FROM DISCRETE TO CONTINUOUS: GARCH VOLATILITY MODELING OF THE BITCOIN

Volatility is an important concept for identifying and predicting the risk of financial products. The aim study to determine most appropriate discrete model volatility Bitcoin returns using discrete-time GARCH its extensions compare it with Lévy driven continuous-time model. For this purpose, modeled daily data / United States Dolar exchange rate. By comparing models according information criteria likelihood values, All-GARCH Johnson's-SU innovations found be adequate persistence half-life are calculated estimation This has been compared continuous in which increments derived from compound Poisson process various error measurements. As a conclusion, that shows better performance predict volatility.