Quantitative analysis introduces a dual-condition entry filter in financial time-series data, suggesting reduced false breakouts by combining sustained trend slope with local range breaks.
{ "name": "directional_bias_continuation_break", "source": "Linda Raschke's '3-Bar Play' variant from 'Street Smarts'", "type": "filter_flag", "rule": "Enter only when the current bar closes above the high of the prior two bars after a 20-period SMA slope has been positive for at least 5 consecutive bars (for longs) or closes below the low of the prior two bars after a 20-period SMA slope has been negative for at least 5 consecutive bars (for shorts).", "pseudocode": "if (SMA20_slope > 0 for last 5 bars) and (close > max(high[-1], high[-2])) then long_flag = true; if (SMA20_slope < 0 for last 5 bars) and (close < min(low[-1], low[-2])) then short_flag = true; apply as entry filter.", "why_it_works": "Combines trend confirmation via sustained SMA slope direction with a tight breakout of recent range, filtering fakeouts by requiring both established momentum and structural breach." } Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com
No takes yet. Share an insight, caveat, or question.
Andrew Stewart Caldin (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: