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Algorithmic Trading in India: Resources, Regulations, and Future

13 min read

By Chainika Thakar

Algorithmic trading implies the execution of trades on stock exchanges without much human intervention (except for tweaking the algorithms according to the required trade positions) using computer programs and software.

While it has its detractors, the general consensus is that algorithmic trading is an inevitable evolution of the trading process. In India, at present, around 50% plus of total orders ⁽¹⁾ at both NSE and BSE account for trades placed algorithmically.

Let us find out more about the popular algorithmic trading in India. with this blog we will cover:

A brief about algorithmic trading

In simple words, algorithmic trading is a process of converting a trading strategy into computer code which buys and sells (places the trades) for stocks in an automated, fast and accurate way.

Generally, the automated way of trading is faster and more accurate, and hence, it is preferred nowadays and is increasing its reach in emerging markets rapidly.

Technically, there are several mathematical algorithms at play for making trading decisions on the basis of current market data, which then send and execute the order(s) in the financial markets.

This method makes the trading free of all emotional human impact (like fear, greed, etc.) since decisions to carry out each trade are made by computers in a systematic manner.

For instance, you can design a simple algorithm that buys shares of Apple (AAPL) if the current market price of the share is less than the 200 days’ average price. Conversely, you can also ensure that it sells Apple (AAPL) shares if the current market price is more than the 200 days’ average price.

Learn algorithmic trading basics and gain a solid foundation in this exciting field. Check out part 1 of the video series, which introduces you to algo trading, the industry landscape, pros and cons, building an algorithmic trading python strategy, the benefits of a quant approach, different types of data, and more.

History of algorithmic trading in India

On April 3rd 2008, the Securities & Exchange Board of India (SEBI), introduced algorithmic trading by allowing a Direct Market Access facility to institutional clients.

In short, DMA allows brokers to provide their infrastructure to clients and gives them access to the exchange trading system without any intervention on their part. Initially, it was provided only to institutional clients and not retail traders.

Nevertheless, the facility brought down costs for the institutional investor as well as helped in better execution by cutting down the time spent in routing the order to the broker and issuing the necessary instructions.

On April 29th 2008, this facility had already become popular with some of the top global players signing up for the DMA facility. FI’s & FII’s like UBS, Morgan Stanley, JP Morgan and DSP Merrill Lynch were the entities awaiting approval.

Edelweiss Capital, India Infoline and Motilal Oswal Securities were among others who had submitted their request to the stock exchanges. It is worthwhile to note that Foreign Institutional Investors (FIIs) were allowed to use the DMA facility through investment managers nominated by them, from February 24th 2009.

By July 31st 2008, leading brokerages along with stock exchanges were preparing the ground for operationalising Direct Market Access (DMA). Brokerages such as Citi, Merrill Lynch, Morgan Stanley, JP Morgan, Goldman Sachs, CLSA and Deutsche Equities had started holding test runs of their DMA software, in an attempt to synchronise it with the systems at the stock exchange.

Role of smart order routing, High-Frequency Trading and co-location in algorithmic trading

Algorithmic trading includes practices such as smart order routing, high-frequency trading (HFT) and co-location under it. You will see these practices discussed below in detail.

Smart order routing

Order routing is a process by which an order goes from the end user to an exchange.

An order may go directly to the exchange from the customer, or it may go first to a broker, who then routes the order to the exchange.

Smart order routing is an automated process used in algorithmic trading that follows a set of rules for executing an order. Smart order routing attempts to achieve the best execution of trades while minimizing market impact.

Here's an informative video on smart order routing trading which explains how SOR optimizes large trades, reduces market impact and enhances execution prices.

High-Frequency Trading (HFT)

High-frequency trading (HFT) is a subset of algorithmic trading. Here, opportunities are sought and taken advantage of on very small timescales from nanoseconds up to milliseconds.

Some high-frequency strategies adopt a market maker type role, attempting to keep a relatively neutral position and proving liquidity (most of the time) while taking advantage of any price discrepancies.

Other strategies invoke methods from time series analysis, machine learning and artificial intelligence to predict movements and isolate trends among the masses of data. Specifics of the strategy aside, for HFT, monitoring the overall inventory risk and incorporating this information into pricing/trading decisions is always vital.


Co-location is a data centre facility in the exchange premises where the exchange’s servers are on the same network. It is used to rent space to trading firms to locate their servers and other computing hardware.

The co-location facility provides the power, bandwidth, IP address and cooling systems. Also, co-location helps in reducing the latency by minimizing the travel time between your server and the exchange’s matching engine.

How to start algorithmic trading in India?

Let us now discuss how you can begin algorithmic trading in India, along with some prerequisite resources to learn algorithmic trading.

Let us begin with the prerequisites first.

Prerequisites for doing algorithmic trading in India

Analytical skills

Having an analytical bent of mind is a very important quality for any quant trader/developer, and is valued in an interview.

For example, a candidate may be given a huge data set and asked to find patterns from the data. Candidates get evaluated on how they approach any given problem and their ability to justify their solutions objectively.

Mathematical skills

As the core of algorithmic trading revolves around algorithms, data, and programming, having reasonable programming skills and a basic understanding of statistics and calculus is important for any job seeker in algo/HFT trading.

Quant jobs in finance require strong mathematical and programming skills to analyze complex data and develop trading strategies.

For example, if a candidate is applying to a firm that deploys low latency strategies, then an expert level of programming would be expected from such a candidate.

Programming skills

Knowledge of a programming language (Python for Trading) is an added advantage as it enables you to function independently. Traders are inclined toward learning the long-term effects and benefits of coding, especially Python.

Python is good for conceptualizing, and backtesting strategies, and has many libraries for validation and visualization of results. It can also be used by firms for strategies that are not dependent on low latency.

The strategy development process

While devising any strategy, it is important to understand the risks and rewards associated with that strategy in order to determine whether it has an edge in the markets. This is done during the backtesting of a strategy.

The frequency of trading, instruments traded, and leverage are all needed to be taken into consideration before going live with the strategy in the markets.

A single strategy doesn’t guarantee profits year after year. One has to formulate and overhaul strategies regularly basis using advanced mathematical models & statistics to remain profitable in the markets.

To understand various algorithmic trading strategies, you can learn about the algorithmic trading strategies, paradigms and modelling ideas.

Looking to learn more about algo trading strategies and create your own trading strategy? Check out part 2 of the video series, which covers a wide range of topics including trading idea generation, alpha seeking, universe selection, entry and exit rules, coding logic blocks, and backtesting.

Understanding the Financial Markets

Quantitative trading involves dealing with large financial datasets, trading in different instruments like stocks, derivatives, forex etc. Hence, even if you are coming from a non-finance technology background, as a developer in a quant firm, you need to have a fair understanding of the financial markets.

Trading firms usually make their new recruits spend time on different desks (e.g. quant desk, trading, risk management desk) to gain an understanding of the markets.

Besides these, it is necessary that one is equipped with domain knowledge. To know more about the skill sets required, check out this infographic about the top skills for nailing a Quant or Trader interview.

If one is thorough with the abovementioned prerequisites, you simply need to be prepared for the quant interview if you need a job in an algorithmic trading or HFT firm.

Besides the above mentioned, let us also see some general skill sets required to become an algorithmic trader, which go as follows:

  • Quantitative analysis
  • Programming skills
  • Statistics and Probability
  • Knowledge of financial markets and trading
  • Logic and reasoning
  • Econometrics
Skills for quants
Skills for quants

Going forward, let us find out reliable resources to learn algorithmic trading.

Resources to learn algorithmic trading in India

For learning algorithmic trading, some useful courses and books specifically for algorithmic trading are a big help!

The courses can help if you want to follow a teaching-oriented learning approach. On the other hand, books can help those who like to read and learn with the detailed concepts covered.

Check out the 3rd and final part of the video series, explore how Python trading bots can be used to backtest a trading strategy on the research platform such as Blueshift.

Regulations on algorithmic trading in India

There are a specific set of rules and regulations for algorithmic trading in India in accordance with the audit requirements, execution of algorithmic trades and commodity markets.

Audit Requirements

All algorithmic trading firms need to get through a half-yearly audit and auditing can only be done by Exchange empanelled system auditors (CISA certified) listed on the exchange’s website. For the audit requirement, you need to maintain logs for order, trade, control parameters, etc. of the past few years.

Now you must know that the control parameters are specifically needed by Indian exchanges to understand if the strategy of the order placed is verified or not.

Here are certain compliances with regard to the execution of the orders. Firstly, it maintains that all the orders must be tagged with a unique identifier as specified by the exchange. Secondly, new orders can only be executed after accounting for the previous unexecuted orders.

Any modifications in the algorithms are to be approved by the exchange and the system should have enough checks to terminate the execution in case of a loop or a runaway.

Commodity Markets specific

There are certain risk control measures like Daily Price Range, Maximum order size, Position limit, etc. which should be adhered to. Additionally, Market Orders and IOC (Immediate or Cancel) orders will not be placed, only limit orders can be placed.

Mini and micro contracts are not entertained by Algorithmic trading. Also, all orders should be routed through member servers located in India and from approved IDs. These systems cannot have any links with any system or ID located/linked outside India.

Members must ensure that their strategy induces liquidity into the market and should submit a document explaining the same. Members shall also maintain all logs as specified above and ensure regular audits and get approvals for any changes to existing strategies.

Algorithmic trading in India today

Algorithmic trading was introduced and allowed in India in 2008 by the Securities and Exchange Board of India (SEBI). Initially, it started with Direct Market Access (DMA) which was restricted to institutional investors only, but due to the cost advantage and better execution, the trading community adopted it.

Exchanges also played an important role in the adoption of algorithmic trading by offering co-location server 'racks' ⁽²⁾ on lease to broking firms in June 2010. The leasing out of server racks helped the brokers to improve trading speed and align with international markets.

In today’s time, most of the leading brokerages along with stock exchanges have the ground for operationalising Direct Market Access (DMA). Brokerages such as Citi, Merrill Lynch, Morgan Stanley, JP Morgan, Goldman Sachs, CLSA and Deutsche Equities have their DMA software to synchronise it with the systems at the stock exchange.

Also, algorithmic trading in India today has become quiteadvanced and there are more High-Frequency Trading (HFT) firms prevalent in the country.

Future of algorithmic trading in India

Algorithmic trading ⁽³⁾ is progressive in many ways - apart from the opportunities for good returns for the trader, algorithmic trading is more systematic since it rules out the impact of human emotions and errors. It also makes the market more efficient and liquid.

So, what is the future of Algorithmic Trading like?

The future of algorithmic trading predicts ⁽⁴⁾ that the resources for algorithmic trading will evolve and become structured and efficient as the market grows.

India has a 50-60% penetration of algorithmic trading in the markets but it is also perceived that algorithmic trading in Indian markets will continue to grow.

Also, there are these two predictions ⁽⁵⁾ for algorithmic trading in India-

  • It is expected that the equities might contribute $8.61 billion in the algorithmic trading market share in 2027.
  • The algorithmic trading market can grow at a CAGR of 11.23% between 2021-2026.

Frequently asked questions about algorithmic trading in India

The following are some of the FAQs about Algorithmic Trading:

Who can do algorithmic trading?

Anyone skilled in a programming language (such as Python), has the knowledge and experience of trading in markets and has acquired the prerequisites for doing algorithmic trading, can do algorithmic trading.

Although, anyone involved in algorithmic trading must keep in mind these:

  • Constant human intervention is needed for resolving any glitch in the system and for tweaking the codes according to the changes in the market.
  • A strong internet connection is needed for keeping the algorithmic trading uninterrupted.
  • Traders must continuously work on their technical skills to develop the algorithms with the advancements in technology.

The approval process is not that tedious, but yes the infrastructure (especially with HFT) can be a bit tricky if you are a retail trader or individual trader. Also, if you have a broker for automation, then the regulation demands that the broker should take the approval on your behalf.

As an individual, you as a retail trader cannot go to the exchange and ask for approval.

Is the approval process and infrastructure cost affordable for retail traders?

The cost depends on the broker but technically it’s not that costly.

The simple answer to this question is “Yes”.

What are the approvals you need before going algo?

In case you are trading in the CME, SGX or Eurex then the approval required is more of a conformance test which means that you will be taking approval for your trading platform. Once it is approved you can code whatever strategy on it and send out orders.

In case you are in geographies like India or Thailand then you will need to get your strategies approved and for that what you will be doing is creating a document for each strategy and sending it out to the exchange for approval.

If you are a member of the exchange yourself you can send it directly and if you are not a member of the exchange then you send it through a broker.

The process in India involves (can vary for different exchanges) getting the strategy signed by the auditor, participating in a mock trading session, and then getting a demo by the exchange. Post that you get approval from the exchange and then you start trading. That’s the rule you have to follow for each strategy.

Is confidentiality maintained while going through the approval process?

The exchanges generally do not focus much on the strategy but more on risk management.

The focus is that your strategy should not create havoc for the market or for them, which is the key concern for the exchange and not what your strategy does.

They would ask you about the strategy at a broad level but I don’t think it goes to a level where your IP is threatened.

Does algorithmic trading give good returns in India?

Good returns for algorithmic trading depend completely on your algorithmic trading strategy. The better your experience in the markets, the better your strategy will be and hence, you will be able to reap better returns.

How risky is algorithmic trading towards manipulation such as co-location?

co-location is not manipulation. It’s just a facility provided to you. It’s like saying how risky it is if you are travelling by air by spending more as compared to someone who is travelling by train to a destination.

You are reaching faster but you are paying for it and you are getting it so it’s a fair market, you pay for what you get.

For those who co-location matters and for most of the exchanges across the globe it is not that expensive hence the exchanges also have been pretty responsible.

Even in India you can get half racks (which is 21 units) you can place a good number of servers in a half rack and that comes to around 50,000 rupees a month. I am not saying it’s cheap but it is not that stringent if you are trading into strategies which are dependent upon co-location for which every millisecond matters.

Are retail traders successfully adopting algorithmic trading? Is there super difficult competition from Institutional traders for retail traders?

Retail traders are the ones which had remained deprived of algorithmic trading for a long time. But, now, retail traders are adopting algorithmic trading since companies or brokers like TD Ameritrade ⁽⁶⁾ are supporting retail algorithmic traders.

According to Economic Times ⁽⁷⁾ on November 29, 2017, Sebi was among the first regulators to issue a discussion paper proposing strengthening of rules on algorithmic trading in August 2016. It produced a set of seven proposals aimed at creating a level playing field between institutional investors and retail investors.

What are the global markets or exchanges that an Indian can trade on?

You can buy stocks based in the US from India and can have a trading account with an international broker. Also, you can buy exchange-traded funds available on international indices.

Also, recently, there are 8 US stocks ⁽⁸⁾ which are made available for trading by Indian traders directly via NSE IFSC.

Take a look at the list below.

List of US stocks available for trading
List of US stocks available for trading

We have curated a list of some of our most demanded blogs on Algorithmic Trading written by experts!


Although India was not an early mover in the world of algorithmic trading, its popularity has been on the rise ever since SEBI allowed the usage of advanced technology to be followed by the equity markets.

This has also created a need for algorithmic trading software, tools, and platforms, which are being accessed by traders to perform financial manoeuvring.

If you want to learn various aspects of Algorithmic trading then check out this algo trading course which covers training modules like Statistics & Econometrics, Financial Computing & Technology, and Algorithmic & Quantitative Trading. EPAT is designed to equip you with the right skill sets to be a successful top algorithmic trader.

Note: The original post has been revamped on 29th September 2022 for accuracy, and recentness.

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