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The development of algotrading

As much as we think that the major computerization is a result of our current affairs, the truth is that this process started long ago, and even a relatively new matter of conduct as the algorithmic trading has its roots going back to the early 70’s. The first example of computing in regarding of trading was marked in NYSE with the introduction of Designated Order Turnaround (DOT) which later was upgraded to SuperDOT. The concept of the first algorithmic perception in trading evolved around routing electronic order for further manual execution. This tendency continued to evolve throughout the decade, leading to fully electronic execution of trades using electronic communication networks in the late 80’s and later 90’s. It led to a higher liquidity of the market, due to decimalization that changed the minimum tick amount from 0.0625$ to 0.01$ per share and contributed to the encouragement to use algo trading even more extensively.

Algotrading in the 21st century

Another significant breakthrough in the usage of computerized algorithms in the trading market occurred early in our century – in 2001 a group of researchers from IBM published a paper which showed beyond any doubt that two types of algorithmic strategies (MGD of IBM and ZIP of Hewlett-Packard) showed better performance than human traders. From this moment on – the course shifted towards algorithmic trading, giving a rise to various strategies and evolving market for computerized trades.

The fast evolution of the computing equipment allowed creating more and more new algorithmic trading strategies, including those combining pricing of several markets at the same time.

These changes prompted the demand for low latency proximity hosting (meaning there’s no lagging between the sent message and the implementation of this message in the form of a trade), as well as global connectivity.

Algorithmic trading these days

In 2011 the CEO of NASDAQ Robert Greifeld admitted that the main form of trading today is purely electronic, which only states the obviously superior status of the algotrading these days.

Algorithmic trading these days

These days the importance of algorithmic trading is entwined with the endless income of financial news, affecting the trades and the outcome of trades. It leads to almost instant reactions of the market to occurring events and eventually demands for ever-evolving algotrading systems. This means that the companies responsible for building new systems, as well as perfecting existing ones has to be sharp and constantly at the edge of technology.

The execution management system has to provide constant interpretation of the messages it receives. In general, the issue which raises the most concerns in the field is the overflow of information demanding to be inserted in the system and its processing for achieving actionable commands.