Golembiovskii D.Y.

This work is devoted to studying methods for modeling and forecasting the value of underlying assets based on market option prices. The use of options allows one to recover probability distributions of future asset prices and construct their volatility surfaces, which is necessary for modeling asset dynamics and valuing derivative financial instruments. Non-parametric approaches based on the extraction of risk-neutral probability density functions from option prices are considered, as well as parametric implied volatility surface models, such as SVI and SABR, which provide input for constructing the dynamic Dupire local volatility model. Dynamic models of asset prices with calibration based on market option quotes are also discussed, including the Heston model and discrete ARMA-GARCH models.