Simple Stock Price Forecasting using FinanceData
Below illustrates the file structure after every auto-generated file and folder is created.
.Quant
+-- Crawler
| +-- crawled_result
| +-- [stock_code]
| +-- News
| +-- fullPage
| +-- pages[from-to].csv
| +-- page[page].csv
| +-- Research
| +-- fullPage
| +-- pages[from-to].csv
| +-- page[page].csv
| +-- __init__.py
| +-- Google_Crawler.py
| +-- Naver_Crawler.py
|
+-- FinanceData
| +-- __init__.py
| +-- FinanceDataCollection.py
|
+-- Model
| +-- [stock_code]_final_data
| +-- image.png
| +-- [stock_code]_plots
| +-- image.png
| +-- Feature_Engineering
| +-- image.png
| +-- model_checkpoints
| +-- [model_name].h5
| +-- __init__.py
| +-- data_config.py
| +-- Data_preparation.py
| +-- FeatureEngineering.py
| +-- Gradient_Boosting.py
| +-- LSTM_Model_.py
| +-- Multivariate_LSTM.py
| +-- Multivariage_supervised_LSTM.py
| +-- Prophet_Model.py
|
+-- NLP
| +-- __init__.py
| +-- config.py (credentials, thus gitignored)
| +-- GCP_Language.py
| +-- Saltlux_Language.py
| +-- entities[id].json
| +-- sentiment[id].json
| +-- keyword[id].json
|
+-- __init__.py
+-- [your_GCP_credential].json
+-- Predict.py
will be updated
Samsung Open, High, Low, Close Stock Price Prediction (LSTM)
Samsung Golden and Dead Cross based on Moving Average
Fourier Transforms on Samsung stock price for Denoising
Feature Importance Test
Facebook Prophet's prediction on Samsung Close price
Facebook Prophet's prediction on ARKQ ETF
