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2020 Curriculum CFA Program Level III Portfolio Management and Wealth Planning

Trade Strategy and Execution

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Introduction

This reading discusses trading and execution from a portfolio manager’s perspective. The reading covers a broad range of topics related to trade strategy selection and implementation and trade cost measurement and evaluation. Growth in electronic trading has led to increased automation in trading, including the use of algorithmic trading and machine learning to optimize trade strategy and execution. Various markets, including equities, fixed income, derivatives, and foreign exchange, are examined. Adequate trading processes and procedures are also discussed from a regulatory and governance perspective.

Portfolio managers need to work closely with traders to determine the most appropriate trading strategy given their motivation for trading, risk aversion, trade urgency, and other factors, such as order characteristics and market conditions. Trade execution should be well integrated with the portfolio management process, and although trading strategies will vary on the basis of market and security type, all trade activity should be evaluated for execution quality and to assess broker and trade venue performance consistent with the fund’s objectives. Additionally, firms should have proper documentation of trade procedures in place to meet regulatory and governance standards.

This reading is organized as follows: Section 2 discusses portfolio manager motivations to trade. Section 3 discusses inputs to trade strategy selection and the trade strategy selection process. Section 4 covers the range of trade implementation choices and trading algorithms and provides a comparison of various markets. Section 5 explains how trade costs are measured and how to evaluate trade execution. Section 6 provides guidance on evaluating a firm’s trading procedures for good governance practices. Section 7 concludes and summarizes the reading. 

Learning Outcomes

The member should be able to:

  • discuss motivations to trade and how they relate to trading strategy;
  • discuss inputs to the selection of a trading strategy;

  • compare benchmarks for trade execution;

  • select and justify a trading strategy (given relevant facts);

  • describe factors that typically determine the selection of a trading algorithm class;

  • contrast key characteristics of the following markets in relation to trade implementation: equity, fixed income, options and futures, OTC derivatives, and spot currency;

  • explain how trade costs are measured and determine the cost of a trade;

  • evaluate the execution of a trade;

  • evaluate a firm’s trading procedures, including processes, disclosures, and record keeping with respect to good governance. 

Summary

  • Portfolio manager motivations to trade include profit seeking, risk management (hedging), liquidity driven (fund flows), and corporate actions and index reconstitutions.

  • Managers following a short-term alpha-driven strategy will trade with greater urgency to realize alpha before it dissipates (decays). Managers following a longer-term strategy will trade with less urgency if alpha decay is expected to be slower.

  • Trading is required to keep portfolios at targeted risk levels or risk exposures, to hedge risks that may be outside a portfolio manager’s investment objectives or that the portfolio manager does not have an investment view on.

  • Trading may be liquidity driven resulting from client activity or index reconstitutions. In these cases, managers typically trade using end-of-day closing prices because these prices are used for fund and benchmark valuation.

  • Inputs affecting trade strategy selection include the following types: order related, security related, market related, and user based.

  • Order characteristics include the side (or trade direction) and size of an order. Percentage of average daily volume is a standardized measure used in trading that indicates what order size can realistically be traded. Large trades are generally traded over longer time horizons to minimize market impact.

  • Security characteristics include security type, short-term (trade) alpha, security price volatility, and a security’s liquidity profile.

  • Market conditions at the time of trading (intraday trading volumes, bid–ask spreads, and security and market volatility) should be incorporated into trade strategy since they can differ from anticipated conditions.

  • Market volatility and liquidity vary over time, and liquidity considerations may differ substantially during periods of crisis.

  • Individuals with higher levels of risk aversion are more concerned with market risk and tend to trade with greater urgency.

  • Market impact is the adverse price impact in a security caused from trading an order and can represent one of the largest costs in trading.

  • Execution risk is the adverse price impact resulting from a change in the fundamental value of the security and is often proxied by price volatility.

  • Reference price benchmarks inform order trading prices and include pre-trade, intraday, post-trade, and price target benchmarks.

  • Managers seeking short-term alpha will use pre-trade benchmarks, such as the arrival price, when they wish to transact close to current market prices (greater trade urgency).

  • Managers without views on short-term price movements who wish to participate in volumes over the execution horizon typically use an intraday benchmark, such as VWAP or TWAP.

  • Managers of index funds or funds whose valuation is calculated using closing prices typically select the closing price post-trade benchmark to minimize fund risk and tracking error.

  • The primary goal of a trading strategy is to balance the expected costs, risks, and alpha associated with trading the order in a manner consistent with the portfolio manager’s trading objectives, risk aversion, and other known constraints. 

  • Execution algorithms can be classified into the following types: scheduled, liquidity seeking, arrival price, dark aggregators, and smart order routers.

  • Equities are traded on exchanges and other multilateral trading venues. Algorithmic trading is common, and most trades are electronic, except for very large trades and trades in illiquid securities.

  • Fixed-income securities are generally traded not on exchanges but in a bilateral, dealer-centric market structure where dealers make markets in the securities. The majority of fixed-income securities are relatively illiquid, especially if they have been issued in prior periods, so-called off-the-run bonds.

  • Most of the trading volume in exchange-traded derivatives is concentrated in futures. Electronic trading is pervasive, and algorithmic trading is growing.

  • OTC derivative markets have historically been opaque, with little public data about prices, trade sizes, and structure details. In recent years, regulators have been placing pressure on OTC markets to introduce central clearing facilities and to display trades publicly in an attempt to increase contract standardization and price discovery and reduce counterparty risk.

  • There is no exchange or centralized clearing place for the majority of spot currency trades. Spot currency markets consist of a number of electronic venues and broker markets. The currency market is entirely an OTC market.

  • The implementation shortfall measure is the standard for measuring the total cost of the trade. IS compares a portfolio’s actual return with its paper return (where transactions are based on decision price).

  • The IS attribution decomposes total trade cost into its delay, execution, and opportunity cost components.

  • Delay cost is the cost associated with not submitting the order to the market at the time of the portfolio manager’s investment decision.

  • Execution cost is the cost due to the buying and/or selling pressure of the portfolio manager and corresponding market risk.

  • Opportunity cost is the cost due to not being able to execute all shares of the order because of adverse price movement or insufficient liquidity.

  • Trade evaluation measures the execution quality of the trade and the performance of the trader, broker, and/or algorithm used.

  • Various techniques measure trade cost execution using different benchmarks (pre-trade, intraday, and post-trade).

  • Trade cost analysis enables investors to better manage trading costs and understand where trading activities can be improved through the use of appropriate trading partners and venues.

  • Major regulators mandate that asset managers have in place a trade policy document that clearly and comprehensively articulates a firm’s trading policies and escalation procedures.

  • The objective of a trade policy is to ensure the asset manager’s execution and order-handling procedures are in line with their fiduciary duty owed to clients for best execution.

  • A trade policy document needs to incorporate the following key aspects: meaning of best execution, factors determining the optimal order execution approach, handling trading errors, listing of eligible brokers and execution venues, and a process to monitor execution arrangements. 

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