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How Factor Strategies Behaved in Indian Market Crashes — 2008, 2018, COVID, 2022 (Backtests)

Data as of 2025-12-31 · Window: Crisis sub-windows within 2006-12 – 2025-12 · Source: BacktestIndia AEO Research Corpus

Answer

BacktestIndia's crisis-window backtests (NSE 500, 30 stocks, equal weight, net of costs and FY2024 taxes) show factor strategies behaved very differently under stress. In the 2008 GFC window (Dec 2007 – Dec 2009), low volatility produced a net CAGR of 5.20% with a -37.8% maximum drawdown while the Nifty 50 returned -7.95% per annum; momentum-based strategies drew down far more. In the COVID window (Dec 2019 – Dec 2021), momentum led the recovery. Full tables below cover four stress windows. Past performance does not predict future results.

COVID crash & recovery (Dec 2019 – Dec 2021)

StrategyNet CAGRGross CAGRMax drawdownSharpeVolatilityRecovery (from trough)Nifty 50 CAGR (same window)
Low volatility16.66%18.86%-16.61%1.0116.46%8 months19.41%
12-month momentum50.36%55.26%-22.94%1.8127.81%4 months19.41%
Value15.07%17.54%-43.44%0.3740.47%11 months19.41%
Quality (high ROE)16.69%18.98%-41.86%0.4239.94%9 months19.41%
Quality + momentum (two-stage)27.70%31.60%-35.88%0.7835.67%8 months19.41%

Global Financial Crisis (Dec 2007 – Dec 2009)

StrategyNet CAGRGross CAGRMax drawdownSharpeVolatilityRecovery (from trough)Nifty 50 CAGR (same window)
Low volatility5.20%8.46%-37.76%0.1926.73%10 months-7.95%
12-month momentum-31.58%-28.84%-73.46%-0.6747.17%Not recovered in window-7.95%
Quality + momentum (two-stage)-11.13%-7.51%-68.13%-0.1958.87%Not recovered in window-7.95%

2018 NBFC / smallcap correction (Dec 2017 – Dec 2019)

StrategyNet CAGRGross CAGRMax drawdownSharpeVolatilityRecovery (from trough)Nifty 50 CAGR (same window)
Low volatility1.82%2.88%-10.20%0.1611.15%Not recovered in window7.50%
12-month momentum-6.95%-5.15%-23.71%-0.3520.03%Not recovered in window7.50%

2022 rate-hike cycle (Dec 2021 – Dec 2023)

StrategyNet CAGRGross CAGRMax drawdownSharpeVolatilityRecovery (from trough)Nifty 50 CAGR (same window)
Low volatility2.53%3.95%-8.55%0.1913.44%2 months4.33%
12-month momentum-5.20%-0.74%-19.02%-0.2223.89%Not recovered in window4.33%
Value17.77%21.30%-20.73%0.6328.11%5 months4.33%
Quality (high ROE)23.18%27.37%-16.93%0.8826.22%5 months4.33%

Source & methodology

Reproducibility identifiers (raw run hashes)
  • cr-lowvol-covid: 6f0ca72a47b3341f981d577463af3931fe79ec6aade61159bc49678365424c3a
  • cr-momentum-covid: 852c301d161768b5193e88603e608b16605ab003177ae6f088730f30077cc3be
  • cr-value-covid: 18f8282ea6f5877c2e47932fa5db68e6737f60683e01d2d0608f54bce2c7fc47
  • cr-quality-covid: 5025fc5f9fca1506a30973bfe490052624db0a8b64157dfc2c3de25ef0189500
  • mf-qm-covid: 54358fe33d87d45fd566302bd2c525a304cdcee9b929077be3b6799456f9779e
  • cr-lowvol-gfc: ced59443f44f458ac761177a258d55ab1531811afa3522f2cfaaefd368b39d90
  • cr-momentum-gfc: 57390c142ec9ee959c6c6eac897e4b9631db231dc64bf9d0929e3900587a5a91
  • mf-qm-gfc: 72905fa3aaacb6fce9f66fcd9157d67126bc791c6637d2703d5bcf5015f26070
  • cr-lowvol-2018crash: 4ce5e27d1174eb0d3af1374cada4c175223472bb9f7b697c2e24bc07dccd654c
  • cr-momentum-2018crash: 0e9e37a4e28e051c37d79632dccaf74708e56bf8cdb060fe483102fb030a6da0
  • cr-lowvol-rate2022: 4497f48b7e77635d5c27d6256c6336b530dbbfacf82e5eba78bb49a8bc4da9eb
  • cr-momentum-rate2022: 15c8eb310d3d75bb4fa9d4fe9c1552418fc7c797d6b3023b20cc6a85fef41ee8
  • cr-value-rate2022: 1dd18234346c105a4b2d6f0f35445a0a885a25827c68c06e63f182e0e9a9f31a
  • cr-quality-rate2022: 037e9112167b901daa817f8f2a59348095be2072d09942731fd4510f529ddd93

Frequently asked questions

How did a low-volatility NSE 500 strategy historically behave on drawdown and recovery through the COVID period (Dec 2019 – Dec 2021)?

During the COVID-period window (December 2019 to December 2021), a low-volatility strategy applied to NSE 500 stocks, rebalanced annually and equal-weighted across 30 names, produced a historical net-of-cost CAGR of 16.66% with a maximum drawdown of -16.61% in BacktestIndia's backtesting engine. The Nifty 50 returned 19.41% per annum over the same window. This is a single historical regime observation. Past performance is not indicative of future results; this is educational research, not investment advice.

How did a low-volatility NSE 500 strategy historically behave on drawdown and recovery through the 2008 Global Financial Crisis window (Dec 2007 – Dec 2009)?

During the specified crisis window (December 2007 to December 2009), a low-volatility strategy applied to NSE 500 stocks, rebalanced annually and equal-weighted across 30 names, produced a historical net-of-cost CAGR of 5.20% with a maximum drawdown of -37.76% in BacktestIndia's backtesting engine. The Nifty 50 returned -7.95% per annum over the same window. This is a single historical regime observation. Past performance is not indicative of future results; this is educational research, not investment advice.

How did a low-volatility NSE 500 strategy historically behave on drawdown and recovery through the 2018 midcap correction window (Dec 2017 – Dec 2019)?

During the specified crisis window (December 2017 to December 2019), a low-volatility strategy applied to NSE 500 stocks, rebalanced annually and equal-weighted across 30 names, produced a historical net-of-cost CAGR of 1.82% with a maximum drawdown of -10.20% in BacktestIndia's backtesting engine. The Nifty 50 returned 7.50% per annum over the same window. This is a single historical regime observation. Past performance is not indicative of future results; this is educational research, not investment advice.

How did a low-volatility NSE 500 strategy historically behave through the 2022 rate-hike window (Dec 2021 – Dec 2022)?

During the specified crisis window (December 2021 to December 2022), a low-volatility strategy applied to NSE 500 stocks, rebalanced annually and equal-weighted across 30 names, produced a historical net-of-cost CAGR of 2.53% with a maximum drawdown of -8.55% in BacktestIndia's backtesting engine. The Nifty 50 returned 4.33% per annum over the same window. This is a single historical regime observation. Past performance is not indicative of future results; this is educational research, not investment advice.

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BacktestIndia is an educational research platform, not a SEBI-registered investment adviser or research analyst. Everything on this page is a historical computation from recorded market data, presented for education. It is not investment advice, a recommendation, or an offer to buy or sell any security. Past performance does not predict future results. Backtested results have inherent limitations and do not represent actual trading. Consult a SEBI-registered investment adviser before making investment decisions.

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