The startup's compliance framework is well-aligned with SEBI in India, the US SEC and other global jurisdictions
India is well on its way to becoming a Vikshit Bharat in a few decades. It is projected to emerge as the fastest-growing economy among the G-20. And its equity market has seen a near-non-stop bull run since the pandemic, primarily driven by institutional investors and a newfound surge in retail participation. Despite a few hiccups in the near term, J.P. Morgan and Goldman Sachs anticipate strong returns in the medium turn and a virtuous cycle of liquidity, sell-side coverage and capital issuance.
Not all retail investors can hope to become the next Rakesh Jhunjhunwala, though. Fast-paced financial markets are in constant flux, with a whirlwind of data, trends, split-second decisions and mammoth losses, overwhelming uninitiated individuals. However, AI-ML-powered algorithmic trading - automatically executed after strategies are pre-programmed based on investors' goals, risk tolerance and trading preferences - has become accessible to a bigger user base.
Set up by Pushpak Dagade, Suraj Bathija and Jimmit Patel, Mumbai-based AlgoBulls offers a user-friendly platform for algorithmic trading, encouraging greater participation from retail investors. The startup has also developed a cutting-edge technology stack that uses AI, trading parameters, deep data analytics and real-time market insights to generate sophisticated trading algorithms.
For context, algo trading covers all aspects of the financial market, from stocks to futures & options and commodities & forex. The auto-trading system is highly coveted by many as it ensures speed and efficiency, reduces operation time and costs (no one has to scan the markets 24×7 to find a suitable deal manually) and minimises human biases and errors.
SEBI has recently released a draft circular aimed at making algorithmic trading more accessible to retail investors -- a positive move for both retail traders and compliant platforms like AlgoBulls. Dagade is a member of the SEBI working group that has actively contributed to shaping these upcoming regulations.
AlgoBulls provides a wide range of strategies, from off-the-shelf solutions to wholly customisable and dynamic models, to meet different requirements. Even users with zero coding knowledge can tweak pre-built templates to generate tailor-made options. These can be further modified, or new parameters can be added without adjusting the core code. Seasoned traders and traditional/small brokerages can leverage these solutions to develop their algorithms.
It has integrated the APIs (application programming interfaces) of several broking houses across India and the US. Hence, anyone with a trading account and an activated algo solution can benefit from automated trading on these platforms when the system finds a match for 'buy' or 'sell'. Additionally, it generates server logs and 'live reports' to establish audit trail for every trading movement.
The platform has introduced extensive backtesting and paper trading capabilities to validate trading strategies before going 'live'. Simply put, these are used to gauge how effectively these strategies will work in different market conditions so that users can assess potential risks and refine parameters.
It has adopted a diversified pricing structure to cater to retail traders, brokers and enterprises of all sizes. The revenue model has been designed to deliver flexibility and value, aligning with the varied requirements of platform users (more on that later).
AlgoBulls has attracted significant investor backing, securing $ 2 Mn in January 2023 during its pre-Series A round led by VCats++, an investor network funding early stage ventures across sectors. The startup raised INR 2 Cr in 2020 from the same lead investor. VCats++ combines funding with mentorship and networking opportunities to help founders drive growth and scale their businesses effectively.
Advantage AlgoBulls: Its USP And Evolving Tech Stack
The journey of AlgoBulls started with a vision: To make tech-driven algorithmic trading accessible to all because of its transformative potential. After graduating from IIT-Delhi, Dagade moved to Bengaluru, where a chance introduction to trading by his colleagues sparked his interest.
"Initially, we were looking at a large block [read application], but soon realised that the pragmatic approach would be to develop more targeted services to cater to different users," the founder and CEO said. "At AlgoBulls, users can create trading strategies from scratch using Python, opt for as-is templates or get modified ones."
Dagade started with a core algorithmic trading engine and a bunch of strategies capable of fetching live market data so that the system could analyse the information and generate trading signals for automatic buying and selling. Over the years, the startup has developed miscellaneous service platforms and strategies. Here is a quick look at AlgoBulls' major offerings.
Platforms for all traders - Odyssey & Phoenix: AlgoBulls lists its pre-built strategies on its curated marketplace called Odyssey and charges monthly subscriptions ranging between INR 499 and INR 3999. There are two more subscription models - Phoenix (INR 1,600-8300 for India, $20-$100 for US) and Phoenix Pro Build (starts from INR 20,000). The first is a customisable powerhouse, enabling users to create, test and execute their strategies. The 'Phoenix Pro Build' version allows traders to turn their unique ideas into actionable strategies minus any coding, as the startup's in-house experts help them throughout the procedure.
An advanced AI tool - Phoenix Copilot: All AI-generated trading strategies are developed using Phoenix Copilot. For instance, a user can describe his/her trading strategy in simple English and say: Buy if the stock rises above the 200-day moving average and sell if it falls below. Once the parameter is specified, AlgoBulls' AI-powered tool generates a sophisticated algorithm for auto-trading.
Phoenix Copilot is primarily trained on indicator-based strategies for equity and options to identify potential entry and exit points. However, it is constantly refined to optimise algos, ensure the accuracy of predictive analytics and provide personalised insights based on historical and live market data.
"AlgoBulls also offers adaptive algorithms to dynamically adjust trading parameters with shifting market conditions such as changes in volatility and volume. These algos help users seize opportunities and minimise risk," said Dagade. "Again, for certain strategies, we use machine learning to detect anomalies and outliers, alert users in real time and safeguard investments. Our AI tool will increasingly support more complex strategies and Indic languages, starting with Hinglish."
White-label partnerships and Enterprise setups: While its subscription-based models are available as SaaS offerings, AlgoBulls also provides white-label solutions (costs INR 50K onwards) and enterprise setups (INR 3 Lakh and above) for brokers, RAs, RIAs, small-medium-to-large hedge funds, fund managers and fintech companies operating in wealthtech space. These setups are hosted on client servers/cloud infrastructure and ensure complete customisation, control and scalability.
The startup claims 75% of its enterprise revenue comes from these custom setups and the remaining 25% from white-label solutions. Enterprise business accounts for 65% of its total revenue, and retail subscriptions contribute the remaining 35%, demonstrating a well-rounded revenue model that balances institutional and individual traders.
The Five Pillars Of AlgoBulls' Performance
In the high-stake financial markets, the likes of AlgoBulls are quickly becoming a darling of retail traders, wresting the stock market away from the traditional gatekeepers and letting people trade. However, putting huge amounts at risk requires responsible trading, even at the algo level, with zero human intervention. Hence, the startup has built its service platforms on five core pillars. These include:
Robust infrastructure: At AlgoBulls, each strategy operates on a virtual server, avoiding resource contention and maximising efficiency. The cloud-based platform also eliminates concerns about local hardware, network downtimes, or resource limitations.
IP protection for strategies: The platform employs proprietary formatting to safeguard user-developed strategies. The strategies generated here remain secure as these cannot be transferred to or run on other platforms.
Low-latency, high-speed execution: AlgoBulls has optimised its low-latency setup for low- and mid-frequency trading, thus ensuring high-speed execution. This speed advantage is critical for highly time-sensitive algo trading, as the goal here is to capture fleeting market opportunities with precision.
Guardrails for risk management: It has incorporated robust risk management tools such as exposure limits, position monitoring, order controls and stop-losses to ensure disciplined trading. It also provides detailed transaction logs and performance reports in sync with compliance norms for easy tracking and monitoring.
Regulatory compliance: AlgoBulls has a compliance-first approach and strictly adheres to SEBI regulations (in India), the SEC (in the US) and other jurisdictions where it plans to operate. Its compliance framework also covers risk management protocols, data privacy measures, internal audits and real-time monitoring systems, strategies and user activities for a secure trading experience.
AlgoBulls' Vision For The Future
According to Dagade and his team, AlgoBulls has gone beyond a fintech platform that demystifies algo trading. It is building a thriving community, conducting 'Quant Quest' competitions for algo trading across IITs and other institutes, educating the next generation of algorithmic traders and democratising access to wealth.
In fact, it is high time for algo trading to take off in India. Despite the rise in overall retail trading, around 50% of the trade volume is automated here compared to 80-90% globally. Moreover, the record increase in demat accounts - the total number surged to 17.5 Cr in September 2024, according to Motilal Oswal - underscores the potential for algo trading. The newbies and the professionals flooding the market will require technical leverage to drive inclusion and profitability.
Globally, the algorithmic trading market is expected to hit $33.9 Bn in 2028 from $20.5 Bn in 2024. On the other hand, India's algorithmic trading market is estimated to see a CAGR of 11.65% between FY25 and FY32, growing from $1.08 Bn to $2.6 Bn in FY32.
Realising the scope for empowering a new generation of investors, AlgoBulls aims to grow its product portfolio and enhance platform capabilities by integrating advanced AI-based features. It will also explore more complex multi-asset and multi-market strategies and expand its global footprint across North America, the EU and the Asia-Pacific.
In the long term, the fintech startup wants to provide easy access to high-frequency trading (HFT) and introduce ASIC- and FPGA-powered algo trading via web browsers. While ASIC chips, short for application-specific integrated circuits, are optimised for specific tasks, FPGAs, or field programmable gate arrays, are more flexible and easily reconfigured to adapt to market shifts.
It will also continue to work on educating retail users, forging strategic alliances with brokers, refining personalised investment strategies and upholding rigorous global compliance and risk management standards.
Global financial markets are changing fast. Automated algo trading will work well in India, or any market, for that matter, if new-age platforms like AlgoBulls can devise ingenious strategies and develop sophisticated trading algorithms.
