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[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)\n2. [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)\n3. [Alpha factors, Alphalens](https://github.com/gtesei/python-for-finance-notes/blob/master/3__Alpha_Factors.ipynb)\n4. [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)\n5. [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)\n6. [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)\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgtesei%2Fpython-for-finance-notes","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgtesei%2Fpython-for-finance-notes","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgtesei%2Fpython-for-finance-notes/lists"}