We propose a neural network-based approach to calibrating stochastic volatility models, which combines the pioneering grid approach by Horvath et al. (2021) with the pointwise two-stage calibration of Bayer and Stemper (2018). Our methodology inherits robustness from the former while not...

This work focuses on the the stability and mean growth rate of stochastic Solow growth model. The uncertainty in our model is generated by the technology part, which includes fluctuations on the technological accumulation and jump growth from new inventions and ideas. We introduce the criteria...