Portfolio Optimization App Creation

Sun, 23 Mar 2025 18:36:09 GMT
User

create a streamlit app for mean-variance optimization. The user should input the number of risky assets and then their names. The app should then provide labeled input cells for expected returns and the covariance matrix. The user should also input the risk-free rate. The app should compute and output the tangency portfolio. It should also compute the minimum risk portfolio for a range of expected return targets requiring weights to sum to 1. It should create a plotly interactive plot showing the means and standard deviations of the assets, the efficient frontier of all risky assets, the tangency portfolio, and the capital allocation line. The hover data should show the weights of the risky assets.

Sun, 23 Mar 2025 18:03:50 GMT
J
Julius

I'll help you create a Streamlit app for mean-variance optimization. We'll use numpy for calculations, plotly for interactive visualization, and streamlit for the interface.

Possibly forgot to install the 'streamlit' module.

Python

This code snippet defines a Streamlit application that allows users to input asset data and perform portfolio optimization using the efficient frontier and tangency portfolio concepts.
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---------------------------------------------------------------------------
ModuleNotFoundError                       Traceback (most recent call last)
Cell In[3], line 2
      1 # Create streamlit app for portfolio optimization
----> 2 import streamlit as st
      3 import numpy as np
      4 import plotly.graph_objects as go

ModuleNotFoundError: No module named 'streamlit'
Also, evaluate what went wrong and consider options for how to fix it. Break the execution up into cell blocks.

Let me install the required packages first and then create the app.

Python

This code snippet installs the Streamlit and Plotly packages using pip.
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Python

This code snippet defines a Streamlit application that allows users to input asset data and perform portfolio optimization using the Sharpe ratio and efficient frontier calculations.
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I've created a Streamlit app for portfolio optimization and saved it as 'portfolio_optimizer.py'. Streamlit app saved as portfolio_optimizer.py

The app includes all the requested features:

  • Input for number of risky assets and their names
  • Input fields for expected returns and covariance matrix
  • Risk-free rate input
  • Calculation of the tangency portfolio
  • Computation of the minimum risk portfolio for various return targets
  • Interactive Plotly plot showing:
    • Individual assets
    • Efficient frontier
    • Tangency portfolio
    • Capital allocation line
    • Hover data with portfolio weights

To run the app:

  1. Download the file from https://julius.ai/files/portfolio_optimizer.py
  2. Open a terminal in the directory containing the file
  3. Run the command: streamlit run portfolio_optimizer.py

The app will open in your default web browser. You can then:

  1. Enter the number of assets
  2. Input asset names
  3. Provide expected returns
  4. Fill in the covariance matrix
  5. Set the risk-free rate
  6. Click "Calculate Optimal Portfolios" to see the results

The interactive plot will allow you to explore different portfolios by hovering over the efficient frontier and seeing the corresponding weights for each portfolio.

The portfolio optimization app has been created and saved. You can access it at https://julius.ai/files/portfolio_optimizer.py

What would you like to explore or modify in the portfolio optimization app?

Sun, 23 Mar 2025 18:05:59 GMT