Modern Portfolio Theory (MPT) studies the tradeoff between return and risk. The risk of a portfolio is determined by not only the variance but also the correlations among assets. For a given risk, a rational investor would prefer an allocation with a higher expected returns; On the other hand, for a given return, he or she would prefer the portfolio with a lower risk level.
https://docs.anaconda.com/anaconda/install/windows/
https://docs.anaconda.com/anaconda/install/mac-os/
https://docs.anaconda.com/anaconda/install/linux/
conda create -n Portfolio_Selection python=3.6
conda activate Portfolio_Selection
pip install ipykernel
python -m ipykernel install --user --name=Portfolio_Selection
numpy
scipy
pandas
statsmodels
matplotlib
pandas_datareader
yfinance
FinanceDatabase
arch
cvxopt
cvxpy
prophet
seaborn
bokeh
geoplotlib
Altair
plotnine
scikit-learn
The first publicly available gradient boosting package. Released by Tianqi Chen (University of Washington, Seattle)
xgboost
lightgbm
catboost
keras
Tensorflow
https://drive.google.com/file/d/12ECPJMxV2wSalXG8ykMmkpa1fq_ur0Rf/view
nltk
textblog
gensim
scrapy
spacy
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blitz
git clone https://github.com/piEsposito/blitz-bayesian-deep-learning.git cd blitz-bayesian-deep-learning pip install .
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pyfolio
git clone https://github.com/quantopian/pyfolio cd pyfolio pip install .
conda install -c conda-forge nodejs
You can install plugins in Jupyter lab by clicking the jigsaw icon on the menu bar on the menu bar on the right of the editor.
toc
jupyterlab_variableInspector
jupyterlab_nbmetadata
jupyterlab_go_to_definition
conda install -c conda-forge jupyter_contrib_nbextensions