Algorithmic trading is a trading style that allows firms to electronically determine the execution time and route orders to different electronic exchanges, therefore, providing a tool for faster, cheaper, and electronic execution of orders. Algorithmic programs analyze orders with ticker data to determine when to execute. Besides electronically executing orders, those programs also determine eligibility of the orders for electronic execution in a particular exchange.
Algorithmic programs use different methodologies to determine when a order can have the best execution. The process involves use of software and mathematical models. There are many different Algorithmic program models. Some of the well known models are:
VWAP (Volume Weighted Average Price)
TWAP (Trade Weighted Average Price)
Currently sell side companies are providing such models to route and determine execution time of an order that allows buy side companies more control over their order executions. Such definition of Algorithmic trading is narrow and only represents order routing algorithms. However, in the larger trading context, â€œAlgorithmic Tradingâ€ shall define algorithmically generating orders as well as execution.
â€œAlgorithmic Tradingâ€ shall be defined as define, decide, and execute orders for a portfolio that automates order generation and execution in real-time. In this definition the order generation is quantitative trading. We can think of â€œQuantitative Tradingâ€ as a tool to determine orders algorithmically, and execution methods as current algorithmic trading.
Currently there are many methodologies besides quantitative trading in investment management industry. An investment house that uses quantitative methods can hugely improve their performance using algorithmic trading in order generation as well as order execution. The currently quantitative workflow will not change but the new â€œAlgorithmic Tradingâ€ platform will hugely reduce the time between order generation and it execution by streamlining the applications.
In Algorithmic Trading environment, order generation and portfolio optimization can be done together to provide near real-time order generation and execution. Such environment shall improve the time to market, trade cost, and ultimately return on the portfolio.
Similarly, an investment house uses many mathematical tools in quantitative models that can be evaluated using such algorithmic trading environments. A portfolio manager will have continuous evaluation of his/her portfolio in real-time that incorporate market changes allowing him/her to make adjustment to portfolio at any given point in the process. Such continuous evaluation of a portfolio or instrument can be done by using simulation techniques and use of â€œwhat-ifâ€ analysis.
Algorithmic Trading is an evolving field that is providing opportunity to refine and redefine algorithmic trading environment for better, faster, and cheaper order generation and execution to improve performance of a portfolio; therefore contributing to the bottom-line of the investment house.