Algorithmic trading or algorithm trading software is something relatively new to Forex, as trading the Forex market is itself a relatively new trading platform. An automated sell program was implemented to slice a larger order of E-mini S&P 500 contracts, a stock market index futures contract traded on the Chicago Mercantile Exchange's Globex electronic trading platform, in to several smaller orders to minimize market impact.
Computer algorithms encompass the whole trading process—buy side (traditional asset managers and hedge funds) as well as sell side institutions (banks, brokers, and broker-dealers) have found their business significantly migrated to an information systems-driven area where trading is done with minimum human intervention.



That said, once it's well developed, you are letting your bot trade on your behalf as if you were trading manually, and now you don't need to monitor the markets and you can also monitor more stocks at the same time without any emotions affecting your trade execution, which is very compelling.
Richard Balarkas, CEO of Instinet Europe, an institutional brokerage firm, draws a dark future for human intermediaries: It algorithmic trading signaled the death of the dealer that just outsourced all risk and responsibility for the trade to the broker and heralded the arrival of the buy-side trader that could take full control of the trade and be a more discerning buyer of sell-side services” ( Trade News 2009 ).

Algorithmic trading not only has altered the traditional relation between investors and their market-access intermediaries but also has caused a change in the traders' focus as the invention of the telephone did in 1876 for communication between people.
The consequence of these developments has been an escalation in market volatility, an increase in unhedgeable catastrophic risk, and thus a decrease in risk-adjusted returns (if one truly accounted for catastrophic risk), all resulting in what I would argue is an unsustainable overweight in the overall market's portfolio away from fundamental investing into short-term trading.

In addition to these models, there are a number of other decision making models which can be used in the context of algorithmic trading (and markets in general) to make predictions regarding the direction of security prices or, for quantitative readers, to make predictions regarding the probability of any given move in a securities price.
Nearly 21,000 trades were cancelled on various exchanges because they were deemed erroneous and it caused widespread panic among investors and traders and a 1,000 point drop in the Dow Jones industrial average, the largest single-day decline in Dow Jones history.
Academic literature distinguishes between implicit cost such as market impact or timing costs and explicit costs such as commission or access fees ( Harris 2003 ). Cost-driven algorithms concentrate on both variants in order to minimize overall trading costs.

The HKMA noted various sound practices adopted by the more advanced AIs, such as maintaining two inventories, one for the algorithms implemented strategies algo trading and the other for risk controls, to facilitate the identification of any inconsistencies in the risk controls across the implemented algorithms.
In addition, with the help of new market access models, the buy side has gained more control over the actual trading and order allocation processes and is able to develop and implement its own trading algorithms or use standard software solutions from independent vendors.