Algorithmic Trading

By: Bank of Baroda
Thu Nov 5, 2020
Share This:
75c9619f-d9e2-41d1-8372-b9b532ced2d6.jpg

Generally, humans carry out analysis of companies, sectors, businesses, prices and other data and then decide when to buy or sell a stock. But this data can be automatically analysed by a computer as well. In Algo or Algorithmic, a set of rules/instructions are given to a computer on various parameters and mathematical models to ease the process of trading and maximising return on each trade.

Once the instructions are fed in a program, it lowers the process of human involvement and a computer can trade for a specified period of time without any constant supervision. It enables faster decisions and quick implementation which improves the chances of making higher return over other traditional investing methods.

Algo trading also have many other advantages over manual trading like no emotional bias, high level of accuracy and ability to backtest. Backtesting over a historical data certainly gives an investor more confidence in the trading strategy.

Kuants, the fintech platform of Gurugram-based MeanBox Technologies Pvt Ltd,offers an Algorithm Lab, on which stock traders, investors and enthusiasts can create and test different trading algorithms without the need for coding. It provides web-based technology platform that can backtest and deploy desired trading strategies. The user can also pick and choose an algorithm made by other thousands of experts. Similarly, Streak, Bangalore-based startup, provides a platform for algo-traders to create, backtest and deploy numerous algos based on customised requirements like risk appetite.

According to a study by the National Institute of Financial Management (NIFM), around 50 percent of total orders at both NSE and BSE are algorithmic trades on the client side. Similarly, on the proprietary side, more than 40 percent of the total orders placed at both exchanges are algorithmic trades. This has seen the emergence of many startups in the algo trading ecosystem like Quantopian, Amibroker, Sensibull, NinjaTrader, Metatrader etc.

Multitude of tech-savvy brokers are developing APIs to simplify the trading process by extending an integration with their trading platform with which one can build their own customized Algo trading applications.

According to a new market research report published by MarketsandMarkets, the global Algorithmic Trading market size is expected to grow from $11.1 billion in 2019 to $18.8 billion by 2024, at a Compound Annual Growth Rate (CAGR) of 11 % during the forecast period.

Credits : Akhil Handa

Leave a Comment

Search in Archives

Close
[!BOB_UserLogin!]
Back to Top