# StockProdiction

**Repository Path**: TerenceLau/StockProdiction

## Basic Information

- **Project Name**: StockProdiction
- **Description**: Stock Prodiction by SVM & ARIMA
- **Primary Language**: Python
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 1
- **Created**: 2021-05-03
- **Last Updated**: 2021-12-15

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

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                |
|:----------------------------------:|
| ![Conclusion](pic/ARIMA_EX.png)    |

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                  |
|:----------------------------------:|
| ![Conclusion](pic/SVM_V2.0.png)    |