Connectedness of energy markets around the world during the COVID-19 pandemic.

This paper studies the connectedness among energy equity indices of oil-exporting and oil-importing countries around the world. For each country, we construct time-varying measures of how much shocks this country transmits to other countries and how much shocks this country receives from other countries. We analyze the network of countries and find that, on average, oil-exporting countries are mainly transmitting shocks, and oil-importing countries are mainly receiving shocks.

Forecasting mid-price movement of Bitcoin futures using machine learning.

In the aftermath of the global financial crisis and ongoing COVID-19 pandemic, investors face challenges in understanding price dynamics across assets. This paper explores the performance of the various type of machine learning algorithms (MLAs) to predict mid-price movement for Bitcoin futures prices. We use high-frequency intraday data to evaluate the relative forecasting performances across various time frequencies, ranging between 5 and 60-min.

Global uncertainties and portfolio flow dynamics of the BRICS countries.

This paper investigates the dynamics of bond and stock market capital flows to BRICS countries under uncertainties such as global economic policy uncertainty and the US trade policy uncertainty. We use a time-varying Granger causality framework over the January 2008-November 2019 period to analyze the predictive power of uncertainties on capital flows in the form of bond and equity. The results show that the effects are heterogeneous across countries and stronger during the Global Financial Crisis period and post-2018 period while it lost its significance in the subsequent period.