arminm4 / iranbourseanalyser

Python scripts for downloading and analyzing iran bourse (stock exchange) data. اسکریپت پایتون برای دانلود و تحلیل داده های بورس تهران.

Iran bourse data downloader and analyzer

Extract and Analys data from Iran bourse or stock exchange

دانلود و تحلیل کننده داده های بورس اوراق بهادار تهران

Our preference in decision support and inference approach are as below :

1. Bayesian Approach, like : Bayesian Inference
   • To prevent overfitting on small data
   • To use human expertise and belief
2. Frequentist Inference, such as : hypothesis testing
   • To apply descriptive analysis
   • To apply diagnostic analysis
   • To apply prescriptive analysis
   • To apply predictive analysis
3. Other data science techniques, like : Neural network and Machine Learning Technologies
   • To handel time series with large input dimension
   • To use useful libraries

This project has 3 packages

1. DataPrepairing
2. AnalysisHelpers
3. DecisionSupports
   • My decision cycle is here

The last package is the main one !

with following usage examples :

• DataPrepairing :

import DataPreparing.PrepareAllData
DataPreparing.PrepareAllData.DownloadAll()
DataPreparing.PrepareAllData.MergeAll()
DataPreparing.PrepareAllData.ExtractAll()

# for new function and their usage see "main.py" file

• AnalysisHelpers :

import AnalysisHelpers.Distributions
AnalysisHelpers.Distributions.computePercentOfChangeDistributionForAllNamadsAsWhole(OutputDir='DataPreparing/Data/distributions', InputFile='DataPreparing/Data/AllDataByDays.pkl')
AnalysisHelpers.Distributions.computePercentOfChangeDistributionForAllNamads(OutputDir='DataPreparing/Data/distributions', InputFile='DataPreparing/Data/AllNamadsByNamads.pkl')

import AnalysisHelpers.SomeCharts
AnalysisHelpers.SomeCharts.drawScaters(OutputDir='DataPreparing/Data/Charts', InputFile='DataPreparing/Data/AllNamadsByNamads.pkl')
AnalysisHelpers.SomeCharts.drawCorrelations(InputDir='DataPreparing/Data/NamadsExcelsFromIranBourse', OutputDir="Data/Charts/IntraNamadCorrelations")

• DecisionSupports :

# for new function and their usage see "main.py" file

Helps and Tutorial Articles

Analysis useful links

1. Bayesian Inference
   • Introduction to Bayesian Inference
   • PyMC: Bayesian Stochastic Modelling in Python
   • BayesPy: Variational Bayesian Inference in Python
   • Frequentism and Bayesianism: A Python-driven Primer
   • Frequentism and Bayesianism: A Practical Introduction
   • Bayesian Statistics at Coursera

Data sets useful links

• آموزش بورس اوراق بهادار
• انواع تحلیل
• فیلم های آموزشی انواع تحلیل
  • ویدیوهای تکنیکال مقدماتی
  • ویدیوهای تکنیکال پیشرفته
  • ویدیوهای تحلیل بنیادی مقدماتی
• حجم مبنا و قیمت پایانی

Support or Contact

email me : hosein.ghiasy at gmail.com