Algorithmic Trading

Section: Algorithmic Trading and Trade Cost Analysis Estimated study time: 60 minutes Content: Algorithmic trading uses computer programs to execute securities transactions based on pre-defined rules, typically to achieve specific execution objectives with minimal market impact and transaction cost. At CFA Level 2, algorithmic trading is analyzed within the framework of trade cost analysis, market microstructure, and its implications for portfolio performance. Trade execution quality affects portfolio returns directly — the difference between the decision price and the actual execution price compounds over thousands of trades and can significantly erode the returns of active investment strategies. Understanding execution costs is essential for evaluating whether a strategy's gross alpha exceeds its implementation costs. Implementation shortfall (also called the arrival price framework) is the primary metric for measuring total execution costs. Implementation shortfall = (Paper portfolio return - Actual portfolio return) = Opportunity cost + Explicit costs + Market impact costs. More formally: IS = [Actual Execution Price - Decision Price] / Decision Price * Portfolio Value, where the decision price is the price at the time the investment decision was made (often the prior day's close or the time of the order decision). IS captures: (1) explicit costs — commissions and fees; (2) market impact — the price moves against the trader as they trade (buying pressure pushes prices up); (3) delay costs — the price moves against the trader before execution begins; and (4) opportunity costs — the cost of orders that were never executed (the stock moved away before trading began). Algorithmic trading strategies fall into several categories based on their execution objective. VWAP (Volume-Weighted Average Price) algorithms execute trades pro-rata with market volume over a specified period,…