Founder & CEO
Ayush Pandey
Treats every backtest as a claim to disprove, from the first data pipeline to the published paper.
Ayush Pandey is a quantitative researcher and software developer who has tested 150+ trading strategies, published quantitative research on SSRN, and builds systematic trading systems from the ground up.
His work spans the entire quantitative research lifecycle — from data engineering and backtesting to walk-forward validation, Monte Carlo simulations, risk analysis, and institutional-grade performance reporting.
He focuses on leveraged trading systems, algorithmic strategy design, and quantitative portfolio research, combining mathematical modelling with production-grade software engineering across Python, C++, and Flutter.
- In systematic trading research1
- ~3 yrs
- Strategies tested1
- 150+
- Building software and hardware2
- 4+ yrs
- Projects shipped2
- 15+
- SSRN papers2
- 2
1 Founder’s quantitative research
2 Ayush Pandey, personal site (2026)
Research
Published papers.
June 2026
Optimal Leverage Sequencing in Leveraged Dollar Cost Averaging: Theory and Multi-asset Evidence
Proves that, for a fixed total leverage over a DCA schedule with falling entry prices, an increasing leverage sequence uniquely minimises the weighted average entry price. Tested on gold, Bitcoin and the NASDAQ.
October 2025
A Dynamic DCA-Leverage Algorithm for Optimized Average Positioning and Reduced Liquidation Risk
Pairs a drawdown-based DCA schedule with an increasing leverage sequence, so larger positions are taken at lower prices with a safer liquidation buffer than uniform or decreasing leverage.
Projects
Selected open-source work.
Crypto agent reverse-engineering
A Binance perpetuals backtester with fees, spread, funding and liquidation, plus bias audits, walk-forward and Monte Carlo validation.
Crypto options latency arbitrage
Live three-exchange research into whether Binance and Bybit options lag Deribit, with latency-aware paper trading and real fees.
Momentum survivorship audit
A pre-registered audit of cross-sectional crypto momentum on a point-in-time universe, with Deflated Sharpe, PBO and walk-forward tests.
Futures curve intelligence engine
Detects futures-curve mispricing, classifies market regimes and validates signals through walk-forward backtesting.
Best averaging and leveraging
Proof and backtest code for optimal leverage sequencing in leveraged DCA strategies.
Indian options backtest study
Backtests NIFTY and BANKNIFTY weekly options with a full Indian cost model, and shows how look-ahead bias can fake a perfect win rate.
Talk to the team.
Early access, partnerships or press.