Algorithmic Trading
An Algorithm is a process or set of rules to be followed in calculations or other problem-solving operations especially by a computer. Algorithmic trading is a method executing a large order using automated pre-programmed trading instructions accounting for a variety of variables such as time and price to send smaller orders out to the market over time. It involves a trading system that relies on mathematics and computer science to output different strategies of trading.
The greatest part of Algorithm Trading is High Frequency Trading. High Frequency Trading(HFT) is a program trading platform that uses powerful computers to transact a large number of orders at very fast speeds. High Frequency Trading uses multiple complex algorithms to understand a number of markets and execute the orders based on market conditions.
Algorithmic trading is used is by investment banks, pension funds, mutual funds, and other buy side institutional traders. It is used to minimize the cost, market risk and market impact in execution of an order. Algorithms are used in this method so that the larger amount of stock can be distributed into smaller groups to be electronically executed over minutes, hours and days. In order to evaluate an algorithm the average prices obtained by trading with a market benchmark must be compared.
In one of my previous entries, I explained how machines are taking over all the industries. The future of Investing is said to be Algorithmic Trading.The algorithm simply takes all the tradable assets and combines the decision-making components with technical analysis using computers and math in order to create a final signal which will predict the direction the asset will move.The algorithm is able to put in a lot of different dynamics which is generally impossible for an analyst.This could affect the future market price and thus forecast the future price movement in advance.The algorithms learn from previous forecasts and is continuously adapting the relationships and thus, is capable of quickly adjusting to a fluctuating market. As a result of the algorithm learning from past data and previous forecasts it consequently becomes more intelligent and produces increasingly more accurate forecasts as time progresses.
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References
- https://en.wikipedia.org/wiki/Algorithmic_trading
- http://financialtalkies.com/top-5-beginner-books-for-algorithmic-trading
- https://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&ved=0ahUKEwiToPPknYPPAhWJ1CYKHQOWBlMQjB0IBg&url=http%3A%2F%2Fwww.valuewalk.com%2F2016%2F03%2Falgorithmic-trading-makes-money-energy%2F&psig=AFQjCNFwutLPFX2ilKGVkGW5WslGL3TObw&ust=1473543030799737(Image)
- https://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&ved=0ahUKEwiSluyrmoPPAhUJSiYKHe2jDCcQjRwIBw&url=%2Furl%3Fsa%3Di%26rct%3Dj%26q%3D%26esrc%3Ds%26source%3Dimages%26cd%3D%26ved%3D0ahUKEwiSluyrmoPPAhUJSiYKHe2jDCcQjRwIBw%26url%3Dhttp%253A%252F%252Ffinancialtalkies.com%252Ftop-5-beginner-books-for-algorithmic-trading%252F%26bvm%3Dbv.131783435%2Cd.cWw%26psig%3DAFQjCNHKj2OViISjjjQTizTBqKLWsgBRPA%26ust%3D1473542033177525&bvm=bv.131783435,d.cWw&psig=AFQjCNHKj2OViISjjjQTizTBqKLWsgBRPA&ust=1473542033177525 (Image)
- https://www.math.nyu.edu/faculty/avellane/QuantCongressUSA2011AlgoTradingLAST.pdf
- https://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&ved=0ahUKEwi43eD5noPPAhVB7iYKHXrqDEcQjRwIBw&url=http%3A%2F%2Fiknowfirst.com%2Falgorithmic-trading-methods&bvm=bv.132479545,d.eWE&psig=AFQjCNHMMAD0ZnuDACwUox9EMHU7ek16yw&ust=1473543360817519( Image)
- http://iknowfirst.com/algorithmic-trading-future-investing
One of the most interesting aspects you addressed in the post is the role of self learning algorithms (A.I.). Already making up such a large part of the current US stock market, it will be interesting to see the shift in power dynamics between large institutions, HFT firms and regulators in the next 3-5 years.
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