ARCH/GARCH models can assist or improve the forecast of ARIMA models. Firstly, time series data must be stationary for these models to be applicable. If not, we should apply some transformations such as differencing. Since these models are mainly used in finance we will refer to the price returns from Read more…
Los modelos ARCH/GARCH pueden asistir o mejorar el pronóstico de los modelos ARIMA . En primer lugar, los datos de las series temporales deben ser estacionarios para que estos modelos sean aplicables. Si no, deberíamos aplicar algunas transformaciones como la diferenciación. Dado que estos modelos se utilizan principalmente en finanzas, en adelante nos referiremos a Read more…
Volatility is a statistical measure of the dispersion of data or variance around its mean over a certain period of time. In finance, it refers to how much the price changes between periods. For example, if it is high, the price may increase or decrease a lot from one day Read more…