DR ANINDITA BHATTACHARJEE
@scmsnoida.ac.in
Associate Professor at symbiosis Centre for Management Studies
Symbiosis International University
RESEARCH INTERESTS
Broad areas:
• Modeling and simulation
• Quantitative Finance
• Econophysics
Specific areas:
• Modelling Financial data
• Analysing time series and forecast
• Exploring and characterizing capital market
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Anunay K. Chaudhary, Saureesh Das, Pankaj Narang, Anindita Bhattacharjee, and M. K. Das
Springer Nature Switzerland
Anindita Bhattacharjee, Dolly Gaur, and Kanishka Gupta
Emerald
PurposeIndia is not geographically close to either Russia or Ukraine. However, India's trade relations with them make it vulnerable to the consequences of the war between these countries. Thus, the present study aims to examine the impact of the Russia–Ukraine war on various sectoral indices of the Indian economy.Design/methodology/approachEvent study methodology has been used in this study for analysis. The date of the war announcement is the event day. The sample studied includes ten sectors of the Indian economy listed on the National Stock Exchange (NSE). Results correspond to the period of −167 days to +20 days of the announcement of the war, i.e. from June 25, 2021, to March 28, 2022.FindingsAlmost all the sample sectors earned significantly positive abnormal returns in the post-event period. The metal industry has led this group by showcasing the highest abnormal returns. Though Indian sectors made overall positive returns, the market soon corrected itself and abnormal returns were wiped out.Practical implicationsThese results can benefit portfolio managers, analysts, investors and policymakers in hedging risks and selecting suitable investments during increased global uncertainty. The study's conclusions help policymakers establish an institutional and supervisory framework that will make it easier to spot systematic risks and reduce them by putting countercyclical measures in place.Originality/valueIndia has no geographical proximity or trade relations with Russia or Ukraine, as strong as any other European country. However, Russia has remained a strong ally to India in the trade of defense equipment. Similar is the case with Ukraine, a significant global partner for India. Thus, the impact of conflict between these two countries has not been limited to Europe only but has also engulfed related economies. Hence, the present study is one of the first attempts to examine the burns sustained by the Indian economy due to this war.
Bhumika Gambhir and Anindita Bhattacharjee
Emerald
Purpose The purpose of this paper is to highlight how Artificial intelligence (AI) and its subsets are changing the face of the accounting and finance (A&F) profession. Expectations from A&F professionals are changing due to the expeditious changes in technology. This paper proposes new skill set expectations from these professionals. Design/methodology/approach This is a viewpoint paper based on the opinions/views of the employees working in medium and large organizations in A&F in the United Arab Emirates (UAE). The employee viewpoints were gathered through an emailed questionnaire. Findings This paper illustrates the need to embrace technology and acquire the necessary skills to work in conjunction with machines. This will help A&F professionals to meet the changing expectations of employers. Practical implications This paper emphasizes the usefulness of training, learning, and development of the skills necessary for A&F professionals to work with AI and its subsets. Originality/value This paper discusses how AI will bring in challenges and opportunities in the future. It suggests how A&F professionals can embrace technology (driven by AI) and understand to work with it.
Himani Singh
Institute of Advanced Scientific Research
Anindita Bhattacharjee and M.K. Das
Elsevier BV
ANINDITA BHATTACHARJEE, M. K. DAS, and SUBHENDU GHOSH
World Scientific Pub Co Pte Lt
Synchronization behavior of an ensemble of unidirectionally coupled neurons with a constant input is investigated. Chemical synapses are considered for coupling. Each neuron is also considered to be exposed to a self-delayed feedback. The synchronization phenomenon is analyzed by the error dynamics of the response trajectories of the system. The effect of various model parameters e.g. coupling strength, feedback gain and time delay, on synchronization is also investigated and a measure of synchrony is computed in each cases. It is shown that the synchronization is not only achieved by increasing the coupling strength, the system also required to have a suitable feedback gain and time delay for synchrony. Robustness of the parameters for synchrony is verified for larger systems.
Subhendu Ghosh, Anindita Bhattacharjee, Jyotirmoy Banerjee, Smarajit Manna, Naveen K. Bhatraju, Mahendra. K. Verma, and Mrinal K. Das
Springer Netherlands