In this paper, we modify Duan’s (1995) local risk-neutral valuation relationship (mLRNVR) for the GARCH option-pricing models. In our mLRNVR, the conditional variances under two measures are designed to be different and the variance process is more persistent in the risk-neutral measure than...

This paper provides several estimates of the GARCH models' parameters for the S&P500 index, based on returns and CBOE VIX. Using a daily sample collected from 2007 to 2022, we can conclude that adding the VIX information improves the estimates of the long-term volatility. By providing an...

An accurate weather forecast is the basis for the valuation of weather derivatives, securities that partially compensate for financial losses to holders in case of, from their perspective, adverse outside temperature. The paper analyses precision of two forecast models of average daily...

We provide a new framework for modeling trends and periodic patterns in high-frequency financial data. Seeking adaptivity to ever-changing market conditions, we enlarge the Fourier flexible form into a richer functional class: both our smooth trend and the seasonality are non-parametrically...

The estimation of inflation volatility is important to Central Banks as it guides their policy initiatives for achieving and maintaining price stability. This paper employs three models from the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) family with a view to providing a...

This paper introduces Quasi-Maximum Likelihood Estimation for Long Memory Stock Transaction Data of unknown underlying distribution. The moments with conditional heteroscedasticity have been discussed. In a Monte Carlo experiment, it was found that the QML estimator performs as well as CLS and...

This paper considers observation driven models with conditional mean and variance dynamics for non-negative valued time series. The motivation is to relax the restriction imposed on the higher order moment dynamics in standard multiplicative error models driven only by the conditional mean...

In this paper, we used the GARCH (1,1) and GARCH-M (1,1) models to investigate volatility and persistence at daily frequency for European and US financial markets. In the study we included fourteen stock indices (twelve Europeans and two Americans), during March 2013 - January 2017. The results...

In this paper we propose a maximum entropy estimator for the asymptotic distribution of the hedging error for options. Perfect replication of financial derivatives is not possible, due to market incompleteness and discrete-time hedging. We derive the asymptotic hedging error for options under a...