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Forecasting the Price of Bitcoin with Geometric Fractional
Brownian Motion Through Monte Carlo Approach
Che Aimi Mastura Binti Che Mansor
Supervisor: Dr. Hassilah Binti Salleh
Bachelor of Science (Financial Mathematics)
School of Informatics and Applied Mathematics
Bitcoin is a cryptocurrency derived from mathematical cryptography introduced in 2009
under a pseudonym Satoshi Nakamoto. Based on the data at World Coin Index website,
the Bitcoin market price is fluctuated since it being introduced until today. This paper
demonstrates the appropriate volatility measurement that may provide forecast value
which closely approximate to actual movement of Bitcoin price for a better investment
decision. Data is taken from World Coin Index and being analysed through a Hurst
exponent H > 1 in order to forecast the price of Bitcoin. A Monte Carlo approach with
2
10 4 Geometric Fractional Brownian Motion (GFBM) is performed as extensions of historical
data. The computer algebra system M ATHEMATICA is applied throughtout this paper; in
particular, fBms are generated as Fractional Brownian Motion Process [ μ , σ , H ]. The
accuracy of statistical inferences is 10%.
795 | UMT UNDERGRADUATE RESEARCH DAY 2018