Update app.py

app.py

@@ -22,6 +22,16 @@ from sharp_ratio import(
     preprocess,
     sharp_ratio_func
 )
+
+def risk_str(num):
+    if num >=5 and num <15:
+        return 'Low Risk Aversion'
+    elif num >= 15 and num <25:
+        return 'Medium Risk Aversion'
+    elif num >= 25 and num <=35:
+        return 'High Rish Aversion'
+#### Koi
+        
 def load_heading():
     """The function that displays the heading.
         Provides instructions to the user
@@ -142,16 +152,33 @@ return is calculated. The model results can be found in Appendix A.
         ##### EDIT HERE ##### koi
         st.header('CAPM Model and the Efficient Frontier')
         """
-    CAPM model measures systematic risks, however many of it's functions has unrealistic assumptions and relies heavily on a linear interpretation 
+    CAPM model measures systematic risks, however many of it's functions have unrealistic assumptions and rely heavily on a linear interpretation 
     of the risks vs. returns relationship. It is better to use CAPM model in conjunction with the Efficient Frontier to better
     graphically depict volatility (a measure of investment risk) for the defined rate of return. \n
     Below we map the linear Utility function from the CAPM economic model along with the Efficient Frontier
-    Each circle depicted above is a variation of the portfolio with the same input assest, only different weights. 
-    Portfolios with higher volatilities has a yellower shade of hue, while portfolios with a higher return has a bigger radius. \n
+    Each circle depicted above is a variation of the portfolio with the same input asset, only different weights. 
+    Portfolios with higher volatilities have a yellower shade of hue, while portfolios with a higher return have a larger radius. \n
     As you input different porfolio assets, take note of how diversification can improve a portfolio's risk versus reward profile.
         """
         ef_viz(choices['data'],choices['choices'])
-        ##### #####
+        """
+    There are in fact two components of the Efficient Frontier: the Efficient Frontier curve itself and the Minimum Variance Frontier. 
+    The lower curve, which is also the Minimum Variance Frontier will contain assets in the portfolio 
+    that has the lowest volatility. If our portfolio contains "safer" assets such as Governmental Bonds, the further to the right 
+    of the lower curve we will see a portfolio that contains only these "safe" assets, the portfolios on 
+    this curve, in theory, will have diminishing returns.\n
+    The upper curve, which is also the Efficient Frontier, contains portfolios that have marginally increasing returns as the risks 
+    increases. In theory, we want to pick a portfolio on this curve, as these portfolios contain more balanced weights of assets 
+    with acceptable trade-offs between risks and returns. \n
+    If an investor is more comfortable with investment risks, they can pick a portfolio on the right side of the Efficient Frontier. 
+    Whereas, a conservative investor might want to pick a portfolio from the left side of the Efficient Frontier. \n
+    Take notes of the assets' Betas and how that changes the shape of the curve as well. \n 
+    How does the shape of the curve change when 
+    the assets are of similar Beta vs when they are all different?\n 
+    Note the behavior of the curve when the portfolio contains only assets with Betas higher than 1 vs. when Betas are lower than 1.\n  
+
+        """
+        ##### ##### Koi
         basic_portfolio(choices['combined_df'])
         display_heat_map(choices['data'],choices['choices'])
         #display_portfolio_return(choices['combined_df'], choices['choices'])