Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Contrary to the current practice that mainly considers stand-alone statistical loss functions, the aim of the paper is to assess oil price volatility forecasts based on objective-based evaluation criteria, given that different forecasting models may exhibit superior performance at different applications. Thus, we forecast the implied and several intraday oil price volatilities and we evaluate them based on financial decisions for which these forecasts are used. Confining our interest on the use of such forecasts from financial investors, we consider four well-established volatility trading strategies. We evaluate the after-cost profitability of each forecasting model for 1-day up to 66-days ahead. Our results convincingly show that our forecasting framework is economically useful, since different models provide superior after-cost profits depending on the economic use of the volatility forecasts. Should investors evaluate the forecasting models based on statistical loss functions, then their financial decisions are sub-optimal. Several robustness tests confirm these findings.