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Buying dips in stock indices: a strategy that held up on data it was not picked on

24 October 2026, 08:47
Dobril Karakanchev
Dobril Karakanchev
0
30

The short answer

Yes, this one worked. Buying a stock index (like the US500 or the NASDAQ) after a short, sharp drop and selling a few days later made money over 14 years, also in the years we had not used to choose it. But the profit is modest: about 2% a year at a careful risk level. It is a real edge, not a way to get rich.

The idea

Stock indices tend to rise over time. When one drops hard for a day or two while it is in an uptrend, it often bounces back within a few days. The strategy buys after such a drop and sells after the bounce. Larry Connors made it popular.

The rules in plain words

  • Only buy, never sell short
  • Only when the index is in an uptrend: its price is above its average of the last 200 days
  • Buy after a sharp drop of a day or two (the RSI(2) indicator is below 10)
  • Sell when the price closes above its average of the last 5 days, or after 10 days at the latest

How we tested it

We let a computer trade these rules on 10 stock indices from 2012 to 2026, with trading costs included. We chose the indices that worked using only 2012 to 2018, and then checked 2019 to 2026, which the choice had never "seen".

What happened

Per index: "won" is the share of trades that made money, "average" is the average gain per trade:

  • NAS100: 121 trades, 73% won, average +0.49% a trade
  • JPN225: 114 trades, 72% won, average +0.51%
  • US500: 124 trades, 80% won, average +0.38%
  • US30: 127 trades, 76% won, average +0.18%
  • GER40: 123 trades, 70% won, average +0.09% (it lost in 2012 to 2018)
  • UK100: 100 trades, 59% won, average -0.06% (lost in both periods)
  • HK50: 73 trades, 64% won, average -0.12% (made money in 2012 to 2018, lost in 2019 to 2026)
  • FRA40, EU50 and AUS200 lost in 2012 to 2018 and made money afterwards

Five indices made money in 2012 to 2018: US30, NAS100, US500, JPN225 and HK50. In 2019 to 2026, four of them made money again; only HK50 failed. Small changes to the rules (buying after a bigger or a smaller drop, or after 3 or 4 down days in a row) mostly worked too. When a strategy keeps working after small changes, that is a good sign it is real and not luck.

With a stop loss on every trade

We added a stop loss (an automatic exit if the price keeps falling) to every trade and risked 2% of the account per trade, with at most 3 trades open at once. Result: 4.7% a year. The biggest fall from a high point (the "drawdown") was 18.5%, and the worst year lost 8%. 74% of the trades won and 12% hit the stop loss.

We also ran it in the MetaTrader 5 Strategy Tester on a broker's prices (4 indices, January 2020 to October 2026, 1% risk per trade): +15.8%, 254 trades, 72% won, profit factor 1.44 (1.44 dollars won for every dollar lost), biggest drawdown 6.5%. With 3% risk per trade: +53.9%, but with a 19.1% drawdown.

The honest read

At 1% risk per trade this made about 2% a year. To make more you have to risk more, and the falls get bigger too. The strategy is out of the market most of the time, so it can run next to other strategies. It is not a get-rich system, and nobody should sell it as one.

The Giza Gold EA trades exactly these rules as its "Index Dip" part, next to its gold breakout, with a stop loss on every trade: https://www.mql5.com/en/market/product/203469. Free set files and the full test numbers: https://www.mql5.com/en/blogs/post/777419

Details for those who want them

  • Data: daily index CFD prices from Dukascopy, 2012 to 2026
  • Entry at the close when RSI(2) is below 10 and the close is above the 200-day simple average; exit at the first close above the 5-day average, or after 10 days
  • Costs: 0.015% per side, plus 4% a year financing for every day held
  • Stop loss version: 3 times ATR(10) below the entry (ATR = the average daily range); with a stop, every version we tried made money in both periods

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Next week: the ICT "Power of Three" and the Judas swing on 18 years of gold.

#rsi, backtest, stock indices, mean reversion, strategy test