Deploy Strategies to a Live Environment

In Chapter 10, Set up the Interactive Brokers Python API, and Chapter 11, Manage Orders, Positions, and Portfolios with the IB API, we set the stage to begin deploying algorithmic trading strategies into a live (or paper trading) environment. Before we get there, we need two more critical pieces of the algorithmic trading puzzle: risk and performance metrics and more sophisticated order strategies that allow us to build and rebalance asset portfolios. For risk and performance metrics, we will introduce the Empyrical Reloaded library, which generates statistics based on portfolio returns. empyrical-reloaded is the library that provides the performance and risk analytics behind Pyfolio Reloaded, which we learned about in Chapter 9, Assess Backtest Risk and Performance Metrics with Pyfolio. In this chapter, we’ll use empyrical-reloaded to calculate key performance indicators such as the Sharpe ratio, Sortino ratio, and the maximum drawdown...