About BacktestIndia

2006-2008: The Observer Phase

My investing story started in 2006 during my second year of B.Com in a small town in Gujarat. I didn't have capital—my grandmother wisely prohibited investing while studying—but I became obsessed with tracking our family's portfolio.

Every day, I'd check Reliance and L&T prices. The 2006-07 bull run felt magical. Watching those numbers climb was intoxicating, even though it wasn't my money.

Then came 2008. I watched our family portfolio get cut in half.

First lesson learned: Bull markets don't last forever. You need more than "buy good companies and hold."

Looking back, my grandmother's rule was brilliant. I learned about market volatility without losing my own money—a rare gift.

2009-2013: The Excel Obsession

Shaken by 2008, I became obsessed with finding a "systematic edge." During my MBA Finance years, I started downloading historical NSE EOD data and analyzing patterns on Excel.

I attempted Chartered Accountancy alongside my MBA (didn't complete CA, but the financial accounting rigor shaped my analytical approach).

After analyzing 1995-2009 data, I discovered a gap trading pattern that showed consistent profits across 14 years. On paper, it looked bulletproof.

Spoiler: Historical patterns in Excel ≠ Live market reality. But I wouldn't learn that until I had real capital at risk.

2013-2017: The Reality Check (My Money This Time)

After securing employment, I finally had capital to trade. This time, it was my money—not a family portfolio I was observing.

I implemented my gap trading algorithm from 2013-2017.

The thrilling part: In 2015, I grew ₹50,000 to ₹3.27 lakhs in just 5 months. I thought I'd finally cracked the code.

The humbling part: That ₹3.27 lakhs shrank to ₹70,000.

Transaction costs, slippage, and emotional execution errors destroyed what looked perfect in historical data. The intraday data crunching taught me invaluable lessons about pattern recognition vs. curve fitting, overfitting to historical data, the discipline required for systematic execution, and why most "proven systems" fail in live markets.

The emotional weight of losing your own hard-earned salary is incomparable. Exhausted and humbled, I stopped active trading. But I didn't stop studying markets.

2017: The Turning Point - Academic Clarity

Frustrated with trading failures, I was searching for a more disciplined approach. That's when I connected with Professor Mayank Joshipura, Associate Dean at NMIMS Mumbai.

Professor Joshipura's academic work on factor investing opened my eyes to systematic strategies backed by decades of research. But what really helped was our conversations where he patiently clarified my doubts about low volatility investing.

These readings clarified my thinking: Markets are more random than we believe, and systematic approaches beat discretionary stock-picking over long periods.

His guidance helped me shift from failed trading strategies to evidence-based factor investing approaches with proper risk management.

Due Diligence: Trust, But Verify

After my trading disasters, I was skeptical of everything—even PhD research. Following Professor Joshipura's guidance, I spent months independently backtesting low volatility strategies using NSE historical data.

The results matched the academic literature:

• Lower absolute returns than aggressive strategies
• Dramatically better risk-adjusted returns
• Shallower drawdowns (-44% vs. market's -55%)
• Faster recovery times (7 months vs. 60 months)

Satisfied with my own analysis, I implemented a systematic low volatility approach in 2017, investing a significant portion of my inheritance based on verified academic research.

This wasn't blind faith—it was verified conviction. The academic research aligned with my independent backtests, and I was ready to put real capital behind it.

2017-2024: Diversification & Deep Research

Implementing systematic strategies taught me another critical lesson: diversification beyond equities.

In 2018, following academic guidance on asset allocation, I purchased Sovereign Gold Bonds when they were trading at attractive rates. I still hold those SGBs today in 2025—haven't sold a single unit. That gold allocation provided stability during equity market volatility.

Key lesson: True risk management isn't just low volatility stocks—it's asset allocation across uncorrelated instruments.

The Research Itch: Low Scaled Turnover Discovery

While my portfolio was on autopilot with systematic low volatility, I couldn't stop analyzing data. The question haunted me: Could you combine low volatility's defensive characteristics with momentum's growth capture?

After hundreds of backtests, I discovered something interesting: Low scaled turnover stocks performed exceptionally well.

What is scaled turnover?
Turnover = (Volume of shares traded × Average price) / Market capitalization

Low scaled turnover identified "boring, ignored stocks"—companies with low trading activity relative to size. These stocks boosted BOTH momentum and low volatility factor performance.

I wrote an academic paper documenting these findings.

The rejection: Researchers in China had published similar findings on liquidity factors first.

The validation: My independent research had replicated findings from global institutions. I was on the right track, even if I wasn't first.

2024: Building BacktestIndia (with Ishani Desai)

After 18 years—from watching family portfolios crash to losing my own trading capital to finally finding systematic factor investing—I realized something critical:

The tools I needed to learn these lessons faster never existed for Indian retail investors.

Every backtesting platform either ignored India's LTCG/STCG tax structure (making results meaningless), used survivorship-biased data (overstating returns by 30-50%), assumed frictionless trading (ignoring real-world costs), or cost thousands of dollars monthly (pricing out retail investors).

So I taught myself Python and Streamlit from scratch and spent 2 months building the backtesting engine.

Ishani Desai, founder of BacktestIndia.com, shares the vision of democratizing systematic investing education for Indian retail investors. Together, we built a platform that represents:

• 18 years of painful lessons (2008 observation, 2015 trading collapse, 2017 breakthrough)
• Intraday trading discipline (understanding overfitting and curve-fitting)
• Academic rigor (learned from Professor Joshipura's factor research)
• Practical validation (my inheritance invested using systematic low volatility approach)
• India-specific focus (LTCG/STCG modeling, survivorship bias handling, realistic costs)