Algo Trading- What it is and what it is not!

Algorithmic trading has revolutionized currency equities and bond markets globally, making them more efficient. In developed markets such as the US, it stands at approximately 70- 80% of the equity market turnover. Algorithmic trading in India has also increased up to 49.8% of total turnover from 9.26% in 2010. In March this year, 44.8% of the cash market volume and 48.2% of the equity derivatives market was driven by algo trading, as per NSE data. On the BSE, 37.22% of trade in March 2018 was driven by algo trading.

SEBI’s recent announcements on steps for strengthening algo trading through shared co-location has also boosted the sentiments of algo solutions providers and it is likely that this term will become a part of our daily lexicon sooner than we know.

The trend is here to stay. Therefore it is important to understand what the word actually means and what it doesn’t!

WHAT DOES ALGO TRADING MEAN AND HOW IT DIFFERS FROM OTHERS

HFT (high-frequency) trading – Trading strategies can be categorized as low-frequency, medium-frequency and high-frequency strategies as per the holding time of the trades. High-frequency strategies are algorithmic strategies which get executed in an automated way in quick time, usually on a sub-second time scale. Such strategies hold their trade positions for a very short time and try to make wafer-thin profits per trade, called scalping, executing millions of trades every day. The current NSE – CBI issue regarding certain issues with co-location access etc all fall in this class of trading. Apart from this, these are the strategies which have caused the “flash crashes” we hear about.

Algorithmic trading – Algorithmic trading simply means turning a trading idea into a trading strategy via an algorithm. The trading strategy thus created can be backtested with historical data to check whether it will give good returns in real markets. The strategy can be executed either manually or in an automated way. PL’s Traders Edge product is an example of this type of trading and uses end to end automation without human intervention.

Quantitative trading – Quantitative trading involves using advanced mathematical and statistical models for creating and executing trading strategies.
Automated trading – Automated trading means completely automating the order generation, submission, and the order execution process. This is therefore a subset of the above 3. This is also called an Execution Algo – as differentiated from Strategy Algos above.

An important point to note here is that automated trading does not mean it is free from human intervention- it just caused the focus of human intervention to shift from the process of trading to a more behind-the-scenes role, which involves devising newer alpha-seeking strategies on a regular basis, what we call “Öptimisation”.

ALGO TRADING OBJECTIVES

PL offers Algo Trading via the Traders Edge bouquet. This type of trading is an advanced and sophisticated investing mechanism which uses complex mathematical formulas and models to make quick decisions and transactions in financial markets.

Such strategies can be continually improved by not only the process of optimization but improving these to “machine learning” algos – example, Google searches to assist in trend decisions like for example Weekly search averages for a particular term (e.g. defaults by Private Banks) which can be used to buy, hold, sell or re-buy stocks for that period.
Having the technology to set strict parameters and carry out orders autonomously removes all legwork for the investor as well as the emotion – therefore improving the probable profits multifold.As such, Algo traders generally enjoy three benefits over the traditional investor – speed, accuracy and lower cost. Algorithms can execute on multiple indicators simultaneously, so orders are carried out in a fraction of a second, removing the chance of human error and making greater opportunities available at better prices.
To read more about Traders Edge , do visit www.plindia.com/tradersedge

 

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