Our Multi-Factor Dynamic Quantitative Algorithm (QMIM) aims to build long-term wealth for clients over 5-10 years, focusing on stocks with strong momentum and other key factors from the NSE 750 universe. This dynamic strategy protects capital during downturns with effective risk management. The portfolio, limited to 10 stocks, is rebalanced quarterly and may hold cash equivalents like liquid bees when necessary. We recommend allocating 10-20% of your total portfolio to this algorithm for potential significant returns and balanced risk management.
Our Multi-Factor Dynamic Quantitative Algorithm (QMIM) aims to build long-term wealth for clients over 5-10 years, focusing on stocks with strong momentum and other key factors from the NSE 750 universe. This dynamic strategy protects capital during downturns with effective risk management. The portfolio, limited to 10 stocks, is rebalanced quarterly and may hold cash equivalents like liquid bees when necessary. We recommend allocating 10-20% of your total portfolio to this algorithm for potential significant returns and balanced risk management.
Sankalp Krishnan
7+ years experience
Sankalp is an accomplished Advisor with a Bachelor of Engineering (BE) degree in Computer Science from Mumbai University and a Master of Science (MS) degree in Financial Engineering from the University of Illinois at Urbana-Champaign, USA.
With over 7 years of experience in Quantitative Trading, Portfolio, and Risk Management, Sankalp has honed his expertise in these fields. He has spent the last four years as a consultant for a proprietary trading firm based in New York, where his technological proficiency has been crucial in managing risk and navigating through volatile markets.
Sankalp's proficiency extends to developing automated trading strategies based on back-testing frameworks, focusing on intraday long/short positions in US equities and futures. He is responsible for managing a portfolio of strategies within a designated account, ensuring optimal performance and risk management.
Sankalp is an accomplished Advisor with a Bachelor of Engineering (BE) degree in Computer Science from Mumbai University and a Master of Science (MS) degree in Financial Engineering from the University of Illinois at Urbana-Champaign, USA.
With over 7 years of experience in Quantitative Trading, Portfolio, and Risk Management, Sankalp has honed his expertise in these fields. He has spent the last four years as a consultant for a proprietary trading firm based in New York, where his technological proficiency has been crucial in managing risk and navigating through volatile markets.
Sankalp's proficiency extends to developing automated trading strategies based on back-testing frameworks, focusing on intraday long/short positions in US equities and futures. He is responsible for managing a portfolio of strategies within a designated account, ensuring optimal performance and risk management.
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