Daily setup · September 28, 2026

$BA -6.91% on 2.7× volume

Setup: -4.6% to -10.4% day, on ≥1.3x avg volume, below the 50-day. Here is what happened after days like this, and the exact rule so you can test it yourself.

After days like this

Matching days: -4.6% to -10.4% day, on ≥1.3x avg volume, below the 50-day · BA. How often the stock closed higher afterwards, vs. a typical day (since 2016).

Next day

73% up

typical 50% · median +1.51% · n=30

5 days later

60% up

typical 52% · median +3.10% · n=30

20 days later

47% up

typical 53% · median -0.41% · n=30

Next day: closed higher more often than after a typical day.

The rule, backtested

Buy at the next open after a matching day, hold 1 day, sell at the open. Run on 58 large caps with slippage, compared with buying any day the same way. The out-of-sample period is the most recent 30% of the data.

Backtest (buy next open, hold 1 day, net of slippage): +0.23%/trade vs -0.01% buying any day (1187 trades since 2016); out-of-sample 2023-2026: +0.39%.

Period	Dates	Trades	Win rate	Mean / trade	Median	Any day: win	Any day: mean
All	2016-09-29 to 2026-09-28	1187	49%	+0.23%	-0.07%	50%	-0.01%
In-sample	2016-09-29 to 2023-09-28	766	47%	+0.15%	-0.14%	50%	-0.02%
Out-of-sample	2023-09-29 to 2026-09-28	421	52%	+0.39%	+0.16%	50%	+0.01%

Run this setup yourself

This is the complete AlgoDeploy config behind the backtest above. Change symbol to test the same setup on any ticker, or adjust the thresholds and holding period.

# AlgoDeploy setup rule for BA, from its 2026-09-28 move.
# Run:  algodeploy backtest setup_rule.yaml
# Change `symbol` to test the same setup on any ticker.
name: "Setup: -4.6% to -10.4% day, on ≥1.3x avg volume, below the 50-day, hold 1d"
symbol: "BA"
start: "2016-09-29"
end: "2026-09-29"
equity: 100000
data:
  provider: "yfinance"
entry:
  conditions:
    - "pct_change(1) <= -0.046"
    - "pct_change(1) >= -0.104"
    - "volume_ratio(20) >= 1.3"
    - "close < sma(50)"
  position_size: "95%"
exit:
  max_hold_days: 1
fill_on: "next_open"
slippage_bps: 5
commission_per_share: 0.005

Download setup_rule.yaml

Backtest this setup on your own machine

Start a 7-day free trial of AlgoDeploy, then run the rule above. Same engine for backtesting and live trading, and your strategies and keys never leave your computer.

Start your 7-day free trial

Start your free trial and install AlgoDeploy.
Save the rule above as setup_rule.yaml (or download it).
Run algodeploy backtest setup_rule.yaml to get the full HTML report.

Method: a "matching day" is one with the setup above. History uses close-to-close returns with clustered events collapsed; the rule backtest uses next-open fills with 5 bps slippage per side. The universe is today's large caps, which carries survivorship bias (names that became large caps because they rose).