文件列表:

GYN.json (4932, 2017-01-21)
IASP520_ARMA_V1.01.py (4017, 2017-01-21)
IASP520_SVM.py (2381, 2017-01-21)
IASP520_SVM_V2.py (2970, 2017-01-21)
IASP520_SVM_V2_With_Polarity_Json.py (3775, 2017-01-21)
NQN.json (1706, 2017-01-21)
pic (0, 2017-01-21)
pic\ARIMA_EX.png (186338, 2017-01-21)
pic\ARIMA_V2.0.png (154056, 2017-01-21)
pic\SVM_V2.0.png (135022, 2017-01-21)

StockPrediction ========= Stock data come from Yahoo_finance by Python. News data come from tm.plugin by R. ARMIA === Step --- 1.Use Daubechies 4 wavelet to transform the Stock Data which comes from Yahoo_finance. 2.Difference the time series make it stationary. 3.Create ACF & Pacf pictures to find out p & q which is the parameter in ARIMA. 4.Predict the stationary time series by ARIMA(p,q). Because this ARIMA package can't do difference bigger than 2, thus I don't use ARIMA(p,d,q). 5.Revert difference which we do in step 2. | ARIMA | |:----------------------------------:| |  | SVM === Not good enough. I try to transform Price to the relation, like the relation between Open & Close attributes or today & yesterday. Stock can't be Predicted only based on history stock data, so we pull in new data. It's still not good but much better than before. | SVM | |:----------------------------------:| |  |

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