We study the effects of a firm's decision to disclose carbon emissions and carbon emissions intensity on the idiosyncratic volatility (IdVol) of U.S. S&P 500 firms from 2009 to 2019. We document that the decision to disclose corporate carbon emissions reduces the IdVol of...

A firm follows its industry peers when undertaking corporate diversification. We entitle this firm behavior peer effects in corporate diversification. Peer effects in corporate diversification are stronger in more competitive markets and in periods of tight external capital markets and high...

This paper investigates whether geopolitical risks (GPRs) contains incremental information content to predict crude oil futures volatility under high-frequency Heterogeneous Autoregressive (HAR) model specifications. Moreover, considering structural breaks in crude oil volatility, we extend the...

This paper examines the time-frequency spillovers and connectedness network between European ETS and the sustainability markets. Empirically, we rely on the Baruník and Křehlík (2018) Diebold and Yilmaz (2012) spillover index to measure the time-varying spillovers, directional spillover, net...

This paper examines the time and frequency dynamics of connectedness between oil price shocks (demand and supply), and energy, electricity, carbon and clean energy markets using the methodology developed by Diebold and Yilmaz (2012) and Barunik and Krehlik (2018). The empirical findings show...

Using a sample of firms from 24 countries over the 2001–2020 period, we investigate the relationship between economic policy uncertainty (EPU) and investment efficiency captured by the association between investment and growth opportunities. Consistent with our hypothesis, EPU negatively...

In a novel take on the gradual information diffusion hypothesis of Hong et al. (2007), we examine the predictive role of industries over aggregate stock market volatility. Using high frequency data for U.S. industry indexes and various heterogeneous autoregressive (HAR) type and machine learning...