Abstract
Volatility is a quantity that measures how far a stock or cryptocurrency price moves in a certain period. To measure volatility properly, it can be done by using volatility modeling. The stochastic volatility model is one of the models used to predict volatility in a time series data, one of the stochastic volatility model is the Heston model. There are two schemes for estimating volatility using the Heston model, namely the Euler scheme and the Milstein scheme. The purpose of this study is to compare the estimation results of Bitcoin volatility with the two schemes. In using the Heston model, several parameters such as , , dan are needed. This parameter is calculated using the maximum likelihood estimation method. The results of the calculation of these parameters, respectively, are = 29.9996, =0.1464, and =2.1164. With the help of these three parameters, volatility estimation is generated. In this study, the Milstein scheme produces a lower volatility value than the Euler scheme.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
