Update app.py

app.py

@@ -43,17 +43,26 @@ st.write("""
 This tool estimates potential price movements of a selected stock or cryptocurrency over a specified time horizon using Monte Carlo Simulations.
 The estimates are based on historical volatility and the implied volatility derived from the Black-Scholes-Merton model. 
 You can adjust the time horizon, number of simulations, and volatility measures to explore different scenarios of price dynamics. 
-To read more about the methodologies, visit [this link](https://entreprenerdly.com/price-movements-with-historical-implied-volatility-monte-carlo/).
 """)
 
-# Adding LaTeX formatted formulas
-st.latex(r'''
-P_t = P_0 \times e^{(\mu - \frac{1}{2} \sigma^2) \times t + \sigma \times \sqrt{t} \times Z}
-''')
+with st.sidebar.expander("Click here for more information about the methodology", expanded=True):
 
-st.markdown("""
-**Monte Carlo Simulation Inputs** are **(Pt)**: Estimated asset price at time (t). **(P0)**: Current asset price. **(μ)**: Mean of the log returns. **(σ)**: Standard deviation of the log returns, representing historical volatility. **(t)**: Time horizon in days. **(Z)**: Random variable from the standard normal distribution.
-""")
+    # Adding LaTeX formatted formulas
+    st.latex(r'''
+    P_t = P_0 \times e^{(\mu - \frac{1}{2} \sigma^2) \times t + \sigma \times \sqrt{t} \times Z}
+    ''')
+    
+    st.markdown("""
+    **Monte Carlo Simulation Inputs** are 
+    - **(Pt)**: Estimated asset price at time (t). 
+    - **(P0)**: Current asset price. 
+    - **(μ)**: Mean of the log returns. 
+    - **(σ)**: Standard deviation of the log returns, representing historical volatility. - 
+    - **(t)**: Time horizon in days. 
+    - **(Z)**: Random variable from the standard normal distribution.
+    """)
+
+    st.write("""To read more about the methodologies, visit [this link](https://entreprenerdly.com/price-movements-with-historical-implied-volatility-monte-carlo/).""")
 
 st.write(f"""
 These simulations project multiple potential future price paths for the asset based on the volatility models described.