Ali Safdari-Vaighani; Pooya Garshasebi
Abstract
The financial markets reveal stylized facts that could not be captured by Black-Scholes partial differential equations (PDEs). In this research, we investigate 3/2 stochastic volatility to pricing options which is more compatible with the interpretation of implied volatility. Numerical study and ...
Read More
The financial markets reveal stylized facts that could not be captured by Black-Scholes partial differential equations (PDEs). In this research, we investigate 3/2 stochastic volatility to pricing options which is more compatible with the interpretation of implied volatility. Numerical study and calibrations show that the 3/2 model incorporating jumps effectively encompasses key market characteristics attributed. However, it requires more estimating parameters in comparison to the pure diffusion model. Stochastic volatility models with jumps describe the log return features of the financial market although more parameters are involved in estimations.
Marzieh Vahdani; Ali Safdari
Abstract
Insurance companies and pension funds which deal with human lifetime are interested in mortality forecasting to minimize the longevity risk. In this paper, we studied the mortality forecasting model based on the age-specific death rates by the usage of the state-space framework and Kalman filtering technique. ...
Read More
Insurance companies and pension funds which deal with human lifetime are interested in mortality forecasting to minimize the longevity risk. In this paper, we studied the mortality forecasting model based on the age-specific death rates by the usage of the state-space framework and Kalman filtering technique. To capture the volatility of time, the time varying trend has been added to the Lee-Carter (LC) model, which is the benchmark methodology in modeling and forecasting mortality since it was introduced in 1992. So, this model is a random walk with time varying drift (TV). We illustrated the performance of the proposed model using Iranian mortality data over the period 1950–2015. Numerical results show that, both models have good fitness and are tangent. So the TV model acts as well as the LC model, but the TV model has the advantages of fewer calculations and the time-varying drift which can be beneficial in time varying data sets.