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Renewables introduce new weather-induced patterns and risks for market participants active in the energy commodity sector. We present a flexible framework for power spot prices that is capable of incorporating a weather model for the joint distribution of local weather conditions. This not only allows us to make use of a long history of local weather data in the calibration procedure but also makes it possible to assess how changes in the renewable generation portfolio impact the characteristics of future wholesale spot prices. Empirical tests demonstrate the model’s capability to reproduce salient features of market variables. We furthermore show why our model offers unique benefits for market players compared to existing approaches.

Why do investors entrust active mutual fund managers with large sums of money while receiving negative excess returns on average? Our explanation is that investors have a coarser information set than fund managers which leads them to systematically misinterpret managers' skill. When investors are unable to correctly quantify risk because they have no knowledge of factor investing on beyond-market-risk factors, Fake Alpha strategies based on factor investing look like skill from the investors' perspective. As running such strategies is relatively cheap for the managers, the investors' coarser information set misleads them to invest beyond the point of zero excess returns in equilibrium. We confirm our theory by analyzing the sample of US equity active managed mutual funds and find significant evidence of decreasing returns to scale at the fund level as well as negative excess returns to investors in equilibrium states.

Renewables introduce new weather-induced patterns and risks for market participants active in the energy commodity sector. We present a flexible framework for power spot prices that is capable of incorporating a weather model for the joint distribution of local weather conditions. This not only allows us to make use of a long history of local weather data in the calibration procedure but also makes it possible to assess how changes in the renewable generation portfolio impact the characteristics of future wholesale spot prices. Empirical tests demonstrate the model's capability to reproduce salient features of market variables. We furthermore show why our model offers unique benefits for market players compared to existing approaches.

We provide evidence of a strong effect of the underlying stock's illiquidity on option prices by showing that the average absolute difference between historical and implied volatility increases with stock illiquidity. This pattern translates into significant excess returns of option trading strategies that are not explained by common risk factors. Simulation results show, however, that our results can be explained by the hedging costs of market makers who are net long in options on some underlyings and net short in options on other underlyings. Our empirical findings are robust with respect to the chosen illiquidity measure, the measure of option expensiveness, and the return period.

We analyze the impact of market frictions on trading volume and liquidity premia of finite maturity assets when investors differ in their trading needs. Our equilibrium model generates a clientele effect (frequently trading investors only hold short-term assets) and predicts i) a hump-shaped relation between trading volume and maturity, ii) lower trading volumes of older compared to younger assets, iii) an increasing liquidity term structure from ask prices, iv) a decreasing or U-shaped liquidity term structure from bid prices, and v) spill-overs of liquidity from short-term to long-term maturities. Empirical tests for U.S. corporate bonds support our theoretical predictions.