Algorithmic trading Facility in Stock and Commodity Exchanges
Algorithmic Trading Facility (ATF) refers to any software or facility by the use of which, upon the fulfillment of certain specified parameters, without the necessity of manual entry of orders, buy/sell orders are automatically generated and entered by the software/program facility into the Exchange trading system to be matched by the Exchange’s trading system.
Algorithmic trading is a method of executing a large order (too large to fill all at once) using automated pre-programmed trading instructions accounting for variables such as time, price, and volume to send small slices of the order out to the market over time. They were developed so that traders do not need to constantly watch a stock and repeatedly send those slices out manually.Popular platforms for algorithmic trading include MetaTrader, NinjaTrader, IQ Broker, and Quantopian.
Algorithmic trading is not an attempt to make a trading profit. It is simply a way to minimize the cost, market impact and risk in execution of an order. It is widely used by investment banks, pension funds, mutual funds, and hedge funds because these institutional traders need to execute large orders in markets that cannot support all of the size at once.
High-frequency trading (HFT) is a form of algorithmic trading characterized by high turnover and high order-to-trade ratios. Although there is no single definition of HFT, among its key attributes are highly sophisticated algorithms, specialized order types, co-location, very short-term investment horizons, and high cancellation rates for orders. In the U.S., high-frequency trading (HFT) firms represent 2% of all firms operating today, but account for 73% of all equity trading volume.
Dark pools are alternative trading systems that are private in nature—and thus do not interact with public order flow—and seek instead to provide un-displayed liquidity to large blocks of securities. In dark pools trading takes place anonymously, with most orders hidden or “iceberged.” Gamers or “sharks” sniff out large orders by “pinging” small market orders to buy and sell. When several small orders are filled the sharks may have discovered the presence of a large iceberged order.
These algorithms or techniques are commonly given names such as “Stealth” (developed by the Deutsche Bank), “Iceberg”, “Dagger”, “Guerrilla”, “Sniper”, “BASOR” (developed by Quod Financial) and “Sniffer”.
Spoofing, Layering (finance)
It is the act of placing orders to give the impression of wanting to buy or sell shares, without ever having the intention of letting the order execute to temporarily manipulate the market to buy or sell shares at a more favorable price. This is done by creating limit orders outside the current bid or ask price to change the reported price to other market participants. The trader can subsequently place trades based on the artificial change in price, then canceling the limit orders before they are executed.
Quote stuffing is a tactic employed by malicious traders that involves quickly entering and withdrawing large quantities of orders in an attempt to flood the market, thereby gaining an advantage over slower market participants. The rapidly placed and canceled orders cause market data feeds that ordinary investors rely on to delay price quotes while the stuffing is occurring. HFT firms benefit from proprietary, higher-capacity feeds and the most capable, lowest latency infrastructure. Researchers showed high-frequency traders are able to profit by the artificially induced latencies and arbitrage opportunities that result from quote stuffing.
Low latency trading systems
Network-induced latency, a synonym for delay, measured in one-way delay or round-trip time, is normally defined as how much time it takes for a data packet to travel from one point to another. Low latency trading refers to the algorithmic trading systems and network routes used by financial institutions connecting to stock exchanges and electronic communication networks (ECNs) to rapidly execute financial transactions. Most HFT firms depend on low latency execution of their trading strategies. Joel Hasbrouck and Gideon Saar (2013) measure latency based on three components: the time it takes for 1) information to reach the trader, 2) the trader’s algorithms to analyze the information, and 3) the generated action to reach the exchange and get implemented. In a contemporary electronic market, low latency trade processing time was qualified as under 10 milliseconds, and ultra-low latency as under 1 millisecond.
BSE launches algo trading test facility
BSE launched an algorithm trading test facility for investors on its equity and derivatives platform on 18 January 2016. The new service is free-of-cost for market participants. Algorithmic trading or algo trading refers to orders on bourses that are generated using high-frequency, automated execution logic.This service will enable all market participants to test their trading algorithms in equity, equity derivative and currency derivative segments free-of-cost,” BSE said. BSE has also made a provision to generate data analytics reports to check the performance of the strategies.