List of Low Code/No Code Algorithmic Trading Platforms in India
A comprehensive article to get you started!
7 min read
Hi There 😇, in this article, we will be covering the list of all available No-Code to Low-Code Algorithmic Trading platforms developed in and for India.
Why am I writing on this, considering I plan to educate Algo-Trading using Python?
Frankly, learning Python actually to start Algo-Trading has a steep learning curve. Until you get there, these No-Code Algo Trading platforms are a chance for you to actually backtest the strategy you have in mind and even do paper/live trading after connecting with your broker.
These platforms are also an excellent opportunity to learn more about the terminology used when creating algos for trading, for example, slippage, backtest, brokerage, commission, drawdowns, etc.
Below is the list of platforms; I have tried to personally analyze them for you with some comments for better decision-making. Frankly, the technology behind all of these platforms is amazing, and I envy the founders of each one of these. If you find any material errors in my comments, please do reach out to me to fix them. If I have missed any other No-Code/Low-Code platform based out of India, drop me a line, and I will analyze and add it (giving you full credit)
All the names in the below list have been hyperlinked to the original website; you can click on it to go there directly.
Disclaimer: I am not associated with any of the platforms below, and none have sponsored this post; this is just for informational purposes only.
Disclaimer: One of the readers of this blog Niftytrader has made some very valid points regarding compliance issues with the platforms in the comments below and I have got conflicting views in the industry on the legality of it. Hence, please use these platforms at your own discretion and consult a legal expert if required. TradeWithPython will not be liable for any damages or legal issues.
- TradeTron: TradeTron is an Algo Strategy Marketplace where portfolio managers can come and build their strategies and sell them to customers for a profit-sharing fee. Customers can also create their own strategies using their simple-to-use Strategy Builder. The platform also allows you to paper trade and has the ability to connect with the highest number of brokers in India. Below is the pricing for TradeTron. Below is the pricing for TradeTron.
- Kuants: AlgoLab is a Backtesting Platform by Kuants, and SMART is a marketplace where users can buy and sell their Algo strategies. AlgoLab is still in the development phase and currently only supports individual stocks and Index Futures. Backtesting on Options is not yet supported, but as per the support team, it is underway. Here is the pricing for Kuants.
- StockMock: If you would like to backtest Index Strategies on Options, StockMock will be your most likely choice, they are the leaders in this segment and probably the people who gave rise to the 9:20 straddle. A lot of other platforms do not provide historical option backtesting but StockMock does, unlike others, they do not provide live execution services. They are a pure backtesting platform. Their pricing looks like below. (Added into the blog on 4 Sep 2021)
- RoboMatic 🤖: This product is by TradeLab Technologies and supports backtesting on up to 5 years of data for all categories like options, stocks, futures, etc. The pricing for RoboMatic is as per below.
- Streak: One of the first backtesting platforms in India, Streak is backed by Rainmatter which is a Fintech incubator from Zerodha. This is one of the most famous platforms out there and supports paper trading; it also integrates multiple brokers and has scanners that you can create without coding. A scanner can be as simple as notifying you when the 20 SMA cross LTP for a list of stocks you wanted to scan. Here is the Pricing by Streak on a Zerodha account.
- AlgoCrab: This platform allows you to deploy selected strategies by connecting your broker account, they do support multiple brokers, and each of their existing strategies is customizable. They also support external charting platforms like TradingView, MT4, and NinjaTrader to do Algo Trading. All their strategies vary in price.
- AlgoBulls: This platform also serves as a strategy marketplace and segregates strategies based on your status, i.e., Retail Investor, HNI, Ultra HNI, etc. They also allow you to develop strategies and backtest for free. They also have a developer API with a Python wrapper which can be used to develop your own strategies and put them on Marketplace. Here is the pricing for AlgoBulls.
- Keev: Keev is one of the newest platforms in India in the Algo-Trading space, they are in the Beta phase at the moment. What I really like about this platform is that they allow you to visualize your strategy while building it (see screenshot below), and they have a fast backtesting framework; you can also run multiple iterations with different conditions of your strategy in one click (like stop-loss, rebalancing, profit%) to see when it performs best. They currently only support Zerodha and Angel Broking for live trading, and they do not have Options for backtesting at the moment.
- Quantman: Quantman is also a new entrant in the backtesting and live-trading space. They are also in their Beta-phase at the moment and one thing which I really like about them is that they offer backtesting on Options-based strategies as well, which very few platforms in this space do. Their integration with brokers for live trading is still under construction. Do check out their free beta trial and give them any feedback you might have.
AlgoTest: AlgoTest launched in November 2021 as a no-code solution back of the popularity of time-based entry-exit strategies, the tool is relatively simple to use and if you have time-based entry/exit points, they are a good tool to use and they also integrate with major brokers in India allowing you to paper trade/live trade or backtest any time-based strategies. After speaking to their team last week, they have advised of a new upcoming TradingView Integration which will enable you to trade based on charts/patterns and will substantially differentiate them from the crowded low-code/no-code market. They give you 25 backtests for free and post that their pricing looks like this:
- Algoji: This platform is also quite famous, but unlike others, it does not allow you to create your own strategies. Instead, AlgoJi provides the fastest APIBridge, which can connect with multiple brokers for the fastest order execution time (50ms latency), which is very, very good; you can also connect this bridge with existing trading software like Amibroker, MT4. It also has a product, VPS4Trading, which help you host your strategies on a Virtual Server. Their product MyCoder allows anyone with a strategy to come and talk to their developers, who will charge between Rs 10,000/- to Rs 50,000/- depending on complexity.
- AlgoMojo: This platform also comes under the category of Low-Code as they provide an API Bridge which takes care of your order execution with multiple brokers in a single API at fast speeds. They support 10 brokers and support external software like MetaTrader, AmiBroker, TradingView, etc. If you open a brokerage account via them, they provide you a Free AlgoMojo account. Here is their pricing.
- AlgoBaba: AlgoBaba also provides an API Bridge which connects with multiple brokers for fast order execution and risk management. They also have an Expert Coder service where you can book a call with their coders who can build your strategies for a fee and integrate that Algo in any of the external software/charting tools you use. They also provide a VPS to host your algorithm.
Update: After posting this article, AlgoBaba reached out to me on Twitter to say the below, I think having 100% Trade Signal Security is phenomenal. By IAB, they mean Intelligent API Bridge.
Phew! 😓 This was a time-consuming piece to research all the platforms. But hopefully, it helps you decide which no-code/low-code platform to use in your algo-trading journey.
Again, I would be more than happy to listen to you for some feedback and any ideas on future articles/content; I thank you for being a reader of TradeWithPython.
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