Can be installed using pip install or conda install for Anaconda environment

• Python 3.7
• Libraries
  • numpy (1.17.0)
  • pandas (0.24.2)
  • scipy (1.3.1)
  • matplotlib (3.1.1)

Steps to be followed:

• Data: Current implementation is based on data obtained from Yahoo Finance. Convert your data to the specific format and place under data folder.
• Baseline: Update BASE_LINE in optimizer.ipynb to compare the portfolio's performance
• Stocks: Update SYMBOLS in optimizer.ipynb to relevant stocks in the portfolio
• Allocation: Update allocations in optimizer.ipynb to the allocation of stocks in the portfolio (must sum to 1)
• Sampling Frequency: Update sampling_freq in optimizer.ipynb. Currently, configured for daily, use weekly: 52, monthly: 12
• Risk Free Rate: Update risk_free_rate (must be in percentage) in optimizer.ipynb. Configure it with the minimum return rate, if the amount was invested in fixed returns options such as savings account/fixed deposits etc.
• Start and End Date: Update start and end date in optimizer.ipynb.
• Initial Investment: Update initial_investment in optimizer.ipynb.