Sentence examples for modeling the volatility from inspiring English sources

The GARCH model is used for modeling the volatility of daily return series for the three types of contracts (near, next near, and far contracts) for crude oil and gold commodity futures and only for next near and far month contracts for mentha oil futures.

This approach is less exact than the SDE approach in modeling the volatility of the underlying stochastic interaction between molecules.

This approach is rigorously modeling the volatility of the stochastic dynamics of the kinetic processes provided that the assumptions of the SDE approximation itself are valid.

We model the volatility in the error term in our MS-AR model as a Garch (1,1).

In particular, this study tried to model the volatility dynamics of the taka US dollar exchange rate return using GARCH, APARCH, EGARCH, TGARCH, and IGARCH models.

This study aimed to model the volatility of the taka US dollar exchange rate return using daily observations over a span of 7 years.

It does far more than just plotting risk graph such as modeling the implied volatility of the stock.

Further, (gamma) is the speed of transition parameter and (gamma > 0) ensures that the transition between the regimes follows a nonlinear sigmoid type transition in modeling the dynamics of the conditional volatility.

As equation system (6) represents, we conducted a VAR analysis to estimate the SOPIt type shock variable and we model the volatility of crude oil returns with an AR(1 -GARCH 1,1) specification.

Similarly, Çağlayan, Ün, and Dayıoğlu (2013) modeled the exchange rate volatility of MIST (Mexico, Indonesia, South Korea, and Turkey) countries against the US dollar using asymmetric GARCH models.

The new model is a multiple regime smooth transition extension of the Heterogeneous Autoregressive (HAR) model, which is specifically designed to model the behavior of the volatility inherent in financial time series.