This paper proposes “implied stochastic volatility models” designed to fit option-implied volatility data and implements a new estimation method for such models. The method is based on explicitly linking observed shape characteristics of the implied volatility surface to the coefficient functions that define the stochastic volatility model. The method can be applied to estimate a fully flexible nonparametric model, or to estimate by the generalized method of moments any arbitrary parametric stochastic volatility model, affine or not. Empirical evidence based on S&P 500 index options data show that the method is stable and performs well out of sample.

Using a large panel of more than 140,000 state-owned enterprises (SOEs), this study examines SOEs’ investment behavior surrounding 82 national elections in 25 European countries between 2001 and 2015. We find that SOEs increase their corporate investment by about 29% of the sample average during national election years. This effect is more pronounced in fixed timing and closely contested elections. The effect is also stronger in countries with low institutional quality, more centralized political systems, and state-controlled banking systems. In contrast, we find the matched non-SOEs significantly decrease their corporate investment during national election years.