Do U.S. investors worry about fear in international equity markets? Empirical evidence on dynamic panel data

Abstract

This is the first study of the dynamic relation between U.S. bilateral equity flows and the Chicago Board Options Exchange (CBOE's) implied volatility around the globe that employs the panel vector autoregression. We primarily find the unidirectional interdependence relation from the fear indices to the U.S. net equity flows and to the U.S. equity outflows, respectively. In addition, the impact of the fear indices on the U.S. equity flows is asymmetric, suggesting that U.S. investors are more sensitive during a high level of fear in foreign equity markets. Moreover, flight‐to‐quality, informational frictions and distance, and benefits of international portfolio diversification help to explain the movement of U.S. capital flows between European countries and Asia‐Pacific countries. Our findings call for policy makers in local equity markets to consider the impact.

Uncertainties and green bond markets: Evidence from tail dependence

“…Specifically, areas in various shades of red running from the northwest corner of these heatmaps to the north side reveal that UVIX and OVX could positively drive the volatility of the green bonds in bearish states, especially when the uncertainties change dramatically; meanwhile, if the UVIX and OVX are in the bearish state (0.05–0.45), green bond volatility would always be negatively dependent on them. The economic or financial story behind this asymmetric relationship is “financial contagion” and the “flight to quality” effect (Afonso & Kazemi, 2020; Cheuathonghua & Padungsaksawasdi, 2019). Since green bonds have become an optional asset in diversification, the huge increases in financial uncertainty would guide a capital flight from risky assets to safe havens.…”

Does market power explain margins in dual banking? Evidence from panel quantile regression

“…Studies on the bank market power use different methods such as OLS regression, panel data with fixed effects (FE) or random effects (RE), and GMM (Ahmed & Hla, 2019; Alexiou, Vogiazas, & Nellis, 2018; Almaqtari, Al‐Homaidi, Tabash, & Farhan, 2019; Amidu & Wolfe, 2013; Cheuathonghua & Padungsaksawasdi, 2019; Jiménez, Lopez, & Saurina, 2013; Labidi & Mensi, 2015; Soedarmono et al, 2011). On the other hand, the QR method is more robust to outliers (Feng & Huang, 2020; Lyon & Olmo, 2018; Oliveira, Tabak, de Lara Resende, & Cajueiro, 2013) and thus more appropriate for the analysis of the interest margin, as it considers the conditional distribution of the regressor (dependent variable), which in our case is not homogeneous 1 and has an increasing hetero trend.…”

Asset allocation, limited participation and flight‐to‐quality under ambiguity of correlation

“…Finally, our paper provides a new theoretical explanation for the appearance of flight‐to‐quality phenomenon by incorporating correlation ambiguity. Many of the existing papers illustrate the phenomenon in the episodes of financial crises (Tunaru & Fabozzi, 2021; Gubareva & Keddad, 2020; Cheuathonghua & Padungsaksawasdi, 2019; etc.) by the changes in market liquidity (Rösch & Kaserer, 2013; Guerrieri & Shimer, 2014; Bethke et al, 2017; etc.…”