Stock prices, analysis and prediction

In this project I used advances statistics methods, Machine learning and Artificial Intelligence trying to answer the following questions:

Are there regularities in finance historical data? if so
Is it possible to express historical finance data as a series of regularities or small/simple patterns? If so what could be the right way to represent them (in length and shape), mathematical models? computational ones?
if there is repetition of patterns along the time, is there a chance to make predictions?
if is possible to make predictions, how far in the future can they be performed? This project has as background philosophical questions that find solution in research on complexity and neural sciences, such as:
how regularities take place in phenomena that seems random? Do these regularities can be represented as a pattern of regularities and then to have a single pattern of them?
What kind of computational and mathematical models realize such patterns
If is possible to model such behavior, how much we can trust in such predictions?
Is there a better way to approximate such complex behaviors?

Name		Name	Last commit message	Last commit date
Latest commit History 8 Commits
images		images
.gitignore		.gitignore
1.Analysis_a.py		1.Analysis_a.py
10.whole_analysis.py		10.whole_analysis.py
11.hierarchicalClustering.py		11.hierarchicalClustering.py
2. Analysis_b.py		2. Analysis_b.py
3.looking_for_patterns.py		3.looking_for_patterns.py
4.looking_for_patterns_2.py		4.looking_for_patterns_2.py
5.simple_clustering.py		5.simple_clustering.py
6.SOM.py		6.SOM.py
7.SVN.py		7.SVN.py
8.SVMimages.py		8.SVMimages.py
9.clustering_2.py		9.clustering_2.py
README.md		README.md
requirements.txt		requirements.txt

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