ITG has recently introduced more real-time functionality into its implementation shortfall algorithm, designed for buysiders who trade portfolios.
The latest version of the software, Dynamic Implementation Shortfall Algorithm 2.0 or DIS 2.0, adjusts its execution strategy in real-time as the market changes. That means, in effect, it slows or speeds up its trading as needed. The ability to change speeds automatically allows the algo to more effectively manage risk while executing trades, Jeff Bacidore, ITG managing director and head of algorithmic trading told Traders Magazine.
“This version has new built in features; it is designed for a trader to load up a list and hit “go” and get an intuitive outcome,” Bacidore said.
Keeping track of the many securities in a portfolio, or program, trade and their behavior during the trading day is extremely difficult. A list can have upwards of hundreds of stocks. Tracking these individual stocks can demand a buyside trader’s attention the entire day, without him ever getting a trade done. This holds especially true when the portfolio is being re-adjusted as part of a rebalance or a change in the index that a portfolio is tracking.
DIS was created to execute portfolio trades in a coordinated, automated cost-effective manner.
Bacidore said the latest iteration offers users a better way to trade the portfolio in the most cost- and risk-effective manner, especially when handling imbalanced and illiquid portfolio trades. The new 2.0 version incorporates both intraday trade and price information. The old version did not. This allows the revamped algorithm to better balance cost and risk when formulating its trading strategy and automatically update the speed of execution when trading.
In the algo’s first iteration, DIS required the buyside trader to input more information, such as cash constraints, or how much cash a portfolio is willing to hold at a given time. Also, in the old version, a user had to input some number indicating how fast the algo needed work out any trade imbalances (when the buy orders and sell orders are not equal) on a list, before it would calculate how to trade. The newer version doesn’t need all of this data to be entered manually by the trader. The algo can determine the optimal strategy, Bacidore added.
“The algo is meant to be aware of market conditions and the individual stocks in the list,” Bacidore said. “For example, the algo is programmed to behave differently depending on the market environment. It will trade a given list much differently at 9:30am than it will at noon. It will also trade a chunkier, imbalanced list much differently than a liquid, balanced list but in a way that is intuitive to the trader.”
Implementation shortfall algorithms try to minimize slippage in stock prices. That means they are programmed to ensure that the price at which a trade gets done is as close as possible to the price when the trader made the decision to trade the stock.
In this case in DIS, it determines the best time to execute multiple stocks on a list. It updates this information in real-time, so the buyside trader vis-a-vis the algo can trade his list automatically and more efficiently.
Bacidore said that while this is difficult enough when trading a single stock, it can be positively onerous when trading a basket of stocks. Thus, the algo simplifies the trader’s workflow.
