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Historical analogues & backtest

How today's factor profile compares with past Indian market episodes, and what followed each sentiment band historically.

Historical periods

PeriodScore thenSimilarity
2008 Global Financial Crisis
2008-01-08 → 2009-03-09
3177%
2013 Taper Tantrum
2013-05-22 → 2013-09-04
3986%
2015 China / global slowdown
2015-08-10 → 2016-02-29
3682%
2018 NBFC / credit stress
2018-08-29 → 2018-10-26
4886%
2020 COVID crash
2020-02-20 → 2020-03-24
2670%
2022 global inflation / rate shock
2022-01-18 → 2022-06-17
3480%
2024 election volatility
2024-05-13 → 2024-06-07
6884%
Current52

Similarity = 100 − mean absolute difference of factor scores over factors available in both periods. It describes resemblance, not a forecast.

Current vs 2020 COVID crash

Current conditions share 3 of 16 factor characteristics with the 2020 COVID crash (Retail / MF / IPO, Bond Market, Earnings) but differ in Volatility (63 now vs 1 then), Option Premium Flow (78 now vs 20 then), Equity Momentum (52 now vs 2 then).

FactorCurrentThenDifference
Equity Momentum522+51
Market Breadth385+33
Derivatives Positioning4710+38
Option Premium Flow7820+58
Volatility631+62
FII/DII Flows4937+12
Liquidity4736+11
Currency7931+49
Bond Market5753+4
Credit4614+32
Global Risk Appetite4112+29
Commodities4075−35
Valuation4892−44
Earnings4149−8
Macro Economy5942+17
Retail / MF / IPO6669−3

Differences within ±10 points count as shared characteristics.

Backtest — HISTORICAL OBSERVATIONS, not forecasts

Forward NIFTY 50 returns after each sentiment band, 2006-01-02 → 2026-10-19 (1086 weekly observations with ≥ 50% factor coverage). Horizon: 3 months.

Sentiment bandObservations≈ IndependentAverage returnMedian returnPositiveAvg max drawdownWorst max drawdown
Extreme Fear00—————
Fear14311−2.46%−1.07%45%-11.3%-35.0%
Mild Fear20215+1.97%+2.14%59%-7.2%-32.1%
Neutral24518+4.80%+4.48%70%-6.4%-37.6%
Mild Greed33425+3.78%+3.98%68%-7.2%-37.6%
Greed14911+5.69%+5.97%71%-5.7%-15.2%
Extreme Greed00—————
  • · HISTORICAL OBSERVATIONS — not forecasts or expected returns.
  • · Scores are reconstructed point-in-time: each date uses only data published by then (publication lags applied) and trailing-only percentiles.
  • · Weekly sampling; forward windows overlap for horizons longer than one week, so the number of independent observations (shown) is much smaller than the sample count.
  • · Index-level returns (NIFTY 50 price index, excluding dividends) avoid single-stock survivorship bias; index membership changes are inherent to the index.
  • · Weights and thresholds are judgement-based and were not optimised on these results (to limit data snooping and overfitting).
  • · Dates with less than the minimum factor coverage are excluded.