The product uses IBM Optimization Portfolio Cloud Service based on Markowitz Algorithm. Achieve visualization by Hicharts. Used to predict the optimazed investment portfolio.

Please find attached a Python code in Jupyter Notebook and two csv datafiles. You should run ipynb code on the cloud by registering for free cloud solution such as http://datascientistworkbench.com or by installing Python locally on your computer (for instance Anaconda distribution http://www.anaconda.com/download/).

Provided Python code implements portfolio optimization use case described at https://developer.ibm.com/code/journey/construct-a-socially-responsible-investment-portfolio/ based on Portfolio Optimization service from IBM Cloud https://console.bluemix.net/catalog/services/portfolio-optimization .

You would need to register for IBM Cloud free trial account or can obtain a full one-year access via your university http://ibm.onthehub.com to run services on IBM Cloud.

The investment portfolio optimization is based on Markowits Algorithm, using IBM Optimization Portfolio Cloud Service to realize the algorithm in Python. Using Sequential Least Squares Programming Algorithm(SLSP) for optimization.

Run 'Portfolio_Practice.py' 5 Real stocks optimal portfolio in Tushare Finance based on Markowitz Algorithm. Using Sequential Least Squares Programming Algorithm(SLSP) for optimization.

Ppresen/Pinitial, standardized with 100 histogram of yield distribution

Return, Volatility and Sharp Rate Scatter Plots of 5000 Portfolios Effective Boundary and Red Star is the Sharpe Maximum Portfolio The Weight Distribution of the Portfolio of The Largest Sharp Rate

Using html, javascript, css to develop the product and use web visualization tool Highcharts(Most of the big companies in the world use this to achieve data visualization, including IBM).

You could use the URL below to see.

https://qiyuanma.github.io/Investment-portfolio-optimization/

All the charts are dynamic, It is compatible excellent in PC/Phone/Pad