What we teach, learn, and share about Quant Trading

Why volatility can create long-term returns while also forcing investors out before those returns are ever realized.

Ish Singh•7 November 2026•2 min read

A note on why great-looking historical performance can be fragile, and why robust backtests matter more than perfect ones.

Ish Singh•31 October 2026•2 min read

How quant strategies begin with hypotheses, then move through disciplined definition, testing, and validation.

Ish Singh•24 October 2026•2 min read

Why the investing versus trading debate misses the bigger question: whether decisions are driven by stories or evidence.

Ish Singh•15 October 2026•2 min read

Srinivas Lakkireddy, Sr. Lead Architect at JPMorgan & Chase, shares how the Foundations cohort helps transition technical leadership to portfolio-level systematic trading.

Srinivas Lakkireddy•19 June 2026•2 min read

A view on how elite degrees, alternative credentials, AI, apprenticeships, and real-world portfolios may split the future of education.

Ish Singh•12 April 2026•2 min read

Piyush Gupta, Senior Flow Trader at Delta Exchange, shares how the Foundations course builds problem-solving intuition and strategy robustness.

Piyush Gupta•23 February 2026•2 min read

Rakshit Tiwari (ElevenLabs, ex-Stripe, IITG) reflects on building a repeatable hypothesis-testing process and moving away from gut-feel trading.

Rakshit Tiwari•6 February 2026•2 min read

Vishal N. (IIT Kanpur / Erasmus University) details why QuantYog provided more practical value than quantitative Master's programs and the CFA exams.

Vishal N.•30 January 2026•3 min read

Vineeth S, Google ML engineer, discusses moving from retail curiosity to institutional-grade research and systematic strategy design.

Vineeth S•26 January 2026•2 min read

Why QuantYog's next phase is about scaling impact through software and AI agents instead of simply adding headcount.

Ish Singh•1 January 2026•2 min read

A short risk-first read on why the nof1.ai trading experiment exposed serious drawdown and risk-adjusted-return failures across LLM traders.

Ish Singh•4 November 2025•1 min read

QuantYog crosses 100 students with consistently strong ratings, while staying focused on mentoring serious learners into real quants.

Ish Singh•9 October 2025•1 min read

Shivam Kathuria, Product Manager at JPMC, shares his experience in the QuantYog Essentials cohort and how it helped build institutional-grade systematic trading conviction.

Shivam Kathuria•14 September 2025•2 min read

Rajat Kumar, Software Engineer III at Walmart, highlights how QuantYog Essentials distills complex institutional concepts into an efficient roadmap.

Rajat Kumar•26 August 2025•2 min read

Why Calmar can be a more intuitive risk-adjusted return metric than Sharpe when drawdowns, leverage, and survival matter.

Ish Singh•24 August 2025•2 min read

Sagar Saluja, BITS Pilani alum, shares his journey from retail option trading to designing robust, data-driven systematic research tools.

Sagar Saluja•15 August 2025•2 min read

A blunt note on the unrealistic promises in trading education and why QuantYog chooses honesty over easy marketing.

Ish Singh•10 August 2025•1 min read

Why renewing QuantYog.com for nine more years is a commitment to tackling India's trading education and financial literacy crisis.

Ish Singh•3 August 2025•3 min read

Anshul Goel, Quantitative Strategist at Goldman Sachs, explains how QuantYog Foundations bridges the gap between academic MFE programs and real-world trading.

Anshul Goel•9 May 2025•1 min read

Anshul Pokharna (IB / M&A / CQF) contrasts theoretical quantitative programs with the sharp, actionable insights of QuantYog Foundations.

Anshul Pokharna•6 May 2025•1 min read

Ankith Singh Malik, Data Engineer at PayPal, details how the Foundations course provides institutional rigor for data professionals.

Ankith Singh Malik•4 May 2025•2 min read

Manny J., ML Engineer at DOMYN, explains why QuantYog Foundations is "takda" and highly valuable for machine learning and AI experts.

Manny J.•3 May 2025•1 min read

A trading simulation showing how a small negative edge can make most retail traders lose money while a lucky few mistake randomness for skill.

Ish Singh•22 April 2025•2 min read

A reminder that automation without guardrails is not scale; it is fragility moving faster.

Ish Singh•13 April 2025•1 min read