Bitcoin Time Series Forecasting Model Results

Last updated on: 2019-04-04

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The 1st most accurate forecasting model is the AutoARIMA model.

ARIMA(p,d,q,P,D,Q)[m]: p is 1 , q is 1 , P is 0 , Q is 0 , m is 1 , d is 1 , D is 0; Coefficient ar1 is -0.7 ; Coefficient ma1 is 0.77

The forcasted bitcoin prices for the coming 5 days are:
Lower.99..CI Lower.95..CI Lower.68..CI Forecasted.value Upper.68..CI Upper.95..CI Upper.99..CI
6 4271 4431 4681 4939 5197 5447 5607
7 3987 4221 4587 4965 5343 5709 5943
8 3755 4040 4486 4947 5407 5854 6139
9 3575 3906 4425 4960 5494 6013 6344
10 3404 3774 4353 4950 5548 6127 6497
model ME MAE MSE MPE MAPE
2 AutoARIMA 245 268 2e+05 5.2 5.8

The 2nd most accurate forecasting model is the AutoARIMA model.

ARIMA(p,d,q,P,D,Q)[m]: p is 1 , q is 1 , P is 0 , Q is 0 , m is 1 , d is 1 , D is 0; Coefficient ar1 is -0.7 ; Coefficient ma1 is 0.77

The forcasted bitcoin prices for the coming 5 days are:
Lower.99..CI Lower.95..CI Lower.68..CI Forecasted.value Upper.68..CI Upper.95..CI Upper.99..CI
6 4271 4431 4681 4939 5197 5447 5607
7 3987 4221 4587 4965 5343 5709 5943
8 3755 4040 4486 4947 5407 5854 6139
9 3575 3906 4425 4960 5494 6013 6344
10 3404 3774 4353 4950 5548 6127 6497
model ME MAE MSE MPE MAPE
2 AutoARIMA 245 268 2e+05 5.2 5.8

The 3rd most accurate forecasting model is the Regression model.

Fitted regression equation is: price^ = -1472.96 + 5.69 *t R-squared = 0.48 p-value = 0

The forcasted bitcoin prices for the coming 5 days are:
Lower.99..CI Lower.95..CI Lower.68..CI Forecasted.value Upper.68..CI Upper.95..CI Upper.99..CI
759 2387 4934 7556 10178 12726 14354
765 2392 4940 7562 10184 12732 14359
770 2398 4946 7568 10190 12737 14365
776 2404 4952 7573 10195 12743 14371
782 2409 4957 7579 10201 12749 14376
model ME MAE MSE MPE MAPE
Regression -3395 3395 1.2e+07 -82 82