Through sponsorship we hope to build and improve our existing Python library for financial markets and potentially add new libraries:

• finmarketpy - backtesting library
• findatapy - for downloading market data from many data sources such as
• chartpy - an easy to use wrapper for Plotly and Matplotlib
• tcapy - transaction cost analysis library

As well as maintaining existing code, here is some functionality we'd love to add to our libraries:

• event based backtesting and execution in finmarketpy
• using vaex in finmarketpy for fast backtesting with high frequency datasets (have partially in closed source)
• add total returns indices for more assets like interest rate swaps
  • at present generates total returns indices for FX spot, FX forwards and FX vanilla options
• add FX options backtester to finmarketpy (have already done total return indices for FX options)
• add functionality to create futures time series series from individual futures contracts (have partially in closed source)
• more data sources for findatapy
• adding bqplot to chartpy
• adding additional asset classes and analytics to tcapy
• adding more support for the cloud (eg. AWS Lambdas for tcapy and for backtesting in finmarketpy)