subject: The Fundamentals Of Algorithmic Trading Practices [print this page] Technical mathematical models used to decide on buying and/or selling in the financial market are used by a process known as algorithmic trading. It entails the application of risk management tools that have been formulated to strategize market trends and estimate the risk involved in each trade. Investors who develop a solid awareness of this method are able to make more accurate predictions of future market behavior. Investors can skip analyzing the data themselves by employing this easy-to-interpret information concerning the market.
The two primary aspects of a trading algorithm are sequences of steps establishing when to trade and how to trade. The deciding factor of when to trade in the market is watching and finding opportunities. How to trade is a question of placing and managing your orders so as to maximize your potential gain.
The formulas in algorithmic trading are created according to real-time analysis, based on data in the market's history. The most prevalent algorithmic formulas are known as GAATS and represent the seven proprietary algorithms that have been developed. To develop a useful strategy requires an iterative process of development and testing, which can take weeks to months, even for the most skilled marketers. A technology called genetic algorithms is used to speed up the process.
A genetic algorithm is a simulated market which generates artificial data that closely mirrors the real markets using a statistical analysis of past market data. Determined by the stock price and price increments during a certain time span, a market simulator will make data for you from a random number. In such a way, you will be able to test a market prior to putting real money in and potentially losing it.
There have been some people, mostly brokers and traders who are worried about being replaced by computers, who have argued against the use of algorithmic trading. Claiming that these protocols could fall apart when stress is present, there are those who have insisted that the modeling utilized in algorithmic trading has its limits.
Algorithmic trading is most widely used by sizable institutional investors due to the huge amount of shares they buy each day. A well-designed algorithm means that such large-scale investors can buy or sell at the best available price without substantially altering the stock's price or raising their own expenditures.
