Trading system

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[edit] Overview

In electronic financial markets, trading system, also known as algorithmic trading, is the use of computer programs for entering trading orders with the computer algorithm deciding on certain aspects of the order such as the timing, price, quantity of order. It is widely used by hedge funds, pension funds, mutual funds, and other institutional traders to divide up a large trade into several smaller trades in order to manage market impact, opportunity cost, and risk. It is also used by hedge funds and similar traders to make the decision to initiate orders based on information that is received electronically, before human traders are even aware of the information.

Computerization of the order flow in financial markets began in the early 1970s with some landmarks being the introduction of the New York Stock Exchange’s “designated order turnaround” system.

Recent years have seen a surge in the growth of automated trading. The global electronic markets continue to attract more volume, as firms worldwide utilise trading automation at an increasing rate.

This allows traders to deploy complex strategies that would be impossible to execute manually.

Market data rates are skyrocketing as a result of automated electronic trading. In the last 10 years, market data has grown by roughly two orders of magnitude, requiring ongoing upgrades of data networks and computing systems.

And this growth is continuing, so today's data infrastructures will require persistent improvement and expansion to keep up with constantly increasing market data volume.

Technologies devised for automated trading are making markets more interdependent. As bigger data pipes and faster computers are increasingly deployed by trading firms to monitor real-time prices across multiple markets, the window of time required to capture inter-market arbitrage opportunities is diminishing.

Today, using information and trading platforms has become a de facto requirement for successful trading in the financial markets. Their advantages as compared to conventional trading schemes include, for example, an unprecedented speed of processing and delivery of information to end users, the level of integration with data providers, and a wide array of built-in technical analysis instruments.

At the same time, an investor opening an account with a brokerage firm simply cannot simultaneously manage the real-time analysis and trade in more than 4-6 financial instruments in several markets 24 hours 7 days a week. This brings about the need to employ automatic trading systems in the form of runtime environment with client and server parts and the programs to control these systems (scripts).

Various software components embrace the entire target sector of the market from analytics and forecasting to complex trade and administration. The components of a trading platform provide its clients—brokers, dealers, traders, financial analysts and advisors—just the service they need at the very moment they need it, from immediate round-the-clock access to information of concern by means of mobile devices, to multi-move trading operations in the major client terminal.

[edit] Trading System Examples

One such example of a trading system is the ACD Method, a quantitative application developed by Mark Fisher, a professional trader and founder of MBF Clearing Corp., one of the largest clearing firms on the New York Mercantile Exchange, and supports the trading of several hundred exchange members. Fisher is well known for his book The Logical Trader: A Method to the Madness, which is the dissertation to The ACD Method, a quantitative systems developed at the Wharton School of Business, and is based on extensive back testing that analyzes opening price trading ranges for stocks and futures contracts. More information at http://www.thelogicaltrader.net.

Another example is POSIT[1] or POrtfolio System for Intstitutional Trading, an electronic trading system serving institutional traders. It is run by the Investment Technology Group (NYSE:ITG). It attempts to match buy and sell orders between larger traders. POSIT is a type of crossing system, where a broker acts as agent on both the buy side and sell side of a given transaction. If the broker has a buy order and an equivalent sell order, he/she can "cross" the orders. This is a common situation in the case of large orders.