Extract and Analys data from Iran bourse or stock exchange
دانلود و تحلیل کننده داده های بورس اوراق بهادار تهران
- Bayesian Approach, like : Bayesian Inference
- To prevent overfitting on small data
- To use human expertise and belief
- Frequentist Inference, such as : hypothesis testing
- To apply descriptive analysis
- To apply diagnostic analysis
- To apply prescriptive analysis
- To apply predictive analysis
- Other data science techniques, like : Neural network and Machine Learning Technologies
- To handel time series with large input dimension
- To use useful libraries
- DataPrepairing
- AnalysisHelpers
- DecisionSupports
- My decision cycle is here
The last package is the main one !
- 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
- Bayesian Inference
- آموزش بورس اوراق بهادار
- انواع تحلیل
- فیلم های آموزشی انواع تحلیل
- حجم مبنا و قیمت پایانی
email me : hosein.ghiasy at gmail.com