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Some Unique Facts about Automated Trading that Every Trader Must Know!

Since 2008, under the surveillance of trading bodies like SEBI, automated trading has been operational in India. Since then, the number of firms using algorithmic trading has been on the rise.

In developed markets like the US, 70-80% of trading owes to algorithmic trading. This opens paths for a bright career in algorithmic trading in Asian countries where the market tends to be much more exciting as the concept is relatively new compared to developed markets. 


Here are some little-known facts about algorithmic trading:


Prerequisites before you start algorithmic trading


Various stock exchanges have different prerequisites before you can get an approval to start algorithmic trading. One can choose to be a trading member and directly trade through the exchange by fulfilling the stated criteria. The members of the exchange(s) apply for approval directly while the non-members apply through brokers. Anyone eyeing a change in algorithms must have the exchange’s approval before implementation.


Co-location and its role in the market


The first one to react to news is the one to use it to their advantage. In the race to be the fastest to respond, most high-frequency trading firms rent space on server racks on the same network right in stock exchange premises. This is called as ‘Co-location’. The best benefit is reduced latency, i.e., time a system takes to respond to trigger compared to those who have servers away from the exchange. The concept is, data travels a lot lesser distance and results in a faster response. Co-location leads to more efficient market due to decrease in bid-ask spread, as market makers respond much faster to new updates and afford to quote much higher prices.


Types of Algorithmic strategies


Not every algorithm is designed for high-frequency trading. Institutional investors design various algorithms to trade in similar markets using. Some of the popular algorithms include:

  • Momentum/Trend Following 
  • Statistical Arbitrage
  • Machine Learning-based algorithms

The order-to-trade ratio helps monitor the market.


The order-to-trade ratio is the ratio of the total number of orders sent to the exchange, to the number of orders traded. A ratio of 2:1 indicates that only half of total orders were traded and the other remained pending or were rejected. The importance of this ratio is that the exchange penalizes firms with high order to trade ratio. Thus, while trading order-to-trade ratio needs to be kept in mind while trading our orders!


Research tools and Strategy development


With the support of online research tools, traders are increasingly looking out for online resources and back testing platforms to improve trading models and strategies. Some web platforms give traders access to market data and a platform to build and analyze automated trading strategies using the power of statistics & computing.

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