Python Quants Tutorial 6 - Portfolio Theory | Refinitiv Developers

It is easy to retrieve historical cross asset data using the Eikon Data API. We show how easy it is to generate statistics for single instruments and for portfolios of instruments. For an example, we use Markovitz’s seminal 1952 paper, ‘Portfolio Selection’ to analyse a portfolio of risky assets using Mean-Variance Portfolio Theory (MVP) and then we derive a minimum volatility portfolio using boundaries and constraints. #Eikon #API #Quant #Python #MachineLearning #DataDevelopers #Refinitiv

- How to retrieve historical data across asset classes via the Eikon Data API
- How to work with such data using Pandas, Plotly and Cufflinks
- Generating statistics for single instruments
- Generating statistics for portfolios
- Simulating portfolio composition
- How to compose and analyze portfolios with regard to their expected return and volatility
- How to construct a Minimum Volatility Portfolio

[jamesmarchetti]

Is this notebook available for us to see?

[melinaballario]

mvp = [(portfolio_volatility(fis, weights),
portfolio_return(fis, weights))
for weights in w]
ValueError: shapes (5, 5) and (2, ) not aligned: 5 (dim 1) != 2 (dim 0)
Could you please help with this error?