From December 2021, Proof-of-Work (PoW) crypto assets earn a systematic risk premium of 20\% p.a. over Proof-of-Stake (PoS) crypto assets. This finding aligns with asset pricing theory, suggesting that energy-intensive assets, such as PoW assets, should be systematically riskier than their less energy-intensive PoS counterparts due to the cyclicality of energy prices. We show that contemporaneously, the systematic part of the returns from a portfolio that is long PoW and short PoS covaries negatively with innovations in climate change concerns and with innovations in the oil price. A one standard deviation increase in climate change concerns is associated with 25\% of a standard deviation decrease in systematic PoW minus PoS returns. For an oil price shock, the corresponding number is 11\%. Prior to 2021, PoS assets were systematically riskier than PoW assets. We show that this can be attributed to the cyclicality of the opportunity cost associated with PoS, which dominates the energy-related risk premium of PoW in this period of the sample.
We propose a machine learning methodology for predicting the future liquidity distribution of individual bonds in the U.S. corporate bond market and use it to compute two forward-looking illiquidity measures: expected illiquidity and expected tail illiquidity as measure for downside liquidity risk. We find that bonds characterized by higher expected illiquidity have elevated systematic risk premiums, whereas expected tail illiquidity is predominantly reflected in the alpha. Investors in corporate bond funds preemptively sell their shares in response to anticipated liquidity declines in underperforming funds. All effects are much stronger compared to the standard approach of using today’s realized liquidity.