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https://github.com/gtesei/python-for-finance-notes

Python notes on finance
https://github.com/gtesei/python-for-finance-notes

finance finance-notes portfolio-optimization python sharpe-ratio

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Python notes on finance

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# python-for-finance-notes

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__Python notes on finance__

## Suggested path

1. [Value of an European Call Option, Key Factors for Evaluating the Performance of a Portfolio, Get financial data, Plotting stock prices, Normalizing prices, Rolling statistics, Daily returns, Cumulative return, Rsk, Sharpe Ratio, ](https://github.com/gtesei/python-for-finance-notes/blob/master/1__Warmup.ipynb)
2. [Python optimizers, Convex/NonConvex loss functions, Basin Hopping and Simulated Annealing, More dimensions, contraints and bounds, Optimizing portfolios](https://github.com/gtesei/python-for-finance-notes/blob/master/2__Optimizing_Portfolios.ipynb)
3. [Alpha factors, Alphalens](https://github.com/gtesei/python-for-finance-notes/blob/master/3__Alpha_Factors.ipynb)
4. [Stock Picking 1, Cumulative return and Sharp Ratio as performance indicators ](https://github.com/gtesei/python-for-finance-notes/blob/master/4_1__Stock_Picking_Understand_the_Past.ipynb)
5. [Stock Picking 2, Correlation between Cumulative return and Sharp Ratio, dummy stock picker and performance degradation in time](https://github.com/gtesei/python-for-finance-notes/blob/master/4_2__Stock_Picking_The_Future_is_not_what_used_to_be.ipynb)
6. [Stock Picking 3.1, Forecasting stock prices with ARIMA models](https://github.com/gtesei/python-for-finance-notes/blob/master/4_3_1__Stock_Picking_Predicting_The_Future_Forecasting_ARIMA.ipynb)