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Algorithmic Trading

Algorithmic trading (automated trading, black-box trading, or simply something-trading) is the method of using machines programmed to obey a given series of instructions to position a transaction to produce profits at a pace and frequency which is impossible for a human trader.


Any algorithmic trading strategy needs a defined incentive which, in terms of increased earnings or cost reduction, is profitable. The strategies for algorithmic trading obey specified sets of rules and are based on timing, price, quantity or other mathematical models. Any algorithmic trading strategy needs a defined incentive which, in terms of increased earnings or cost reduction, is profitable. The strategies for algorithmic trading obey specified sets of rules and are based on timing, price, quantity or other mathematical models.


Let us consider an example here:

I want to buy 100 shares of X Ltd.

So now I can code a program which executes this standing instruction for me. This instruction has to be related to some index of comparison, let us say, moving averages.


So, my program will buy 100 shares of X Ltd, when its 100-day moving average goes above the 200-day moving average

And sell shares of X Ltd, when its 100-day moving average goes below the 200-day moving average.

This simplifies the work and research needed on the part of the investor as he or she can now rely on a program to make a decision (given a set of instructions).


Algorithmic-trading can be applied in many forms of trading and investment activities:


Mid to long term investors or buy side firms (pension funds, mutual funds, insurance companies) who purchase stocks in large quantities but do not want to influence stocks prices with discrete, large-volume investments.


Short term traders and sell side participants (market makers, speculators, and arbitrageurs)benefit from automated trade execution; in addition, algorithmic-trading aids in creating sufficient liquidity for sellers in the market.


Systematic traders (trend followers, pairs traders, hedge funds, etc.) find it much more efficient to program their trading rules and let the program trade automatically.


Automated trading provides a more systematic approach to active trading than methods based on a human trader's intuition or instinct.


The speed of order execution, an advantage in ordinary circumstances, can become a problem when several orders are executed simultaneously without human intervention. The flash crash of 2010 has been blamed on algorithmic trading.


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