Marie Skłodowska-Curie Fellow at BCAM - Basque Center for Applied Mathematics
This paper proposes to model the asymmetric response of the volatility to the sign of past returns (leverage effect) nonparametrically in the context of stochastic volatility models. The new stochastic volatility specifications are able to generate volatility clustering and allow for a flexible time-varying functional form of the volatility asymmetry. The objective is to improve option price forecasting by improving the volatility forecasting given that the option pricing depends mainly on the moneyness, maturity and the asset price volatility. The forecasting performances of the new models are compared with three parametric asymmetric stochastic volatility models via intensive Monte Carlo experiments and empirically by fitting the benchmarks and our proposals to two series of financial returns. Using S&P 400 MidCap and S&P 500 options for the 2008 and 2013-1014 periods, we examine parametric and nonparametric forecast performance from three perspectives: (1) underlying volatility forecast accuracy, (2) out-of-sample pricing forecast, and (3) dynamic delta hedging effective cost.
To achieve these objectives, our group will explore the synergies and trade-offs between multiple dimensions of space and time, and between water, energy, and agricultural sectors.. This multi-scale approach will be adopted to propose preferable solutions to approach global challenges for achieving sustainability, while trying to integrate a nexus approach from river basin up to country and global scales. Additionally, we will characterize how uncertainty is perceived by stakeholders and policy makers, how trust in models influences implementation and how researchers can best communicate and disseminate their methodologies, results, and broader impacts to policy relevant stakeholders.