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An in-silico pharmacophore-based molecular docking study to evaluate the inhibitory potentials of novel fungal triterpenoid Astrakurkurone analogues against a hypothetical mutated main protease of SARS-CoV-2 virus
Background: The main protease is an important structural protein of SARS-CoV-2, essential for its survivability inside a human host. Considering current vaccines' limitations and the absence of approved therapeutic targets, Mpro may be regarded as the potential candidate drug target. Novel fungal phytocompound Astrakurkurone may be studied as the potential Mpro inhibitor, considering its medicinal properties reported elsewhere. Methods: In silico molecular docking was performed with Astrakurkurone and its twenty pharmacophore-based analogues against the native Mpro protein. A hypothetical Mpro was also constructed with seven mutations and targeted by Astrakurkurone and its analogues. Furthermore, multiple parameters such as statistical analysis (Principal Component Analysis), pharmacophore alignment, and drug likeness evaluation were performed to understand the mechanism of protein-ligand molecular interaction. Finally, molecular dynamic simulation was done for the top-ranking ligands to validate the result. Result: We identified twenty Astrakurkurone analogues through pharmacophore screening methodology. Among these twenty compounds, two analogues namely, ZINC89341287 and ZINC12128321 showed the highest inhibitory potentials against native and our hypothetical mutant Mpro, respectively (?7.7 and ?7.3 kcal mol?1) when compared with the control drug Telaprevir (?5.9 and ?6.0 kcal mol?1). Finally, we observed that functional groups of ligands namely two aromatic and one acceptor groups were responsible for the residual interaction with the target proteins. The molecular dynamic simulation further revealed that these compounds could make a stable complex with their respective protein targets in the near-native physiological condition. Conclusion: To conclude, Astrakurkurone analogues ZINC89341287 and ZINC12128321 can be potential therapeutic agents against the highly infectious SARS-CoV-2 virus. 2022 Elsevier Ltd -
Evaluation of tea (Camellia sinensis L.) phytochemicals as multi-disease modulators, a multidimensional in silico strategy with the combinations of network pharmacology, pharmacophore analysis, statistics and molecular docking
Tea (Camellia sinensis L.) is considered as to be one of the most consumed beverages globally and a reservoir of phytochemicals with immense health benefits. Despite numerous advantages, tea compounds lack a robust multi-disease target study. In this work, we presented a unique in silico approach consisting of molecular docking, multivariate statistics, pharmacophore analysis, and network pharmacology approaches. Eight tea phytochemicals were identified through literature mining, namely gallic acid, catechin, epigallocatechin gallate, epicatechin, epicatechin gallate (ECG), quercetin, kaempferol, and ellagic acid, based on their richness in tea leaves. Further, exploration of databases revealed 30target proteins related to the pharmacological properties of tea compounds and multiple associated diseases. Molecular docking experiment with eight tea compounds and all 30proteins revealed that except gallic acid all other seven phytochemicals had potential inhibitory activities against these targets. The docking experiment was validated by comparing the binding affinities (Kcalmol?1) of the compounds with known drug molecules for the respective proteins. Further, with the aid of the application of statistical tools (principal component analysis and clustering), we identified two major clusters of phytochemicals based on their chemical properties and docking scores (Kcalmol?1). Pharmacophore analysis of these clusters revealed the functional descriptors of phytochemicals, related to the ligandprotein docking interactions. Tripartite network was constructed based on the docking scores, and it consisted of seven tea phytochemicals (gallic acid was excluded) targeting five proteins and ten associated diseases. Epicatechin gallate (ECG)-hepatocyte growth factor receptor (PDB id 1FYR) complex was found to be highest in docking performance (10kcalmol?1). Finally, molecular dynamic simulation showed that ECG-1FYR could make a stable complex in the near-native physiological condition. Graphical abstract: [Figure not available: see fulltext.]. 2022, The Author(s), under exclusive licence to Springer Nature Switzerland AG. -
Exploring the applications and security threats of Internet of Thingin the cloud computing paradigm: A comprehensive study on the cloud of things
The term Internet of Things (IoT) represents a vast interconnected network comprising ordinary objects enhanced with electronics like sensors, actuators, and wireless connectivity. These augmentations enable seamless communication and data sharing among devices. IoT constitutes an ecosystem of programs, systems, and technologies that operate across diverse communication services. In our rapidly evolving world, cutting-edge technologies are swiftly gaining prominence. IoT, in particular, strives to proliferate innovative applications, programs, and communication amalgamating the virtual and physical realms. The bedrock of this communication is the machine-to-machine communication paradigm. IoT encompasses a spectrum of technologies encompassing smart vehicles, efficient vehicle parking management systems, and roadway-embedded sensors, culminating in the vision of a smart city. Such integration has the potential to alleviate traffic congestion and curb energy consumption. The impact of IoT extends to power generation and business operations, promising transformative outcomes. Furthermore, the synergy between IoT and cloud computing plays a pivotal role in the wireless communication domain. This paper offers a comprehensive insight into IoT's functionalities and underscores the associated security threats. The study aims to equip academia with an enhanced understanding of diverse IoT applications, particularly their integration with cloud computing, referred to as the Cloud of Things.. 2023 John Wiley & Sons, Ltd. -
In silico study of some selective phytochemicals against a hypothetical SARS-CoV-2 spike RBD using molecular docking tools
Background: This world is currently witnessing a pandemic outbreak of COVID-19? caused by a positive-strand RNA virus SARS-CoV-2. Millions have succumbed globally to the disease, and the numbers are increasing day by day. The viral genome enters into the human host through interaction between the spike protein (S) and host angiotensin-converting enzyme-2 (ACE2) proteins. S is the common target for most recently rolled-out vaccines across regions. A recent surge in single/multiple mutations in S region is of great concern as it may escape vaccine induced immunity. So far, the treatment regime with repurposed drugs has not been too successful. Hypothesis: Natural compounds are capable of targeting mutated spike protein by binding to its active site and destabilizing the spike-host ACE2 interaction. Materials and methods: A hypothetical mutated spike protein was constructed by incorporating twelve different mutations from twelve geographical locations simultaneously into the receptor-binding domain (RBD) and docked with ACE2 and seven phytochemicals namely allicin, capsaicin, cinnamaldehyde, curcumin, gingerol, piperine and zingeberene. Molecular Dynamic (MD) simulation and Principal Component Analysis (PCA) were finally used for validation of the docking results. Result: The docking results showed that curcumin and piperine were most potent to bind ACE2, mutated spike, and mutated spike-ACE2 complex, thereby restricting viral entry. ADME analysis also proved their drug candidature. The docking complexes were found to be stable by MD simulation. Conclusion: This result provides a significant insight about the phytochemicals' role, namely curcumin and piperine, as the potential therapeutic entities against mutated spike protein of SARS-CoV-2. 2021 -
Beta carotene inhibiting HIV-1 reverse transcriptase, an in silico approach
Due to the outspread of various emerging diseases, research on the discovery of new drugs is being carried out extensively. Several phytochemicals with medicinal importance are now being used for this purpose due to its effectiveness and safety in comparison to the conventional synthetic ones. Computational docking is further being used for the fast and cost-effective screening. Reverse transcriptase is a key enzyme involved in the conversion of viral RNA sequence into complementary DNA (cDNA) sequence leading to various retroviral diseases like HIV/AIDS. Patchdock docking server was used in this study to perform in silico enzyme-inhibitor binding experiment between twenty phytocompounds and HIV-1 reverse transcriptase enzyme. Beta-carotene was found to have strongest binding potential in comparison to other phytochemicals. The results suggested that this compound can be used as therapeutics in the future as naturally occurring HIV-1 reverse transcriptase inhibitor. 2020 World Research Association. All rights reserved. -
In Silico Analysis of the Apoptotic and HPV Inhibitory Roles of Some Selected Phytochemicals Detected from the Rhizomes of Greater Cardamom
Occurrence of cervical cancer, caused due to persistent human papilloma virus (HPV) infection, is common in women of developing countries. As the conventional treatments are expensive and associated with severe side effects, there is a need to find safer alternatives, which is affordable and less toxic to the healthy human cells. Present study aimed to evaluate the anti-HPV and apoptotic potential of four compounds from the greater cardamom (Amomum subulatum Roxb. var. Golsey), namely rhein, phytosphingosine, n-hexadecenoic acid and coronarin E. Their anti-HPV and apoptotic potential were studied against viral E6, E7 and few anti-apoptotic proteins of host cell (BCL2, XIAP, LIVIN) by in silico docking technique. Phytochemicals from the plant extract were analysed and identified by LC/MS and GC/MS. Involvement of the target proteins in various biological pathways was determined through KEGG. Structural optimization of the three-dimensional structures of the ligands (four phytochemicals and control drug) was done by Avogadro1.1. Receptor protein models were built using ProMod3 and other advanced tools. Pharmacophore modelling of the selected phytochemicals was performed in ZINCPharmer. Swiss ADME studies were undertaken to determine drug likeness. The ligands and proteins were digitally docked in DockThor docking program. Protein flexibility-molecular dynamic simulation helped to study proteinligand stability in real time. Finally, the correlation of evaluated molecules was studied by the use of principal component analysis (PCA) based on the docking scores. All the ligands were found to possess apoptotic and anti-cancer activities and did not violate Lipinsky criteria. n-Hexadecanoic acid and its analogues showed maximum efficacy against the target proteins. All the proteinligand interactions were found to be stable. The uncommon phytochemicals identified from rhizomes of greater cardamom have anti-cancer, apoptotic and HPV inhibitory potentials as analysed by docking and other in silico studies, which can be utilized in drug development after proper experimental validation. 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
An Integrated and Optimized Fog Computing enabled Framework to minimize Time Complexity in Smart Grids
A distributed computing paradigm known as 'cloud computing'works as a connection between IoT devices and cloud data centres. The environment system model in this work is on basis of clouds and fog and includes smart grids, which we explore. Prior to understanding the use of fog computing in smart grids we discuss about various features of cloud computing and talk about how to manage the connection between fog and cloud computing. Along with the usual performance of low latency, low cost, and high intelligence, the distinctive characteristics and service scenarios are also explored. Based on the outcome of the simulation, it appears that our suggested PSO-SA algorithm outperforms other optimization algorithms. It recorded a least mean response time of 3.86 seconds only. While the model build up delay was 4.6 seconds, the model execution delay was also found to be only 4.9 seconds with PSO-SA method. The improved efficiency of the technique can be credited to the best aspects of particle swarm optimisation (PSO) and a modified inertia weight obtained by simulated annealing. 2023 IEEE. -
Prediction of Material Removal Rate and Surface Roughness in Hot Air Assisted Hybrid Machining on Soda-Lime-Silica Glass using Regression Analysis and Artificial Neural Network
Hybrid machining is a combination of conventional with the non-conventional process or two non-conventional processes. In the present work, an attempt has been made to combine hot air with a conventional cutting tool to form a novel Hot Air Assisted Hybrid Machining (HAAHM) for the machining of soda-lime-silica glass. The mathematical model for the Material Removal Rate (MRR) and Surface Roughness (Ra) using Regression Analysis (RA) and the Artificial Neural Network (ANN) models has been developed for the grooving process. The deviation of 8.24% and 7.70% were found in the prediction of MRR and Ra by regression analysis and the deviation of 1.89% and 1.70% for MRR and Ra using an artificial neural network model. The deviation between the predicted and the experimental results of both the models are found to be within the permissible limit. Higher predictive capabilities were observed in ANN model than the regression model. However, both models demonstrated good agreement with the MRR of soda-lime-silica glass by this hybrid machining process. 2020, Springer Nature B.V. -
Parametric optimization on hot air assisted hybrid machining of soda-lime glass using Taguchi based grey relational analysis
The present research underlines the development of a hybrid method for the machining of soda-lime glass known as the hot air assisted hybrid machining. It is a combination of conventional machining assisted with the jet of hot air. The influence of process variables such as feed of the cutting tool, flow of hot air, depth of cut, and the air temperature on the material removal rate (MRR) and surface roughness (Ra) applied to the grooving operation have been investigated. The Taguchi orthogonal array L27 was considered to reduce the number of experiments. The ANOVA was used to recognize the major influencing process parameters for the MRR and Ra. The results of ANOVA indicate that the air temperature is the most significant parameter for the objective of maximum MRR and minimum Ra with contributions ratios of 56.91% and 52.68% respectively for the grooving operation on soda-lime glass. The optimal machining parameters for the maximum MRR and minimum Ra were found to be A1B1C3D3 and A1B1C1D3 respectively. The multi-objective optimization was performed using the Taguchi based grey relational analysis (GRA). The optimal level of parameters based on GRA for maximum MRR and minimum Ra was found to be A1B1C3D3. In addition, the material removal process was explained with the help of SEM micrographs. 2021, Springer Nature Switzerland AG. -
Influence of heat treatment and reinforcements on tensile characteristics of aluminium aa 5083/silicon carbide/fly ash composites
The effect of reinforcements and thermal exposure on the tensile properties of aluminium AA 5083silicon carbide (SiC)fly ash composites were studied in the present work. The specimens were fabricated with varying wt.% of fly ash and silicon carbide and subjected to T6 thermal cycle conditions to enhance the properties through precipitation hardening. The analyses of the microstructure and the elemental distribution were carried out using scanning electron microscopic (SEM) images and energy dispersive spectroscopy (EDS). The composite specimens thus subjected to thermal treatment exhibit uniform distribution of the reinforcements, and the energy dispersive spectrum exhibit the presence of Al, Si, Mg, O elements, along with the traces of few other elements. The effects of reinforcements and heat treatment on the tensile properties were investigated through a set of scientifically designed experimental trials. From the investigations, it is observed that the tensile and yield strength increases up to 160?C, beyond which there is a slight reduction in the tensile and yield strength with an increase in temperature (i.e., 200?C). Additionally, the % elongation of the composites decreases substantially with the inclusion of the reinforcements and thermal exposure, leading to an increase in stiffness and elastic modulus of the specimens. The improvement in the strength and elastic modulus of the composites is attributed to a number of factors, i.e., the diffusion mechanism, composition of the reinforcements, heat treatment temperatures, and grain refinement. Further, the optimisation studies and ANN modelling validated the experimental outcomes and provided the training models for the test data with the correlation coefficients for interpolating the results for different sets of parameters, thereby facilitating the fabrication of hybrid composite components for various automotive and aerospace applications. 2021 by the authors. -
Wear and Friction Behaviour of Aluminium Metal Matrix Composite Reinforced with Graphite Nano Particles for Vehicle Structures
In the current research work, AA7050 a marine aluminium alloy was reinforced with the nano graphite particles processed through stir casting technique. The scanning electron microstructure reveals that the nano particles were uniformly distributed over the matrix material and the hardness of the composites increase with raise in weight percentage of Gr particles owing to the Hall-Petch effect. The wear experiments were conducted by varying reinforcement, load, velocity, distance and temperature. The experimental runs were designed using the L25 orthogonal array in which wear, coefficient of friction and worn surface hardness were recorded as response. The wear resistance of the composites increases with raise in the graphite content attributed to the formation of mechanical mixed layer, the wear rate transfer from mild to severe when there swift in temperature from 100C to 150C. The worn surface hardness of the composites was higher than the as cast composites owing to the presence of Fe on the surface confirmed through the EDAX mapping. The composites were optimized using the modified PROMETHEE optimization technique and results revealed that AA7050 reinforced with 8% Gr particles showed best result and recommended for the marine sector. 2024. Carbon Magics Ltd. -
WEAR AND FRICTION BEHAVIOUR OF ALUMINIUM METAL MATRIX COMPOSITE REINFORCED WITH GRAPHITE NANOPARTICLES
In the current research work, AA7050 a marine aluminium alloy was reinforced with the nano-graphite particles, processed through the stir casting technique. The scanning electron microstructure reveals, that the nanoparticles were uniformly distributed over the matrix material and the hardness of the composites increased with a rise in the weight percentage of Gr particles owing to the Hall patch effect. The wear experiments were conducted by varying reinforcement, load, velocity, distance, and temperature, and the experimental runs were designed using the L25 orthogonal array, in which wear, coefficient of friction and worn surface hardness were recorded as a response. The wear resistance of the composites increases with a rise in the graphite content attributed to the formation of a mechanically mixed layer, the wear rate transfers from mild to severe, when there is shift in temperature from 100C to 150C. The worn surface hardness of the composites was higher than those of as-cast composites owing to the presence of Fe on the surface confirmed through the EDAX mapping. The composites were optimized using the modified PROMETHEE optimization technique and the results revealed that AA7050 reinforced with 8% Gr particles showed the best result and was recommended for the marine sector. 2024, Scibulcom Ltd.. All rights reserved. -
Fabrication and Characterization of AA7050 Nano Composites by Enhancing Directional Properties for High Impact Load Applications
The demand for materials with superior strength and impact resistance has driven the exploration of innovative composite materials. In this research, Al 7050 is chosen as the matrix material due to its excellent mechanical properties, whereas SiC and graphene nanoparticles are incorporated to tailor its directional strength characteristics. The fabrication process involves the synthesis of Al7050 nanocomposites through a meticulous blending of nanoparticles with the matrix material. The characterization phase encompasses a comprehensive analysis of various techniques, including scanning electron microscopy, X-ray diffraction, and mechanical testing. The results shows that the directional strength improvements achieved through SiC and graphene nanoparticle reinforcement with Al7050. The tensile strength of the aluminum in the AA7050-7.5g composite rose from 185.3 to 256.1MPa upon the addition of SiC and graphene. The findings of this study contribute to the evolving field of nanocomposite materials, offering insights into the design and development of advanced materials tailored for specific directional strength requirements. The Institution of Engineers (India) 2024. -
A Novel Edge-Based Trust Management System for the Smart City Environment Using Eigenvector Analysis
The proposed Edge-based Trust Management System (E-TMS) uses an Eigenvector-based approach for eliminating the security threats present in the Internet of Things (IoT) enabled smart city environment. In most existing trust management systems, the trust aggregation process completely depends on the direct trust ratings obtained from both legitimate and malicious neighboring IoT devices. E-TMS possesses an edge-assisted two-level trust computation approach for ensuring the malicious free trust evaluation of IoT devices. The E-TMS aims at removing the false contribution on aggregated trust data. It utilizes the properties of the Eigenvector for identifying compromised IoT devices. The Eigenvector Analysis also helps to avoid false detection. The analysis involves a comparison of all the contributed trust data about every single connected device. A spectral matrix will be generated corresponding to the contributions and the received trust will be scaled based on the obtained spectral values. The absolute sum of obtained values will contain only true contributions. The accurate identification of false data will remove the effect of malicious contributions from the final trust value of a connected IoT device. Since the final trust value calculated by the edge node contains only the trustworthy data, the prediction about the malicious nodes will be accurate. Eventually, the performance of E-TMS has been validated. Throughput and network resilience are higher than the existing system. 2022 G. Nagarajan et al. -
Mental health counsellors perceptions on use of technology in counselling
The objectives of the study were: (a) to explore the self-reported knowledge of counsellors about technology in counselling. (b) to understand the flexibility, usage, and openness to integrating the technology services in their practice, and (c) to identify the problems associated with using technology as a process in counselling. Semi-structured interviews of eleven practising counsellors in Bangalore and Chennai, India, recruited through snowball sampling, were used for data collection. The deductive content analysis of the interview transcripts generated seven concepts, each comprising of several categories. The seven concepts were 'attitude', 'strengths', 'weakness', 'suitability', 'skills and training', 'therapeutic alliance', and 'theoretical approaches'. The analysis revealed that the counsellors preferred face-to-face counselling and were not using technology for their mainstream practice, but all were quite aware of the process, the benefits and costs of using different forms of technology. The study revealed that the counsellors were also aware about the target population and mental health issues for online counselling. This study has strong implications for building additional skills and enhancing training for counsellors to use technology in their counselling practice, along with the formulation of legal and ethical policies, certification and licensing, in order to protect both the clients and counsellors. 2019, Springer Science+Business Media, LLC, part of Springer Nature. -
Rectangular Microstrip Patch Antenna Array Based Sectored Antenna for Directional Wireless Sensor Networks
Directional wireless Sensor Network (DSN) outperforms Wireless Sensor Network (WSN) over different parameters such as transmission range, interference, spatial reusability and energy efficiency. In this paper, a Rectangular Patch antenna Array (RPA) based sectored antenna is proposed for DSN. The individual sector is composed of two-element rectangular patch antenna array with a measured peak gain of 5.2 dBi and half-power beamwidth of 45. Single Pole 8 Throw (SP8T) Radio Frequency (RF) switchboard is designed to connect the sectored antenna to MICAz WSN mote. The antenna performance analysis carried out in simulation and real-time measurement via Ansys High Frequency Structure Simulator (HFSS) and Vector Network Analyzer (VNA) exhibits higher gain, lower return loss, half-power beamwidth and Voltage Standing Wave Ratio (VSWR). 2020 IEEE. -
Energy-Efficient Long-Range Sectored Antenna for Directional Sensor Network Applications
The popularity of Directional Sensor Network (DSN) is increasing due to their improved transmission range, spectral reusability, interference mitigation, and energy efficiency. In this paper, the radio module of the DSN is implemented using an eight-sector antenna array. Two types of sectored antennas, namely the Rectangular Patch Sectored Antenna (RPSA) and the Triangular Patch Sectored Antenna (TPSA), are proposed to operate at frequency of 2.4 GHz ISM band. The RPSA has a half-power beamwidth (HPBW) of 45 and a peak gain of 5.2 dBi, while the TPSA has an HPBW of 48 and a peak gain of 4.16 dBi. The design and performance evaluation of RPSA and TPSA in terms of gain, reflection characteristics (|S11|), and HPBW are conducted using Ansys High Frequency Structure Simulator (HFSS) and Vector Network Analyzer (VNA). To demonstrate the concept, the fabricated sectored antennas are connected to MicaZ Wireless Sensor Network (WSN) nodes using an indigenously designed Single Pole 8 Throw (SP8T) Radio Frequency (RF) switchboard. The performance of the DSNs based on RPSA and TPSA is evaluated using the Cooja simulator and a testbed consisting of MicaZ nodes. The results show that RPSA outperforms TPSA and omnidirectional-based WSNs in terms of power consumption, received signal strength, and packet delivery ratio. 2024 IETE. -
Hybrid area explorationbased mobility-assisted localization with sectored antenna in wireless sensor networks
In common practice, sensor nodes are randomly deployed in wireless sensor network (WSN); hence, location information of sensor node is crucial in WSN applications. Localization of sensor nodes performed using a fast area exploration mechanism facilitates precise location-based sensing and communication. In the proposed localization scheme, the mobile anchor (MA) nodes integrated with localization and directional antenna modules are employed to assist in localizing the static nodes. The use of directional antennas evades trilateration or multilateration techniques for localizing static nodes thereby resulting in lower communication and computational overhead. To facilitate faster area coverage, in this paper, we propose a hybrid of max-gain and cost-utilitybased frontier (HMF) area exploration method for MA node's mobility. The simulations for the proposed HMF area explorationbased localization scheme are carried out in the Cooja simulator. The paper also proposes additional enhancements to the Cooja simulator to provide directional and sectored antenna support. This additional support allows the user with the flexibility to feed radiation pattern of any antenna obtained either from simulated data of the antenna design simulator, ie, high frequency structure simulator (HFSS) or measured data of the vector network analyzer (VNA). The simulation results show that the proposed localization scheme exhibits minimal delay, energy consumption, and communication overhead compared with other area explorationbased localization schemes. The proof of concept for the proposed localization scheme is implemented using Berkeley motes and customized MA nodes mounted with indigenously designed radio frequency (RF) switch feed network and sectored antenna. 2019 John Wiley & Sons, Ltd. -
Impact of Brexit on bond yields and volatility spillover across France, Germany, UK, USA, and India's debt markets
Britain's decision to exit the EU lead to disruptions in global markets. This study investigates the change in the return and volatility spillover pattern due to the repercussions of the Brexit vote between the US, France, the UK, Germany, and India's 10-year government bond yields by applying the VAR and GARCH-BEKK models. The findings demonstrate a substantial rise in the return spillover to India and USA 10-year government bond yields following the Brexit vote compared to the pre-Brexit vote era. In addition, the results showed evidence of unidirectional volatility spillover from India to France, bidirectional volatility spillover between the USA and India, and unidirectional volatility spillover from the UK to India 10-year government bond market post-Brexit vote. However, there was no interconnection between these markets before the Brexit vote. Therefore, the Brexit vote did affect and significantly increased the linkage between the US, France, the UK, and India's 10-year government bond market. The increase in correlation in India-US, India-UK, and India-France's 10-year government bond markets will help predict and have an important implication for hedgers, decision-makers, and portfolio managers if similar political events occur in the future. Sangeetha G. Nagarakatte, Natchimuthu Natchimuthu, 2022. -
Return and volatility spillover between India, UK, USA and European stock markets: The Brexit impact
The 2016 Brexit referendum created potential turmoil in financial markets. The purpose of this study is to examine the impact of the Brexit referendum on the return and volatility spillover between the EU, the UK, and the USA stock markets and the Indian stock market during the pre- and post-Brexit referendum period. The VAR and bivariate GARCH BEKK models were employed. The study results suggest that before the Brexit referendum, Indian stock market returns made no significant return spillover on the other markets. On the contrary, following the referendum, Indian stock returns significantly spilled over to France, Germany, the UK, and the USA stock market returns. The study results also identified a substantial increase in the bidirectional volatility spillover between India-France, India-UK, and India-USA during the post-Brexit referendum period. Therefore, the investors opportunity to invest simultaneously in India, UK, EU, and US stock markets for portfolio diversification is limited. India was affected mainly by its own past shocks before the Brexit referendum. However, after the Brexit referendum, Indian markets are getting more and more integrated with other markets. In order to reap the diversification benefits, a prudent investment strategy will need to be developed in the future, especially during times of economic and political uncertainty and market crisis. Sangeetha G Nagarakatte, Natchimuthu Natchimuthu, 2022