Tag: Quantconnect

  • Best AI Tools for Portfolio Management to Make Investing Smarter

    AI technology is redefining investment in that it makes the processes faster, simpler, and wiser. In fact, these innovations tend to churn vast amounts of data through machine learning, define optimal asset mixes, and execute trades quickly and carefully. Investors can expect intelligent guidance, automatic adjustment of position sizes, and plans that change markets. It captures a large amount of external data that provides invisible analytics. Reducing manual work and embedding behavior insights give even professional and beginner investors a definite advantage. The result will be a sleek and sustainable increase in portfolios that have the potential for significant scaling up.

    Tool Unique Features / Differentiators Target Audience / Best Use Case Key Strengths Limitations / Challenges
    Bloomberg Terminal Built-in chat for teams, mobile app, proprietary & third-party research Finance professionals needing real-time market data & trading tools Comprehensive market coverage, risk analytics, alerts Expensive, complex for beginners
    Alphasense AI summaries, tone checks, Smart Synonyms™, ESG checks Businesses, investors, researchers for market intelligence Fast document/data search, expert insights Limited visualization, collaboration restricted
    Finbox Automated cash flow/dividend models, API & Excel integration Investors & analysts needing valuation models & screeners Instant fair value estimates, curated portfolio ideas No direct broker integration, limited data export
    Betterment Goal-based investing, smart-beta & factor-based options Robo-advising & personal investors Tax-loss harvesting, easy app tracking Premium features for high-balance accounts only
    QuantConnect Open-source LEAN engine, Python/C# API, 15k+ backtests/day Quant researchers & developers for algorithmic strategies High scalability, backtesting, live trading Setup challenging for beginners, extra cost for datasets
    Wealthfront Direct indexing, FDIC-insured cash accounts, custom portfolios with crypto Digital-first investors seeking robo-advisory Automated portfolio creation, low fees No human advisor, limited mutual fund options
    NumerAI Crowdsourced AI models, staking with Numeraire (NMR) Data scientists & quantitative analysts Encrypted data, low fees, global talent pool Requires coding/data skills, only hedge fund exposure
    Nitrogen Wealth Automated Risk Number, AI-generated proposals, sandbox testing Financial advisors & wealth management firms Risk monitoring, client engagement, CRM integration Advisor-focused, not for direct retail investors
    Plaid  Aggregates 12,000+ financial institutions, fraud checks, wealth APIs Developers & fintech firms Flexible APIs, cross-platform integration Some features enterprise-only, add-ons may cost extra
    EidoSearch Predictive analytics, pattern detection, backtesting Institutional investors, quant researchers Custom asset strategy search, visual analytics Professional-level, IT support often required

    Bloomberg Terminal

    Website bloomberg.com/professional/terminal
    Rating 4.6
    Free Trial No
    Best For Finance professionals needing real-time market data, news, analytics, trading, and communication tools.
    Bloomberg Terminal - Best AI Tools for Portfolio Management
    Bloomberg Terminal – Best AI Tools for Portfolio Management

    Bloomberg Terminal, being an AI-powered solution for investing, ensures that decisions are taken quickly and smoothly by providing real-time market data, instant news, and intelligent tools to help with wise decisions. It has made tough jobs easy with AI insights, risk analytics, and personalized views. Spot chances, cut down risk, and act fast within the system. Speedy action is triggered by built-in reporting, alerts, and datasets. Teams stay linked via Built-in chat; one can keep updated while on the go with the mobile application. Strong tracking capabilities report on a portfolio’s performance, assisting users with refining and growing returns. In fast markets, the Bloomberg Terminal makes all work simple, sharp, and effective.

    Pros

    • Quantitative analysis of market data in real-time 
    • Broad range of tools for risk and performance attribution 
    • Insight from both proprietary and third-party research, 

    Cons

    • Expensive for smaller firms and individuals 
    • Model complexity may require training for a new user.

    Pricing

    Bloomberg Terminal offers custom pricing; contact them for a quote.

    Alphasense

    Website alpha-sense.com
    Rating 4.7
    Free Trial No
    Best For Businesses, investors, and researchers using AI-powered market intelligence, document search, and financial insights.
    Alphasense - Best AI Tools for Portfolio Management
    Alphasense – Best AI Tools for Portfolio Management

    Alphasense is powered by AI for fast investing through pulling insights from millions of reports, calls, and filings in seconds. Its smart tools consist of AI summaries, tone checks, and the Smart Synonyms™, which help managers to easily track trends, test ideas, and spot risks. For example, the platform enables one to model data into key numbers and set up auto reports. All deep research has been cut down to little. Both top and bottom reviews become simple and fast. The artificial intelligence machine learning, joined with the viewpoints of experts, smooths workflows, takes care of ESG checks, and has alerts to provide guidance in almost real time. 

    Pros

    • Speedy document and data searching.
    • AI summaries and chat-based research.
    • Integrated insights from experts and brokers

    Cons

    • Limited visualization tools. 
    • Collaborate only with licensed users

    Pricing

    Alphasense offers custom pricing; contact them for a quote.


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    Finbox

    Website finbox.com
    Rating 4.7
    Free Trial Yes
    Best For Investors and analysts needing AI-assisted valuation models, screeners, watchlists, and financial modeling tools.
    Finbox - Best AI Tools for Portfolio Management
    Finbox – Best AI Tools for Portfolio Management

    Finbox is a cloud AI platform that performs stock research in record time and with minimum effort. With coverage of over 100,000 global stocks, it provides fair value estimates instantaneously based on an automated cash flow and dividend model. Users can filter through more than 1,000 financial metrics to pinpoint the data they require with utmost precision. The platform also enables investors to vet top portfolios for investment ideas. Data can be effortlessly transferred to Excel or accessed via APIs, while an intuitive dashboard organizes the tools for both beginner and professional users under one roof. Custom watch lists, price alerts, and historical data facilitate rapid testing and feed into better strategies.

    Pros

    • Automated Value Models, offering an instant fair value 
    • Direct access through Excel and custom API access 
    • Ideas curated from the portfolios of premier investors. 

    Cons 

    • Absence of direct broker integration for live execution. 
    • Data export is very limited without upgrades.

    Pricing

    Finbox offers custom pricing; contact them for a quote.

    Betterment

    Website betterment.com
    Rating 4.8
    Free Trial Yes
    Best For Robo-advising, goal-based investing, tax-loss harvesting, and cash management.
    Betterment - Best AI Tools for Portfolio Management
    Betterment – Best AI Tools for Portfolio Management

    Betterment uses artificial intelligence to make portfolio management hassle-free and automatic. The firm combines tax-loss harvesting, strategic portfolio rebalancing, and goal-based investing with ETF diversification and some personalization. Through smart algorithms, asset allocation gets adjusted as goals work through changes or the market takes its own shape, thereby keeping portfolios low-risk and on track. Investors may watch growth in real-time, set up screens for social impact, and explore smart-beta or factor-based options for extra returns. The platform engages simplicity and insight to allow novice and advanced users to invest with confidence. With app-based access, people can check returns, get advice, and act on plans anytime, turning investing, saving, and wealth building into a smooth and guided process.

    Pros

    • Affordable, transparent fees 
    • Real hands-off automation with tax-loss harvesting
    • App-based goal setting and available for tracking 24/7. 

    Cons 

    • Financial planning has premium prices in premium plans. 
    • Advanced features are only available to high-balance accounts

    Pricing

    Plan Pricing
    Individuals $0–$20K Balance → $4.1/month
    Employers Request for Proposal (RFP)
    Advisors Request for Proposal (RFP)

    QuantConnect

    Website quantconnect.com
    Rating 4.7
    Free Trial Yes
    Best For Quantitative researchers, developers, and traders building, backtesting, and live-trading algorithmic strategies across multiple asset classes via an open-source engine (LEAN).
    QuantConnect - Best AI Tools for Portfolio Management
    QuantConnect – Best AI Tools for Portfolio Management

    QuantConnect is an open-source artificial intelligence platform for trading and portfolio strategy design that allows users to build, test, and run automated strategies in stocks, forex, crypto, and options. The cloud infrastructure can run over 15,000 backtests a day, complete with real-time risk checks and robust broker integrations, and there is also an API in either Python or C# for configuring custom signals. Traders can benefit from many extensive datasets, Jupyter notebooks, and tools for live trading with automated reconciliation. The platform also enables group activities, licensing from Alpha Stream, and heavy portfolio analytics, making life easier for both small traders and capital allocators in developing scalable, event-driven strategies. 

    Pros

    • Highest scalability and fidelity with respect to backtesting 
    • Open-source nature and community support, and monetization options 
    • Cloud notebook and API are available for custom modeling 

    Cons 

    • Setting up code for beginners could prove challenging 
    • Extra charges for specialized datasets

    Pricing

    Plan Pricing
    Researcher $60/month
    Team $120/user/month
    Trading firm $336/user/month
    Institution $1080/user/month

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    Wealthfront

    Website wealthfront.com
    Rating 4.4
    Free Trial No
    Best For Digital-first investors seeking robo-advisory services including automated investing, tax-loss harvesting, goal-based planning, and high-yield cash management.
    Wealthfront - Best AI Tools for Portfolio Management
    Wealthfront – Best AI Tools for Portfolio Management

    Wealthfront is an AI-driven wealth builder, so investors can build and configure portfolios without being overburdened by difficult tasks that diminish their time. The thing about a Wealthfront account is that the system itself can create a designated account and place one’s money into stocks, groups of stocks, bonds, ETFs, REITs, cryptocurrencies, or social-responsibility funds allocation, which will change over time as the market changes or new money is deposited. The app offers high-yield cash accounts, smooth movement of funds, and FDIC insurance up to $8 million. With direct indexing for Wealthfront accounts over $100,000, users can unlock a significantly higher growth rate by crushing the taxes.

    Pros 

    • low fee of 0.25%, and the minimum investment is $500. 
    • Tax-loss harvesting takes place every day for every account. 
    • Custom portfolios with fractional shares and some crypto exposure. 

    Cons

    • There is no human advisor to talk to. 
    • Limited direct mutual fund options or trading flexibility.

    Pricing

    Plan Pricing
    Annual Advisory Fee 0.25% annually

    NumerAI

    Website numer.ai
    Rating 4
    Free Trial Yes
    Best For Data scientists and quantitative analysts who want to build machine learning models, compete in stock-prediction tournaments, stake models with Numeraire (NMR), and potentially earn rewards.
    NumerAI - Best AI Tools for Portfolio Management
    NumerAI – Best AI Tools for Portfolio Management

    NumerAI is an unusual hedge fund that works with machine learning in a crowdsourcing capacity. Over 100 data science models create predictors to predict the world’s stock markets. This is achieved using encrypted, anonymized datasets with a combination of meta-models, which are designed as the finest choice for the quality of signals being measured by accuracy and diversity. NumerAI delegation gives its signal for prediction assessments for some staking in NMR coins. Those who get lucky receive rewards and can continue in the program. However, those getting down go O.S. and lose their connected NMR tokens, sort of self-correcting in nature from that perspective. 

    Pros 

    • Crowdsourced global data science talent
    • Superior confidentiality, encrypted model submissions 
    • Fees are lower than those of a traditional hedge fund. 

    Cons 

    • Necessary data science or coding skills for contribution 
    • No retail portfolios, hedge fund investment only.

    Pricing

    NumerAI offers custom pricing; contact them for a quote.

    Nitrogen Wealth

    Website nitrogenwealth.com
    Rating 4
    Free Trial Yes
    Best For Financial advisors and wealth management firms seeking AI-driven risk assessment, client engagement, proposal generation, and portfolio analytics.
    Nitrogen Wealth - Best AI Tools for Portfolio Management
    Nitrogen Wealth – Best AI Tools for Portfolio Management

    Nitrogen is an AI-powered platform for advisors to manage risk, design portfolios, and establish client trust. Key elements include automated risk scores (Risk Number), live asset reviews, AI-generated meeting notes, smart proposals, and sandbox testing of new ideas. It integrates with widely used CRMs and planning applications for a smooth workflow. The platform also allows easy onboarding and oversight, providing activity monitoring tools for compliance in real time. Custom analytics, clear reports, and optimized allocations scale advice and keep clients engaged. Nitrogen’s interface brings together automation and insight quickly, allowing advisors to work quickly and clearly-growing and managing portfolios with ease.

    Pros 

    • Automated visual risk and performance monitoring 
    • Integrates effortlessly with Proprietary Tech stacks and CRMs 
    • Real-time asset class drill-down and allocation optimisation 

    Cons 

    • Advisor-focused, unsuited for direct retail investors. 
    • Requires customization training for new users

    Pricing

    Nitrogen offers custom pricing; contact them for a quote.

    Plaid 

    Website plaid.com
    Rating 4
    Free Trial Yes
    Best For Developers and fintech firms needing secure, standardized access to users’ bank data and payment initiation across thousands of institutions.
    Plaid - Best AI Tools for Portfolio Management
    Plaid – Best AI Tools for Portfolio Management

    Plaid links more than 12,000 financial institutions, providing users and advisors with one dashboard to see all their accounts—banking, brokerage, retirement, cryptocurrency, and loans. Their AI tools sort transactions, generate fraud checks, and effectuate cross-platform syncing, hence making portfolio monitoring and risk control a cinch. Wealth APIs feed live data on investments, give real-time previews for liabilities, and accelerate the onboarding experience across apps. Plaid also helps surface trends in spending and saving, thereby facilitating personalized financial advice. The platform is highly flexible and developer-friendly. Considering security, privacy, and identity checks form its core principles, Plaid guarantees compliance while granting clean and reliable insights to investors and advisors about their entire financial picture.

    Pros 

    • comparable variety of accounts for global aggregation 
    • Platform-agnostic, mobile, desktop, and third-party apps compatibility 
    • Developer-friendly with very flexible APIs and analytics 

    Cons 

    • Advanced analytics and add-ons attract further costs. 
    • Availability of selected features only for enterprise clients.

    Pricing

    Plaid offers custom pricing; contact them for a quote.

    EidoSearch

    Website eidosearch.com
    Rating 4
    Free Trial Demo available on request
    Best For Institutional investors, quant researchers, and analysts who want AI/pattern-driven predictive analytics and probability-based decision tools across equities, futures, currencies, and more.
    EidoSearch - Best AI Tools for Portfolio Management
    EidoSearch – Best AI Tools for Portfolio Management

    EidoSearch detects the patterns and forecasts asset moves on behalf of investors, with speed and accuracy, through the scanning of millions of financial time series using advanced AI. Its search engine instantaneously retrieves analogous events in the market, revealing analogs and outcomes to inform active portfolio decisions. The platform produces predictive signals, backtests concepts, identifies periods of risk or opportunity, and allows users to test strategies against custom criteria for the market. It is directly integrated with leading order management systems (OMS) and data feeds in a seamless workflow; sophisticated dashboards and visual analytics make deep market research accessible to any investment team.

    Pros

    • Doing real-time big data action discovery.
    • Custom asset strategy predictive pattern search. 
    • Backtesting and forecast tools with visual analytics. 

    Cons 

    • very institutional and professional. 
    • Customization and integrations may need IT support.

    Pricing

    EidoSearch offers custom pricing; contact them for a quote.

    Conclusion

    AI tools have brought about changes in portfolio management in terms of speeding up the processes, automating some functions, and giving smart insights to investors. In managing investments, they utilize prospective models, risk checks, and large data sets to improve returns while cutting exposure to market swings. Rebalancing is easy under these systems since the strategies adjust according to changing conditions. Clear dashboards and easy access bring advanced investing within reach of more people and remove barriers that once limited smart portfolio design. It offers such powerful backing to new and professional users alike by marrying efficiency with transparency. If any imminent technology advances by made, portfolios will become sharper and flexible.


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    FAQs

    How is AI changing investing?

    AI speeds up investing by analyzing data, automating rebalancing, and reducing risks for smarter portfolios.

    What are some Best AI Tools for Portfolio Management?

    Some Best AI Tools for Portfolio Management:

    • Bloomberg Terminal
    • Alphasense
    • Finbox
    • Betterment
    • QuantConnect
    • Wealthfront
    • NumerAI
    • Nitrogen Wealth
    • Plaid
    • EidoSearch
  • Kuants- Algorithmic Trading Made Easy for Retail Traders

    Company Profile is an initiative by StartupTalky to publish verified information on different startups and organizations. The content in this post has been approved by the organization it is based on.

    Algorithmic trading is quite a buzz word among the stock traders community. People are excited about how a computer program can replace a manual trader in a disciplined, scalable, and automated manner to place trades in the stock markets. Being a technology-heavy method of trading, terms like, arbitrage, NSE server racks, etc., often meet the eye of retail traders. SEBI (Securities and Exchange Board of India) allowed algorithmic trading in India in 2009 and since then it has captured over 50% of the trading volumes in India. A major contribution to this is the HNIs and big brokerage and investment management firms who have access to the technology required to perform algorithmic trading.

    Retail traders are not able to exploit the advantages of algorithmic trading due to the costs of technology involved, that can amount from anywhere between INR 1 to 5 lacs per year. But thankfully, there are startups, that are allowing retail traders also to reap the benefit of algorithmic trading.

    Kuants, a Fintech based in Gurugram, is making algorithmic trading easy for those who cannot code themselves and those who are not comfortable in using the readymade algorithms available in the platform.

    StartupTalky interviewed Kuants co-founder Ayush Gangwar to get an insight into the startup.

    Kuants – Company Highlights

    Startup Name Kuants
    Headquarter Gurugram
    Founders Ayush Gangwar & Mohit Bansal
    Sector Fintech
    Founded 2017
    Parent Organization Meanbox Technologies Private Limited

    About Kuants and How it works
    Kuants Founders/CEO
    Kuants – Name, Tagline and Logo
    How was Kuants Started
    Kuants – Startup Launch
    Kuants – Revenue Model
    Kuants – Funding and Investors
    Kuants – User Acquisition
    Kuants – Startup Challenges
    Kuants – Competitors
    Kuants – Awards & Recognitions
    Kuants – Growth and Revenue

    About Kuants and How it works

    Kuants is a startup that is enabling retail traders to do algorithmic trading in the Indian stock markets in a cost-effective manner through its AlgoLab. Founded in Dec 2017, by Ayush Gangwar and Mohit Bansal, the vision of the startup is to ensure that technology never acts as a constraint ever to a stock trader in exploring the domain of algorithmic trading.

    People can write their own algorithms through the web-based AlgoLab, test it on years of historical data and live trade automatically through a single click from the lab itself. For those who are not tech-savvy, Kuants takes care of the trading on behalf of the users so that the users can gain the most out of their investments.

    The product is a web application that people can simply log in via Google at algolab.kuants.in. Just after login, they are presented with their dashboard from which they can navigate to different sections like the Backtest page, the help center, a SMART marketplace and their previous strategies.


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    Kuants lets users do algorithmic trading in two ways–  

    1. Algorithmic lab: Here users can create their own trading algorithms,  and Backtest on Equity, Futures, Commodities and Forex without any code.  Algorithm lab comes with an In-Built Live Execution system with top brokers across the globe. Besides it also offers the users a chance to earn by sharing the algorithm.
    2. Smart Algorithms lets the users Live trade on verified Algorithms developed by peers. Users are given the flexibility to change the algorithm anytime without any locking period.

    Some attractive features offered by Kuants are–  

    • Simple Process of starting Algorithmic trading: Users can backtest anytime and from anywhere simply by logging in to the account  
    • Easy Result Analysis: Thorough Quantitative coverage is done for every algorithm tested  
    • Professional Tools are provided which facilitates optimization, stress testing, paper trading and large scale backtesting within minutes.  
    • Ready to Trade: each time a backtest is complete, the algorithms are automatically converted to trade ready format.  

    Differing from the conventional backtesting system, Kuants has integrated all the individual components like data feed, backtesting code, result metrics in a prebuilt format.

    Kuants – How it works

    The Key USP is that people can write trading algorithms without having to learn any programming language like C, Python Java, etc.

    Emphasizing on uniqueness of the Platform Ayush says, “We have developed an expression based format that automatically converts simple English language based format into a code. This enables traders and quant researchers don’t need to focus on getting the programming right and they can just focus on the code algorithm development and testing”.


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    Kuants Founders/ CEO

    Kuants is co-founded by two IIT Kharagpur graduates Ayush Gangwar and Mohit Bansal.

    Founders Kuants
    Ayush Gangwar (CEO) and Mohit Bansal (CTO)

    Ayush Gangwar is the CEO of Kuants. He holds a Bachelors and Masters degree from IIT Kharagpur. Prior to founding Kuants, he used to work as a part-time Research Consultant at WorldQuant LLC, successfully developing trading algorithms for the US stock markets for a period of 3 years.

    Mohit Bansal is the CTO of Kuants. Prior to joining Kuants, Mohit worked as a data scientist.

    The name “Kuants” is a derivative of quantitative researches and IIT Kharagpur. Ayush credits a lot of his work to his alma mater and the idea of attaching the initials with what the company software does looked convincing enough and also acted as a small gesture to IIT Kharagpur from the founder.

    The tagline, being ‘Where Trading meets Technology’, represents the vision and approach of the company. The logo has been designed with the concept of two different vertices being combined together at the single platform that is Kuants.

    How was Kuants Started

    Kuants was instituted with a view to solving the hassles that the founders themselves faced while doing algorithmic trading.

    “Algorithmic trading needed a lot of programming, and utmost accuracy needed to be maintained in the entire process from start to end and. The maintenance of the code also was a task in itself which took away the focus from trading to developing the technology behind trading. From this experience, it was decided to create a common platform that trades and quantitative researchers can use focusing only on the trading part rather than technology infrastructure” says Ayush.  


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    Kuants – Startup Launch

    Kuants launched the first version of Algolab, then simply known as backtesting system through a press release in June 2018.

    “Algolab’s launch garnered a lot of attention and was instrumental in getting the awareness of our product to the correct target audience. After months of hard work put in by the tech team of developing the backend architecture, it was good to see the amount of traffic we were able to handle that day” Ayush recounts.

    Again, for the first 3 months, the company offered all services on a free-trial basis, which helped it acquire customers and customer feedback.

    Kuants – Revenue Model

    Kuants has taken a freemium approach to its Algolab, with basic features free and premium features of a monthly charge of INR 1999. In the premium version, people can do extensive backtesting as well as live trading on their algorithms in the stock markets, by opening a DEMAT account.

    Kuants has tie-ups with Motilal Oswal Securities Ltd (MOSL) as a sub-broker, so the users need to open the  DEMAT account with MOSL for trading through Kuants. Besides earning revenue from the users, Kuants also earns revenue through Brokerage sharing model with MOSL and by trading its own captive money.

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    Kuants – Funding and Investors

    Kuants raised two round of seed funding till date.

    Funding Date Funding Stage Funding Amount Investor
    November 2017 Seed Undisclosed India Accelerator
    Jaunary 2018 Seed 50 Lacs Mr. Pankaj Chpra & Mr. Ankush Gupta

    Kuants – User Acquisition

    For Kuants, organic marketing techniques have worked really wonders to attract customers while interesting email campaigns are created to retain these customers.

    As Ayush says – “The money we have spent till date is only for the email campaigns and that’s because our user base grew exponentially that our email services provider refused to handle that many volumes of email ids and content for free. We would say it’s a problem we loved to have”


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    Kuants – Startup Challenges

    A major challenge was to keep the pricing of the Algolab well within the reach of a retail trader. Transforming a technology that costs around INR 1,00,000 to something that will cost around INR 16000 per year, that is an 84% drop, needs innovative technology methods and implementations that provide a better experience. After numerous sessions of brainstorming, the Kuants team was able to develop the product which is affordable for retail traders.

    Kuants – Competitors

    Streak, Quantopian, Quantconnect, Amibroker are a few competitors of Kuants.

    Having a competitor is always a blessing as it always enables a startup to do something bigger and better, that repeats as a positive and growth-oriented vicious circle for the industry. – Ayush


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    Kuants – Awards & Recognitions

    Kuants was selected by Morgan Stanley, the global financial technology giant for its CTO Summit, held in Oct 2018. The company was selected from among over 120 startups across Asia working in the fintech domain. The team presented its products and offering to the reveiw committee and was well lauded for its efforts and technological innovation.

    Kuants – Growth and Revenue

    Kuants launched the first version of the backtesting system in July 2018 and has seen an impressive month on month organic growth of 17% in users. Over 20,000 algorithms have been back tested till date(2019) on over 45000 years of data and have generated a trading turnover of INR 30 crore till date through its platform.

    Kuants aims to achieve monthly recurring revenue of Rs 67 lakhs and Rs 3.7 crore in the financial year 2019 and 2020 respectively.