Preprint / Version 1

Cross Country Determinants of Investors' Sentiments Prediction in Emerging Markets Using ANN

Authors

  • Ananth Rao Dubai Business School, University of Dubai, Dubai, United Arab Emirates
  • Anuj Verma Lal Bahadur Shastri Institute of Management, New Delhi, India
  • Thi Le Murdoch Business School, Murdoch University, Dubai, United Arab Emirates
  • Tarun Soni FORE School of Management, New Delhi, India
  • Gaurav Joshi Lal Bahadur Shastri Institute of Management, New Delhi, India
  • B Prashanth Department of Information Science and Engineering, Nitte Meenakshi Institute of Technology, Bangalore, India
  • Shadi Atalla College of Engineering and Information Technology, University of Dubai, Dubai, United Arab Emirates
  • Immanuel Moonesar Health Administration and Policy, Academic Affairs, Department of Public Health, Mohammed Bin Rashid School of Government (MBRSG), Dubai, United Arab Emirates
  • Manoj V Department of Information Science and Engineering, Nitte Meenakshi Institute of Technology, Bangalore, India
  • Hazem Marashdeh Department of Finance, College of Business Administration, Abu Dhabi University, Abu Dhabi, United Arab Emirates

Keywords:

investor sentiments, emerging markets, market index return, ANN, SDG 3, SDG 8, health financial management

Abstract

The paper models investor sentiments (IS) to attract investments for Health Sector and Growth in emerging markets, viz., India, Mainland China, and the UAE, by asking questions such as: What specific healthcare sector opportunities are available in the three markets? Are the USA-IS key IS predictors in the three economies? How important are macroeconomic and sociocultural factors in predicting IS in these markets? How important are economic crises and pandemic events in predicting IS in these markets? Is there contemporaneous relation in predicting IS across the three countries in terms of USA-IS, and, if yes, is the magnitude of the impact of USA-IS uniform across the three countries' IS? The artificial neural network (ANN) model is applied to weekly time-series data from January 2003 to December 2020 to capture behavioral elements in the investors' decision-making in these emerging economies. The empirical findings confirmed the superiority of the ANN framework over the traditional logistic model in capturing the cognitive behavior of investors. Health predictor—current health expenditure as a percentage of GDP, USA IS predictor—spread, and Macro-factor GDP—annual growth % are the common predictors across the 3 economies that positively impacted the emerging markets' IS behavior. USA (S&P 500) return is the only common predictor across the three economies that negatively impacted the emerging markets' IS behavior. However, the magnitude of both positive and negative impacts varies across the countries, signifying unique, diverse socioeconomic, cultural, and market features in each of the 3 economies. The results have four key implications: Firstly, US market sentiments are an essential factor influencing stock markets in these countries. Secondly, there is a need for developing a robust sentiment proxy on similar lines to the USA in the three countries. Thirdly, investment opportunities in the healthcare sector in these economies have been identified for potential investments by the investors. Fourthly, this study is the first study to investigate investors' sentiments in these three fast-emerging economies to attract investments in the Health Sector and Growth in the backdrop of UN's 2030 SDG 3 and SDG 8 targets to be achieved by these economies. Keywords: investor sentiments, emerging markets, market index return, ANN, SDG 3, SDG 8, health financial management

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