The renewable energy sector has accomplished remarkable growth rates over the last decade. This paper examines the dynamics of excess returns for the WilderHill New Energy Global Innovation Index, which lists firms in the renewable energy sector and is used as a global benchmark. We propose a...

This paper analyzes the effect of environmental regulation on stock returns (as a measure of economic performance) for German energy corporations. By using event study methodology, we consider the last minute victory of the acting government in the 2002 German federal elections to the Lower...

This paper analyzes the effect of environmental regulation on stock returns (as a measure of economic performance) for German energy corporations. By using event study methodology, we consider the last minute victory of the acting government in the 2002 German federal elections to the Lower...

This paper proposes a forward-looking metric of transition risk that relates financial performance and incremental carbon costs at the firm level. To this end, we use a consistent dividend discount framework augmented with emission costs of firms and climate scenario projections from four...

Realized divergence gauges the distinct realized moments associated with time-varying uncertainty and is tradeable with divergence swaps engineered from delta-hedged option portfolios. Consistently with established notions of symmetry in arbitrage-free option markets, implied divergence...

We study the term structure of variance (total risk), systematic and idiosyncratic risk. Consistent with the expectations hypothesis, we find that, for the entire market, the slope of the term structure of variance is mainly informative about the path of future variance. Thus, there is little...

Machine learning (ML) is a novel method that has applications in asset pricing and that fits well within the problem of measurement in economics. Unlike econometrics, ML models are not designed for parameter estimation and inference, but similar to econometrics, they address, and may be better...