Constructing a Global Fear Index for the COVID-19 Pandemic

By Afees A. Salisu, Lateef Akanni. Emerging markets finance & trade, 2020

229 citations recorded by the source corpus.

ABSTRACT This paper offers two main innovations. First, we construct a global fear index (GFI) for the COVID-19 pandemic to support economic, financial, and policy analyses in this area. Second, we demonstrate the application of the index to stock return predictability using OECD data. The panel data predictability results reveal the significance of the index as a good predictor of stock returns during the pandemic. Also, we find that accounting for “asymmetry” effect and macro (common) factors improves the forecast performance of the GFI-based predictive model for stock returns. With regular updates and improvements of the index, several empirical analyses can be extended to other macroeconomic fundamentals in future research.

Subfields: Economics and Econometrics, Modeling and Simulation

View Paper: https://www.semanticscholar.org/paper/df90af8246b75e7f6a6c3c6fb7f5660012935a77

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

  1. Sikiru Abidemi Abdulsalam
  2. K. Prabheesh
  3. Afees A. Salisu
  4. Bhavesh Garg
  5. Rakesh Padhan

In Modeling and Simulation

  1. K. Prabheesh

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