Chapter 4 Does Economic Policy Uncertainty Matter for Stock Market Volatility? Abhisek Mishra and Byomakesh Debata Abstract This study examines the dynamic relationship between economic policy uncertainty (EPU) and stock market volatility in a pure order-driven emerging stock market. Considering the non-linear EPU-volatility relationship, this study uses GARCH family of models to capture the impact of policy uncertainty on stock market volatility. Empirical estimates reveal that economic policy uncertainty is an essential determinant of stock market volatility, and higher EPU leads to significant increase in volatility. We believe, a thorough understanding the EPU-Volatility relationship can be beneficial for investors to better predict the behaviour of stock market volatility. Keywords Economic policy uncertainty · GARCH models · Stock market volatility JEL Code E44 · G12 · G14 4.1 Introduction Stock market volatility has been a pertinent subject of interest for investors, policymakers, academic researchers and practitioners due to its implications for asset pricing, hedging, risk management, portfolio diversification, predicting future prospects of market and maintaining financial market stability (Paye, 2012; Ropach & Zhou, 2013; Antonakakis, Balcilar, Gupta, & Kyei, 2016). In the post-global financial crisis, the Economic Policy Uncertainity (EPU) has received considerable attention in finance literature. Existing studies have found that EPU has potential negative effects on various economic activities including economic growth, infla- tion, investment and employment (Rodrik, 1991; Bloom, Bond, & Reenen, 2007; A. Mishra (B ) Nabakrushna Choudhury Centre for Development Studies, Bhubaneswar, India e-mail: abhisek.mishra@hotmail.com B. Debata Birla Institute of Technology and Science, Pilani Campus, Vidya Vihar, Rajasthan, India © The Author(s), under exclusive license to Springer Nature Switzerland AG 2020 A. K. Mishra et al. (eds.), The Financial Landscape of Emerging Economies, Accounting, Finance, Sustainability, Governance & Fraud: Theory and Application, https://doi.org/10.1007/978-3-030-60008-2_4 45