Update app.py
Browse filesMade changes to better explain EF
app.py
CHANGED
@@ -120,11 +120,22 @@ With this initial analysis, beta was calculated to determine the stock’s risk
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price changes to the benchmark. By using CAPM model, annual expected return and portfolio
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return is calculated. The model results can be found in Appendix A.
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"""
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##### EDIT HERE ##### koi
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ef_viz(choices['data'],choices['choices'])
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##### #####
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beta(choices['data'], choices['choices'])
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ER(choices['data'], choices['choices'])
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basic_portfolio(choices['combined_df'])
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display_heat_map(choices['data'],choices['choices'])
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#display_portfolio_return(choices['combined_df'], choices['choices'])
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price changes to the benchmark. By using CAPM model, annual expected return and portfolio
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return is calculated. The model results can be found in Appendix A.
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"""
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beta(choices['data'], choices['choices'])
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ER(choices['data'], choices['choices'])
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##### EDIT HERE ##### koi
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st.header('CAPM Model and the Efficient Frontier')
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"""
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CAPM model measures systematic risks, however many of it's functions has unrealistic assumptions and relies heavily on a linear interpretation
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of the risks vs. returns relationship. It is better to use CAPM model in conjunction with the Efficient Frontier to better
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graphically depict volatility (a measure of investment risk) for the defined rate of return. \n
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Below we map the linear Utility function from the CAPM economic model along with the Efficient Frontier
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Each circle depicted above is a variation of the portfolio with the same input assest, only different weights.
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Portfolios with higher volatilities has a yellower shade of hue, while portfolios with a higher return has a bigger radius. \n
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As you input different porfolio assets, take note of how diversification can improve a portfolio's risk versus reward profile.
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"""
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ef_viz(choices['data'],choices['choices'])
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##### #####
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basic_portfolio(choices['combined_df'])
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display_heat_map(choices['data'],choices['choices'])
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#display_portfolio_return(choices['combined_df'], choices['choices'])
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