Video summary

You Will Be Shocked To See This Portfolio's Returns |Asset Allocation |Weekend Investing | Alok Jain

Main summary

Key takeaways

Finance

Core Idea / Recommendation

  • Build a 3-asset portfolio consisting of:
    • Indian equity
    • Gold (tracked in INR terms)
    • US equity (Nasdaq 100) (also converted to INR for comparison)
  • Rebalance once per year at the end of each year, returning the portfolio to its starting target weights.
  • The purpose is to:
    • Avoid chasing last year’s winners (FOMO)
    • Reduce drawdowns and volatility
    • Improve risk-adjusted returns

Disclosures

  • Includes a general “Disclaimer as always, please read fully” statement.
  • No explicit “not financial advice” line appears in the provided subtitles beyond the general disclaimer.

Assets / Instruments Mentioned

  • Indian equity (benchmarks referenced)
    • Nifty (mentioned)
    • CNX 500 (mentioned)
    • Described as a basket spanning large cap + mid cap + small cap (via multiple Indian indices; exact tickers not specified)
  • Gold
    • Treated in INR terms
  • US equity
    • Nasdaq 100 (explicitly mentioned)
    • Returns converted to INR for comparison

Methodology / Framework

  • Use 19 years of backtest data (~2007 to “now”).
  • Convert US / Nasdaq returns into INR to make performance comparable.
  • Define three portfolio building blocks:
    • Indian equity (large + mid + small cap exposure across Indian indices)
    • Gold (separate INR bucket)
    • Nasdaq 100 (US equity bucket converted to INR)
  • Test multiple static allocation mixes, including:
    • 100% India
    • 1/3 India / 1/3 Gold / 1/3 US
    • 50% India / 25% Gold / 25% US
    • Examples like 60% India, 70% India / 15% + 15%, 40/30/30, 80/10/10, and a plain vanilla equal portfolio
  • Rebalancing rule: At year-end, rebalance to the portfolio’s original target weights.
  • Performance metrics tracked:
    • CAGR
    • Max drawdown
    • Volatility
    • Sharpe ratio
    • Time spent near all-time highs, e.g., within 5% of ATH

Key Numbers and Findings

Standalone Performance (reference: “last year” + long-term CAGR claims)

Last year (2025) in INR terms:

  • Gold: +78%
  • Nasdaq: +24%
  • CNX 500: +2%

Over ~19 years (CAGR in INR terms as stated):

  • US equities (Nasdaq referenced as “US stock market”): 20.4% CAGR
  • Gold: 15.1% CAGR
  • Indian equity: ~12% CAGR

Why Diversification Matters (behavior + risk)

Even with good long-term averages, the speaker emphasizes:

  • Brutal drawdowns
  • “Lonely stretches”
  • The difficulty of resisting switching after underperformance (FOMO / cycle-chasing)

Example Allocation Results

  1. 100% Indian equity

    • CAGR: ~12%
    • Max drawdown: ~70%
    • Volatility: ~24%
    • Time near all-time highs: 16%
    • Time in <5% drawdown: 33%

  2. 40% India / 30% US / 30% Gold

    • CAGR: 16.5%
    • Max drawdown: 39% (vs ~70%)
    • Sharpe ratio improves (explicitly stated: “Sharpe ratio would have gone up”)

  3. “Plain vanilla equal portfolio” (≈ 1/3 India / 1/3 US / 1/3 Gold)

    • CAGR: 16.9%
    • Max drawdown: 34%
    • Volatility: ~13%
    • Sharpe ratio: 0.85
    • Best point on the described chart (roughly):
      • ~17% CAGR and ~36% max drawdown for the ~equal allocation
    • Narrative conclusion: better CAGR and lower drawdown

  4. 80% India / 10% Gold / 10% US

    • RoMaD collapses to less than half (see next section)
    • CAGR: ~13.8% (explicitly stated)

Risk-Adjusted Metric: “RoMaD”

Defined in words as:

  • RoMaD ratio = CAGR / max drawdown
    • Interpreted as “reward per unit of worst-case pain.”

Reported values:

  • Equal weights: RoMaD ≈ 0.5
  • 80/10/10: RoMaD “virtually collapsed to less than half”
  • Only Indian equities: RoMaD ≈ 0.17

Takeaway:

  • Adding gold and US improves the “reward per pain” ratio even if CAGR is slightly lower than the top-performing mix.

“How Often Does It Feel Like Winning?”

For the equal-weight portfolio (1/3–1/3–1/3):

  • 83% of the time, the portfolio is within 5% of all-time highs

For more India-heavy allocations:

  • Less time near highs; specifically:
    • 100% Indian equity: only 1/3 of the time feels like “winning”
      • meaning 2/3 feels like “sulking”

Current regime remark (contextual, not numeric):

  • Mentions a phase where it’s like the investor feels worse about “67% of the time” (implying frequent underperformance vs recent highs).

Macro / Behavioral Framing

  • The speaker argues the biggest failure mode is behavior, not asset selection:
    • Chasing last year’s winners after big runs
    • Switching at poor points in the cycle
  • Rebalancing to target weights is positioned as a discipline mechanism that reduces emotional decisions.

Additional Cautions / Caveats

  • The speaker cautions that:
    • Leadership/winners change by time period, and you can’t predict which asset will lead over the next year.
    • Therefore, don’t concentrate based on recent performance.
  • The test is simplified:
    • Once-a-year rebalance
    • Equal weights within Indian equity across large/mid/small

Presenter / Source

  • Alok Jain (referenced in the video title)

Original video