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Autoregressive Integrated Moving Average (ARIMA) Model for Forecasting Cryptocurrency Exchange Rate in High Volatility Environment: A New Insight of Bitcoin Transaction
( Vol-4,Issue-11,November 2017
)

MLA Nashirah Abu Bakar et al ."Autoregressive Integrated Moving Average (ARIMA) Model for Forecasting Cryptocurrency Exchange Rate in High Volatility Environment: A New Insight of Bitcoin Transaction". International Journal of Advanced Engineering Research and Science(ISSN : 2349-6495(P) | 2456-1908(O)),vol 4, no. 11, 2017, pp.130-137 AI Publications, doi:10.22161/ijaers.4.11.20
APA Nashirah Abu Bakar, Sofian Rosbi(2017).Autoregressive Integrated Moving Average (ARIMA) Model for Forecasting Cryptocurrency Exchange Rate in High Volatility Environment: A New Insight of Bitcoin Transaction. International Journal of Advanced Engineering Research and Science(ISSN : 2349-6495(P) | 2456-1908(O)),4(11), 130-137. http://dx.doi.org/10.22161/ijaers.4.11.20
Chicago Nashirah Abu Bakar, Sofian Rosbi. 2017,"Autoregressive Integrated Moving Average (ARIMA) Model for Forecasting Cryptocurrency Exchange Rate in High Volatility Environment: A New Insight of Bitcoin Transaction". International Journal of Advanced Engineering Research and Science(ISSN : 2349-6495(P) | 2456-1908(O)).4(11):130-137. Doi: 10.22161/ijaers.4.11.20
Harvard Nashirah Abu Bakar, Sofian Rosbi. 2017,Autoregressive Integrated Moving Average (ARIMA) Model for Forecasting Cryptocurrency Exchange Rate in High Volatility Environment: A New Insight of Bitcoin Transaction, International Journal of Advanced Engineering Research and Science(ISSN : 2349-6495(P) | 2456-1908(O)).4(11), pp:130-137
IEEE Nashirah Abu Bakar, Sofian Rosbi."Autoregressive Integrated Moving Average (ARIMA) Model for Forecasting Cryptocurrency Exchange Rate in High Volatility Environment: A New Insight of Bitcoin Transaction", International Journal of Advanced Engineering Research and Science(ISSN : 2349-6495(P) | 2456-1908(O)),vol.4,no. 11, pp.130-137,2017.
Bibtex @article {nashirahabubakar2017autoregressive,
title={Autoregressive Integrated Moving Average (ARIMA) Model for Forecasting Cryptocurrency Exchange Rate in High Volatility Environment: A New Insight of Bitcoin Transaction},
author={Nashirah Abu Bakar, Sofian Rosbi},
journal={International Journal of Advanced Engineering Research and Science},
volume={4},
year= {2017},
}