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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 2024 election volatility

Current conditions share 6 of 16 factor characteristics with the 2024 election volatility (Currency, Liquidity, Option Premium Flow) but differ in Market Breadth (38 now vs 78 then), Earnings (41 now vs 71 then), Derivatives Positioning (47 now vs 75 then).

FactorCurrentThenDifference
Equity Momentum5274−22
Market Breadth3878−40
Derivatives Positioning4775−28
Option Premium Flow7873+5
Volatility6368−5
FII/DII Flows4972−23
Liquidity4750−4
Currency7979+0
Bond Market5749+7
Credit4669−23
Global Risk Appetite4169−28
Commodities4053−12
Valuation4834+14
Earnings4171−30
Macro Economy5946+13
Retail / MF / IPO6671−5

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.