5 Essential Facts About Algorithmic Trading In India



At present automation has changed our lifestyle. Now we are getting more and more depended on technology day by day. It has changed the way of business/investing. Now we got several types of robots or tech to do our work for us even online trading.

In 2008, SEBI allowed automated trading in India. Since then, the number of companies that use algorithmic trading has increased, with current estimates put the figure at 50% of the total volume.

This figure is still low when compared to developed countries like the US where trading volume more than that in India, 70-80% of trades done through algorithmic trading. This makes a career in algorithmic trading in India all the more interesting, where the concept is still relatively new in comparison with developed countries.

Let’s try to understand 5 essential facts about algorithmic trading in India.

Prerequisites Before You Start Algorithmic Trading

Both stock exchanges, the National Stock Exchange (NSE) and the Bombay Stock Exchange (BSE) have different prerequisites before you can get the approval to start algorithmic trading.

Technically, a person can become a member of the trade and direct trade through the exchange by meeting certain criteria. The members of the exchange (s) can apply for direct approval by the exchange. On the other hand, non-members can apply for approval through their broker.

Approval is a multi-step process the right to participate with the relevant algorithmic trading strategy in a trading environment pretend, get it approved by the auditor to give a demonstration to exchange for the approval of the strategy.

One should note that any change in the algorithm must go through an approval process before it can be implemented the exchange.

The Role Of Co-Location In The Market

It is known that the first to react to the news can use it to their advantage. In the race to be the fastest to respond, most of the high-frequency trading (HFT) firms rent space in a rack server on the same network right on the spot exchange itself. This is referred to as the ‘co-location’.

The advantage of co-location of reduced latency, which is the time your system needs to respond to any trigger, as the company can respond quickly when compared with those who house their servers away from the exchange. This idea, your data has to travel less distance, resulting in a faster response.

Co-location is generally required only for HFT strategies such as arbitrage, market making, etc. that require a high level of technology and infrastructure spending and therefore used mainly by institutions and proprietary trading houses. Interestingly, India has one of the co-location charges the lowest among peer exchanges worldwide.

From the perspective of a retailer or individual, Co-location has led to a more efficient market because of a decrease in bid-ask spreads, as market makers can respond more quickly to new updates and is able to offer much more stringent price. One study by Aite Group a few years ago in the US has pegged the savings to retailers/individuals at nearly $ 250 per year!

Type Of Algorithmic Strategies

Contrary to popular opinion, not all algorithms designed for high-frequency trading. There are various algorithms other than arbitrage and market-making algorithms designed by institutional investors and retail traders to trade in the market using the algorithm. Some popular algorithms including:

Momentum / Trend Following – The algorithm is trying to find the company’s stock price trends by using technical indicators and/or quantitatively different to analyze the available information. Once these are identified, the trader can place a trade depending on the perceived profitability of the strategy.

Statistical Arbitrage – One example is a statistical arbitrage trading partner where we see the ratio/spread between a stock price, co-integrated. If the value of spread beyond the expected range, then you buy a stock that has gone down and sell stocks that have outperformed in the hope that the spread will return to normal levels.

Statistical arbitrage can work with a hundred or more of the shares in the portfolio are classified according to a number of factors and can be fully automated from the perspective of both analysis and execution.

Machine Learning Algorithm Based – In simple terms, the use of historical data and feeding this market for machine learning algorithms that they have been designed. the data is divided into data training data and testing.

Machine learning algorithms to learn patterns and features of the training data and trains itself to take a decision as to identify, classify or predict new data or results. algorithms continue to learn from the positive/negative, to improve accuracy and performance.

Order-To-Trade Ratios Help Monitor The Market

The ratio of order-to-trade is the ratio of the number of orders sent to the exchange, with the number of orders that can be traded. A ratio of 2: 1 would indicate that only half of the total orders received are traded and the rest remain pending or to be canceled/rejected.

The significance of this ratio is the fact that the exchange punishes a company with a high frame rate trade as one might weigh on the exchange infrastructure by sending commands that are not expected, or worse, not intended for trading. Indian exchanges enforce penalties on companies that have a ratio of order-to-trade high for orders that prices outside the trading price range mentioned.

Development Of Strategies And Research Tools

With the advent of online research tools, many traders are increasingly looking out for online resources and backtesting platform in an effort to enhance the trading models and strategies. The latest automated trading platform like SGT Markets been granted access to market data vendors, and also a platform to build and evaluate their algorithmic trading strategies using statistical and computational power.

They also use several types of Forex trading signals in order to become more successful because these days every trader uses Forex signals.

In the end, algo trading has brought a new era to online trading. Though it’s not 100% dependable but if you stay vigilant then you can profit consistently from this technology.


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