NEW YORK (Reuters) - Snipes, sniffers and guerrillas are lurking in the stock market. So are dark pools, daggers, boxers, slicers and nighthawks.
Reflecting the nature of the struggle for ascendance in algorithmic trading — or simply, the algo wars — investment banks and hedge funds have been giving military monikers to their increasingly complex and machine-driven trading strategies.
The battlefield names may well be suitable, given that many of the strategies seek to disguise a trader’s real intentions, detect the strategies of rivals and take advantage of them, or capture fleeting anomalies in market behavior.
This isn’t just a war game relevant to ultra-rich investors in hedge funds, or proprietary traders playing with their banks’ money.
Increasingly mainstream mutual funds and pension funds are using such automated programs. And that means even mom-and-pop investors may be gaining some advantages.
The main ones are the possibility of better prices for transactions, as there is less transparency when a big order hits the market, and lower costs, as a bank of computers eventually becomes less expensive than a bank of traders.
“These algorithms are designed to help get an order done without creating market impact,” said Adam Sussman, senior analyst at The Tabb Group, a financial services research and advisory firm.
“You always want to hide your hand and these algorithms give you a way to do that,” he said.
The retail investor who dabbles in the market from home may also need to understand the increasing power of the machine, with many experts predicting such “black box trading” to account for more than half of stock market transactions.
The effects of the algorithmic takeover of trading are already apparent.
It can reduce volatility, as computers constantly push prices back toward the norm, has raised fears of a faster market meltdown on a startling event such as 9/11, and can add to rollercoaster-like share-price movements during the first and last hour of the stock-market trading day.
It also means that humans trying to trade on an event — such as a profit warning — are almost always going to lose out on the initial price moves, however fast their fingers may be on the order button.
Following are some of the best known algorithmic trading techniques and terms:
VWAP — volume weighted average price — is the most basic. It executes a buy order in a stock as close as possible to its historical trading volume in an effort to reduce the trade’s impact on the market.
For example, if over the past three months 10 percent of a stock’s trading volume occurs in the first hour of trading, then a computer with a customer’s buy or sell order will stop trading that order in that hour if the 10 percent level is reached. The rest of the order will be traded in subsequent periods.
The idea is to prevent any appearance of heavier than normal trading activity, which could damage the price at which the order is executed as other traders (whether humans or machines) realize what is happening.
Another basic algorithmic trading technique is time weighted average price, or TWAP. It trades based on the clock, allowing traders to slice a trade up over time, and is most appealing for those investing in a small, illiquid stock where volume analysis makes little sense.
These are employed when an investor “wants to keep up with the volume that’s going on,” said Sussman. “If all of a sudden we see an increased interest in a particular stock, then the algorithm will become more aggressive. And, if there is less trading going on, it becomes less aggressive.”
The technique appeals to momentum investors, the follow-the-money types who want to take advantage of a significant move in a stock.
This algorithm, developed by Credit Suisse, is designed to work orders without signaling the presence of a buyer or seller to the marketplace. In other words, it slices big orders into smaller unobtrusive sizes.
It “uses a variety of trading techniques to disguise its trail,” according to Credit Suisse’s Advanced Execution Services unit, which serves major hedge funds and other buy-side clients.
Guerrilla trades on a wide range of alternative trading networks and is particularly effective in mid-cap and small-cap stocks.
Here’s the verbal equivalent of Guerrilla, for a hypothetical order on Ross Stores: “Sell 150,000 of ROST, not held. Don’t show anything out loud, don’t shop it, don’t lean on it.”
This is another Credit Suisse algorithm, a very aggressive tactic which will trade until it either completes or reaches an investor’s limit price.
“It’s looking at all of the market data and finding ways to very intelligently pick off little pieces here and there,” Sussman said.
According to Credit Suisse, “It never displays a bid or offer and can sniff out hidden liquidity. As a result, it is often a better choice than placing limit orders directly into the market.”
These are used to sniff out algorithmic trading by others and the algorithms being used. The technique aims to find other software at work in the market in the hope that it will pick up trading opportunities — either working with or against the trading flow created by the rivals.
“Sniffers sometimes throw a little bit of an order out waiting to see if someone comes and gets it,” said Sussman. “You’re sort of using it as bait, and if someone hooks on to it, then you try to get more and more of the order.”
Dark pools of liquidity
These are private trading networks — they do not post price quotes — in which buyers and sellers remain anonymous until trades are executed. Orders are matched internally according to software that dissects brokers’ order books looking for better prices than available on the exchanges and public trading networks.
They will record the trade only after it has been privately done.
For example, someone puts in a 1-million-share order to buy IBM into a dark pool and no one knows that it’s there. The order gets filled when other orders come in “as long as they are at the right price and in the right stock,” Sussman said.