Rajandran R Founder of Marketcalls and Co-Founder Algomojo. Full-Time Derivative Trader. Expert in Designing Trading Systems (Amibroker, Ninjatrader, Metatrader, Python, Pinescript). Trading the markets since 2006. Mentoring Traders on Trading System Designing, Market Profile, Orderflow and Trade Automation.

Why Algo Traders Stay Away From Traditional Trading Platforms?

1 min read

The so called Quant or Algo traders prefers to stay mostly away from Traditional trading platforms like Amibroker, Ninjatrader, Metatrader, Metastock, Tradestation etc. Do you know why?

These traditional trading platforms are designed to meet retail level expectation i.e you can connect up to various brokerages, downloading data, charting, custom indicators, backtesting..etc. It is relatively easy to understand their programming language and you can easily automate any simple trading strategies. Retail traders mindset is to create a simple plain vanilla trading algorithm and to find a edge in the trading system.


Retail traders prefer to stay away from trading strategies like Pair Trading, Options Mispricing…etc. Retail traders prefer Data management, coding indicators/signals, charting , backtesting and performance evaluation to be easier, They prefer to concentrate more on trading than their algorithms.

What is a Quant Trader and What Do They Do?

What are the issues with Traditional Trading Platforms?
1)Your trading algorithms are not cross portable. If you are writing a trading algorithm in one trading platform and tomorrow you willing to test another trading platform then you cannot easily port your trading system easily.

2) You cannot code complex mathematical models into traditional trading platforms. For example performing Co-integration between two trading pairs i.e ADF root test or performing complex statical models, implementing feed forward models , machine learning models is quite challenging in traditional trading platforms.

3)Most of the traditional softwares lack multithreaded backtesting capabilities.

4)Performance degradation of your trading system becomes poor when you are planning to test your models on bigger portfolio size.

5)Retail traders are dependent on trading system providers for support, bug fixes and updates.

6)Performing Monte Carlo testing is difficult in most of the trading softwares.

How does the quant traders solve such issues?

Generally most of the quant traders prefer trading programs like C, Python, R, Matlab,FPGA. They build their own data connectors, Order Management, Risk Management, Execution Mechanism, Data managament, backtesting/Optimization/Walkforward testing modules. Programs and modules/packages in python, C are open source and completely free, even for commercial use, as are many of the key scientific libraries. Building complex statistical models are quite easier which the retail level trading platforms are not able to solve. Parallelization and ability to hand huge computational power are another key to depend on such programming models which gives the scalability to your portfolio.

If you ask me to rate the retail level trading platforms for algo trading then multicharts comes at first as it support for backtesting portfolio of strategies, pair trading backtesting, optimization etc which lacks in most of the traditional trading software.

Rajandran R Founder of Marketcalls and Co-Founder Algomojo. Full-Time Derivative Trader. Expert in Designing Trading Systems (Amibroker, Ninjatrader, Metatrader, Python, Pinescript). Trading the markets since 2006. Mentoring Traders on Trading System Designing, Market Profile, Orderflow and Trade Automation.

Mini Certification on Automated Trading using Amibroker

If you are new to Automated trading? This certification course will help you to kickstart your automated trading with your broker and get to...
Rajandran R
1 min read

Finfolab Technologies developed API Solutions for Goodwill

Finfolab Technologies developed Arrow API solutions for Goodwill. Our API solutions enable retail traders and Goodwill commodities partners to design and deploy advanced algorithmic...
Rajandran R
31 sec read

Angel Broking Multi-Client Amibroker Trading Module

Got frequent requirements from Angel Broking Customers to automate Amibroker based trading system where one single generation from charts could punch orders in multiple...
Rajandran R
6 min read

8 Replies to “Why Algo Traders Stay Away From Traditional Trading Platforms?”

  1. I was under the impression that retail investors in India are not allowed to do fully automated algo trading, only semi-automated. Is this not true?

    1. Yes as of now only Semi-automated trading is allowed for retail traders as the exchange is curious about the risk managment inolved in the execution of orders. If it is exchange approved execution mechanisms then you are use dealer terminal to do full automated trading. Otherwise you have to go to the exchange simulate your algorithms with them and then get approved by the exchange.

      What i feel is a temporary restriction by the Exchange. Once big brokers are entering into this segment the gateway will be opened for the retail traders to participate.

      Another Alternative is to go with symphony fintech (Algo solution provider) to do full auto trading.

  2. Dear Rajandran Sir,
    As usual informative article regarding algo trading. India is still a developing market and as markets evolve, the technology becomes more and more advanced. Algo trading at present on NSE is very less but participation might increase in the coming years as more people adapt to the growing technology.

    1. Yes currently some sort of friction is there for people to enter and test algo trading once big brokers are interested in providing algo trading solutions to the clients then i feel the friction will be removed.

  3. Ultimately, as a systematic trader, what matters most is your productivity. Focusing on the tools is in my opinion a mistake. Some great traders I know use only Excel and yet make about $10,000 a month while some other smart PhD guys spend thousands of hours in math-turbation and make no money.

    It is important to know what you’re the most productive at. For example, I do most of my research work in Python (I love the IPython Notebook) or R depending on what I want to do (I love ggplot2). I often pre-process data in Python to add indicators or signals that I believe Amibroker can’t handle, and then code my strategy in the AFL language on top of my customized data.

    FYI, I know of several hedge funds that use retail trading platforms and some even Excel for backtesting! Technology doesn’t (usually) make you money (though it can cost you A LOT of money) – smart strategies do.

    1. Perfect! Even Warren buffet never used even a excel stuff to create money. But When comes to explore complex mathematical modelling, retail trading software platforms had lots of bottle necks.

  4. HI Rajandran,

    Which trading platform(or Brokers) is good for Semi-automated trading in India ?

    Automate till the order details are entered and I need to press enter to submit the order.

    Any details on the costs involved will be helpful

Leave a Reply

Get Notifications, Alerts on Market Updates, Trading Tools, Automation & More