Algorithmic trading, used mostly by institutional investors and large, utilizes advanced mathematical tools developed by traders to forecast the most probable moves in the markets, and to initiate trades.
Algorithmic trading uses specially designed computer programs that, thanks to sophisticated algorithms developed by specialists, support the decision making process in financial markets to achieve maximum profit. Generally, the more unique and innovative the approach implemented by a given tool, the greater the odds of achieving extraordinary profits. If trading gold is done using sophisticated, automated algorithms, then this trading would be called algorithmic gold trading.
There are many other names for algorithmic trading, including: automated trading, algo trading, black-box trading or robo trading.
Algorithms utilize very advanced mathematical/statistical models. Specially designed tools take into consideration many aspects of an order such as timing, price and quantity. They also search for relationships or regularities that occur in the market. Relationships and regularities are then used to forecast the most likely or probable situation in the market for the next period. Algorithmic trading is so reliable that some highly developed programs make their own decisions and initiate orders without human intervention.
There is also a special class of algorithmic trading called "high-frequency trading" (HFT), in which computers make elaborate decisions to initiate orders based on information that is received electronically, before human traders are capable of processing the information they observe. That means that while the human is starting to read data, the decision making process has already been conducted and an order has already been placed. Algorithmic Trading is widely used by pension funds, mutual funds, as well as market makers and some hedge funds and other institutional traders. Due to its sophistication, algorithmic trading is used mainly by professionals. There are few algorithmic trading programs for smaller users. However, this is changing and this innovative method is now being developed for individual investors.
We should keep in mind that algorithms are just programs constructed by humans. They can only use data that is taken into consideration by the programmer and cannot learn (with a few small exceptions). There is a risk that an algorithm wouldn’t notice some important data because it was not programmed to do so. We believe that algorithms are very helpful but the best results can be achieved only when they are supported by human input in the decision making process. Algorithmic programs can provide necessary data and forecasts but the last word should belong to humans.
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