In this chapter, we examined how to combine combinations of assets into a portfolio and how to model those portfolios using pandas objects. Using a portfolio, we examined how to calculate the overall risk involved in the portfolio, and learned how we can use negatively correlated assets to be able to minimize risk.

We then expanded upon this concept of risk minimization, using concepts from modern portfolio theory to be able to determine whether our portfolio represents the best mix of assets to yield the highest return at a specific level of risk. This included calculating the efficiency of a portfolio using the Sharpe ratio, and then using optimization tools from SciPy to determine the optimum allocation of instruments in the portfolio.

In closing, we went on a significant tour of using pandas to perform various tasks related to finance. We touched on a number of the features built directly into pandas to be able to model and manipulate financial data, particularly using time-series...