). Special cause variation was defined as a data point beyond 99.9% probability limits, two out of three consecutive data points beyond 95% probability limits (two standard deviations from the mean) or a run of five consecutive points on one side of the mean. Years showing special cause variation in mortality were identified for each hospital. Cohen's Kappa was calculated for agreement between special causes identified in crude and risk-adjusted control charts. RESULTS: In cross sectional analysis the Cohen's Kappa was 0.54 (95% confidence interval: 0.28 to 0.78), indicating moderate agreement between the crude and risk-adjusted control charts with sensitivity 0.4 (95% confidence interval 0.17–0.69) and specificity 0.98 (95% confidence interval: 0.95–0.99). In longitudinal analysis, the Cohen's Kappa was 0.61 (95% confidence interval: 0.39 to 0.83) indicating good agreement between the tests with sensitivity 0.63 (95% confidence interval: 0.39–0.82) and specificity 0.98 (95% confidence interval: 0.96 to 0.99). CONCLUSION: There is moderate-good agreement between signals of special cause variation between observed and risk-adjusted mortality. Analysis of observed hospital specific CABG mortality over time and with other hospitals appears to be useful in identifying special causes of variation. Case-mix adjustment may not be essential for longitudinal monitoring of outcomes using control charts

Eliminating Malaria Vectors.

Malaria vectors which predominantly feed indoors upon humans have been locally eliminated from several settings with insecticide treated nets (ITNs), indoor residual spraying or larval source management. Recent dramatic declines of An. gambiae in east Africa with imperfect ITN coverage suggest mosquito populations can rapidly collapse when forced below realistically achievable, non-zero thresholds of density and supporting resource availability. Here we explain why insecticide-based mosquito elimination strategies are feasible, desirable and can be extended to a wider variety of species by expanding the vector control arsenal to cover a broader spectrum of the resources they need to survive. The greatest advantage of eliminating mosquitoes, rather than merely controlling them, is that this precludes local selection for behavioural or physiological resistance traits. The greatest challenges are therefore to achieve high biological coverage of targeted resources rapidly enough to prevent local emergence of resistance and to then continually exclude, monitor for and respond to re-invasion from external populations

Characterization of volatile compounds of Daucus crinitus Desf. Headspace Solid Phase Microextraction as alternative technique to Hydrodistillation

<p>Abstract</p> <p>Background</p> <p>Traditionally, the essential oil of aromatic herbs is obtained using hydrodistillation (HD). Because the emitted volatile fraction plays a fundamental role in a plant's life, various novel techniques have been developed for its extraction from plants. Among these, headspace solid phase microextraction (HS-SPME) can be used to obtain a rapid fingerprint of a plant's headspace. <it>Daucus crinitus </it>Desf. is a wild plant that grows along the west coast of Algeria. Only a single study has dealt with the chemical composition of the aerial part oils of Algerian <it>D. crinitus</it>, in which isochavicol isobutyrate (39.0%), octyl acetate (12.3%), and β-caryophyllene (5.4%) were identified. Using GC-RI and GC-MS analysis, the essential oils and the volatiles extracted from separated organs of <it>D. crinitus </it>Desf. were studied using HS-SPME.</p> <p>Results</p> <p>GC-RI and GC-MS analysis identified 72 and 79 components in oils extracted using HD and in the volatile fractions extracted using SPME, respectively. Two types of essential oils were produced by the plant: the root oils had aliphatic compounds as the main component (87.0%-90.1%), and the aerial part oils had phenylpropanoids as the main component (43.1%-88.6%). HS-SPME analysis showed a more precise distribution of compounds in the organs studied: oxygenated aliphatic compounds were well represented in the roots (44.3%-84.0%), hydrocarbon aliphatic compounds were in the leaves and stems (22.2%-87.9%), and phenylpropanoids were in the flowers and umbels (47.9%-64.2%). Moreover, HS-SPME allowed the occurrence of isochavicol (29.6 - 34.7%) as main component in <it>D. crinitus </it>leaves, but it was not detected in the oils, probably because of its solubility in water.</p> <p>Conclusions</p> <p>This study demonstrates that HD and HS-SPME modes could be complimentary extraction techniques in order to obtain the complete characterization of plant volatiles.</p

The Galabat-Metema cross-border onchocerciasis focus: The first coordinated interruption of onchocerciasis transmission in Africa.

BACKGROUND: Onchocerciasis transmission across international borders is not uncommon, yet a coordinated cross border stops mass drug administration (MDA) decision has not been documented. METHODS/PRINCIPLE FINDINGS: The Galabat-Metema focus involves neighboring districts on the border between Sudan and Ethiopia. Mass drug administration (MDA) was provided once and subsequently twice per year in this focus, with twice-per-year beginning in Ethiopia's Metema subfocus in 2016 and in the Sudan's Galabat subfocus in 2008. Ov16 ELISA-based serosurveys were conducted in 6072 children under 10 years of age in the Metema subfocus in 2014, and 3931 in the Galabat in 2015. Between 2014 and 2016, a total of 27,583 vector Simulium damnosum flies from Metema and 9,148 flies from Galabat were tested by pool screen PCR for Onchocerca volvulus O-150 DNA. Only 8 children were Ov16 seropositive (all in the Metema subfocus); all were negative by skin snip PCR. The upper limit of the 95% confidence interval (UCL) for Ov16 seropositive was <0.1% for the overall focus and 0.14 positive fly heads per 2000 (UCL = 0.39/2000). However, an entomological 'hotspot' was detected on the Wudi Gemzu river in Metema district. The hotspot was confirmed when 4 more positive fly pools were found on repeat testing in 2017 (1.04 L3/2000 flies (UCL = 2.26/2000). Information exchange between the two countries led to stopping MDA in a coordinated fashion in 2018, with the exception of the hotspot at Wudi Gemzu, where MDA with ivermectin was increased to every three months to hasten interruption of transmission. CONCLUSION: Coordinated stop MDA decisions were made by Sudan and Ethiopia based on data satisfying the World Health Organization's criteria for interruption of onchocerciasis transmission. Definitions of entomological 'hotspots' and buffer zones around the focus are proposed