2025-04-29 01:34
IndustryIdentify ARIMA Parameters
#CurrencyPairPrediction
Identify ARIMA Parameters (p, d, q) ARIMA has three parameters:
• p = lag order (autoregressive)
• d = differencing order
• q = moving average order Use ACF (AutoCorrelation Function) and PACF (Partial AutoCorrelation Function) plots: from statsmodels.graphics.tsaplots import plot_acf, plot_pacf plot_acf(price_diff, lags=40) plot_pacf(price_diff, lags=40) plt.show()
• ACF plot → helps choose q (MA part).
PACF plot → helps choose p (AR part). Or, automatically find best (p, d, q) using auto_arima: from pmdarima import auto_arima model = auto_arima(price, seasonal=False, trace=True) print(model.summary())
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Identify ARIMA Parameters
Malaysia | 2025-04-29 01:34#CurrencyPairPrediction
Identify ARIMA Parameters (p, d, q) ARIMA has three parameters:
• p = lag order (autoregressive)
• d = differencing order
• q = moving average order Use ACF (AutoCorrelation Function) and PACF (Partial AutoCorrelation Function) plots: from statsmodels.graphics.tsaplots import plot_acf, plot_pacf plot_acf(price_diff, lags=40) plot_pacf(price_diff, lags=40) plt.show()
• ACF plot → helps choose q (MA part).
PACF plot → helps choose p (AR part). Or, automatically find best (p, d, q) using auto_arima: from pmdarima import auto_arima model = auto_arima(price, seasonal=False, trace=True) print(model.summary())
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