This hackathons is only open to students. Double check the event page for more information as this may mean only those from a particular university/country are eligible.
Event Type
online
1,654
Participants
148
Est. Projects
Organizers
Alex Johnson
alex@example.org
Jamie Rivera
jamie@example.org
Sam Chen
sam@example.org
Quality Score
Quality Score
72/100
High confidence
Organiser16/20
Event Maturity14/20
Sponsors18/25
Participants12/20
The QuantQuest algorithmic trading challenge is being held as part of E-Summit '26(Xpecto), IIT Mandi. This event is designed for aspiring quantitative analysts and traders to test their mathematical models and experience the complexities of real-world market dynamics. Over a 48-hour window, participants will develop, backtest, and submit robust trading strategies. This competition provides an excellent opportunity to apply quantitative finance knowledge to real datasets and showcase data-driven problem-solving skills. The problem statement for this hackathon will be released on 14th March at 00:00 AM. Event Details Date: March 14th – 15th, 2026 Mode: Online Time: 48-Hour Window Submission: Online (Google Form Submission) Team Size: Individual participation only (1 member). Eligibility: Open to all college students (undergraduate, postgraduate, or master's) Rules: Students can participate in only 1 submission. Rules & Regulations Internet usage and external libraries for coding are permitted. Originality of the trading logic and clarity of the algorithm will be prioritized. All assumptions regarding slippage or transaction costs must be explicitly stated. Late Submissions: Teams must adhere strictly to submission deadlines. Late submissions will attract a huge penalty or immediate disqualification. Any form of plagiarism or unfair practices will lead to immediate disqualification. Participants are expected to maintain professionalism and ethical conduct throughout the event. Scoring & Judgement Criteria Evaluation will be on the basis of quantitative performance(60%) and report(40%): Sharpe Ratio (Risk-adjusted return) Maximum Drawdown (Risk and resilience) Annualized Return & Volatility. Strategy Robustness Explainability & Financial Logic Code quality & reproducibility