Trade Execution

Algorithmic trading is the practice of using programmed strategies to electronically trade orders. This practice is common in most equity, foreign exchange, and exchange-traded derivative markets. As with fixed income, algorithmic execution is mostly limited to trading highly liquid government securities.

Principal trades involve the executing broker assuming all or part of the risk (which is priced into the quoted spread). In agency trades, the broker finds the other side but only acts as an agent, leaving the risk of trading the order to the trader.

Some examples of potential trading venues for algorithmic trading include:

• Electronic trading includes alternatives.
• Multilateral trading venues (ATS or MTF).
• Direct market access (DMA).
• Dark pools.

An exchange that uses DMAs allows all participants to see and manipulate the order book of the exchange. All limit orders that have not yet been filled will appear in the order book, as well as market orders that will be filled.

The term high-touch refers to the degree of human intervention necessary. High-touch algorithms require more human oversight, while the opposite would be fully automated algorithms.

Two Main Types of Algorithms

Execution Algorithms are algorithms that take a portfolio manager's decisions as input and decide how to best realize those decisions consistent with the objective of the fund.

Profit-seeking Algorithms are algorithms that make their own buy and sell decisions and then additionally decide how to best implement those within the market.

Algorithm Classifications

Scheduled (POV, VWAP, TWAP)

A scheduled algorithm contains a set of instructions to transact in a security at specific times. This program will be based on historical trading volumes and important time periods. Scheduled algorithms are:

• Most appropriate when traders do not have expectations of large/adverse price movement during the trade window.
• Used by traders who have greater risk tolerance for longer execution time periods.
• Prioritized to minimizing market impact.
• Suitable for small orders, liquid securities, or risk-balanced baskets, where trading all orders at the same pace will maintain risk balance.

Participation algorithms (POV's) will increase their own transactions along with increasing market liquidity and vice versa. Often there will be a specified percentage set on daily market volume, and the algorithm will continue to trade up to this point (such as 5% of market volume). One potential issue with POV’s is that they may incur higher trading costs by continuing to buy as prices move higher and vice versa.

VWAP algorithms create segments of time-based on historical intra-day volume. Loosely speaking, the English instructions would read something like: “Trade 5,000 shares within one hour of market opening”. These instructions, of course, will need to be further translated for the machine using a programming language.

TWAP strategies are similar to VWAP strategies except that they use an equal-weighted time schedule rather than one based on volumes.

If a normal trading day is 8 hours, and 80 shares are to be traded, the algorithm will transact 10 shares per hour, regardless of volume.

Liquidity Seeking

These algorithms are appropriate for trading securities that are less liquid and thinly traded or when liquidity is non-constant. Much like POV scheduled algorithms, liquidity-seeking algorithms will trade along with market liquidity. These algorithms may use dark pools or alternative markets and often trade with offsetting orders when they deem liquidity to be high and prices to be favorable.

Arrival Price

Arrival price algorithms seek to maintain the decision price. That is, whether they are under or over, arrival price algorithms deviate as little as possible from the price of the stock at the time when the manager decides to trade. This often means the strategy will trade more aggressively at market opening. They can be most useful when an adverse price movement is expected to come, using the arrival price as the anchor point to reduce price slippage or capture the trade's alpha before it disappears.

Dark Strategies

Dark strategies refer to a set of algorithms that operate in non-transparent markets. This is designed to limit information leakage and can be useful for securities that are relatively illiquid. The downside of using dark channels for trading is the higher probability that orders may go unfilled due to the smaller amount of potential trading partners.

Smart Order Routers (SORs)

SORs continuously watch both dark and lit trading venues in real time to find the best place to execute the trade successfully. SORs can work with both market and limit orders. They're typically used when the order size is similar to existing market orders or recently closed ones.

However, the ideal venue isn't always apparent. Sometimes, multiple venues may have the same limit price. In such cases, the SOR will select the venue with the highest likelihood of success and direct the order there.

Market orders

Smart Order Routers (SORs) are employed for relatively small orders that won’t significantly impact the market if executed as market orders. They are particularly suitable for orders that demand immediate execution due to impending price shifts, heightened risk aversion by portfolio managers or traders, or exceptionally high-risk levels.

SORs are also useful for marketable orders when the market is highly dynamic, preventing traders from manually selecting venues that might result in suboptimal executions due to rapidly changing conditions.

Limit orders

Smart Order Routers (SORs) are also employed for relatively small orders where placing a limit order wouldn’t disclose information or significantly impact prices.

They are suitable for stocks actively traded on multiple markets when it’s not clear which venues the order should be directed to, especially when several venues are offering orders at the trader’s limit price. SORs help optimize order execution in these situations.

Question

Which of the following algorithms is least likely to consider higher trading volumes?

1. Volume-Weighted Average Price.
2. Liquidity seeking.
3. Time-Weighted Average Price.

Solution

The correct answer is C.

Time-Weighted Average Price (TWAP) is an algorithmic trading strategy that aims to execute trades evenly over a specified time period, regardless of trading volumes. It divides the total trading volume into smaller, equal-sized orders to be executed at regular intervals throughout the trading day. TWAP does not prioritize or consider higher trading volumes, and it focuses on distributing trades evenly over time.

A is incorrect. Volume-Weighted Average Price (VWAP) is an algorithm that takes into account trading volumes. It calculates the average price at which a security was traded over a specific time frame, with each trade’s contribution to the average weighted by its trading volume. VWAP is specifically designed to consider trading volumes.

B is incorrect. Liquidity-seeking algorithms are designed to actively seek out and interact with higher trading volumes in the market to complete a trade efficiently. These algorithms aim to minimize market impact and achieve better prices by accessing available liquidity, which often involves considering higher trading volumes.

Portfolio Management Pathway Volume 2: Learning Module 8: Trade Strategy and Execution; Los 8(e) Describe factors that typically determine the selection of a trading algorithm class