~7 years of NASDAQ history went into this in the backend, replayed at 1-minute bar resolution: the same feed the live algo trades on today.
Now I've built it into one algo program. Every morning, it watches the day's hottest movers, flags the ones with edge, and calls them out.
Below: how it works, and what ~7 years of NASDAQ history says about it. Daily catches live on the journal page.
01 / Strategy
Edge first
Level-aware entries
Confluence between key reference price levels, recent structure, and tape behavior.
Hostile-condition suppression
Some market conditions are structurally hostile to the algo's setups. Signals there are blocked unless momentum confirms a real move.
Discipline always
Risk sized to setup
Stops are tight, level-aware, and protected against tape-velocity events.
Liquidity-capped sizing
Each trade takes a fixed share of the book, scaled down by a live liquidity cap so it never bids for more than the market can fill. Dollar-capped downside, uncapped upside.
Live-account gate
Broker stays suspended by default; only un-suspends per program-routed order. A watchdog re-asserts the suspend.
Manual = same harness
Manual trades route through the identical suspended-by-default broker gate. No side door.
The specific signal logic is intentionally not published. The methodology below is.
~0yrs
at 1-minute
resolution
0
strategies in
the live stack
0
unified scanner
+ executor
02 / Methodology
Every result on this page is from a backtest of the live trading code path against minute-bar history. Same scanner code, same strategy logic, same execution rules. Only the price feed differs.
No look-ahead bias.
Signals only see bars that would have closed at signal time; the algorithm cannot peek at future price action. The candidate universe is built causally too: a name only enters once it has actually qualified that day, never with end-of-day hindsight.
Worst-case fill modeling.
Exits are modeled pessimistically: every fill assumes the unfavorable side of the move, so results carry realistic slippage instead of idealized prices.
No survivorship bias.
The universe is reconstructed from each historical day's actual NASDAQ listings, not today's. Stocks that delisted are still counted.
Live-vs-backtest parity.
The scanner, strategy logic, and entry/exit rules are the same code in backtest and live trading. There are no "backtest-only" optimizations.
Costs included.
SEC fees and margin interest are subtracted from every result. No fantasy zero-friction P&L.
Tick-level realism.
Signal validation and fills run at tick resolution against raw trade prints and quotes, not just minute-bar summaries. Real execution costs (spread and slippage) are measured per trade, so the realistic-fills drag is reported, not assumed away.
03 / Backtest
Nearly seven years of NASDAQ history, replayed at the live trading resolution. Every signal, fill, and stop runs against the same 1-minute bar feed the algo trades on today.
The stack · walk-forward
The algorithm runs a small stack of independent setups side by side. Below is the combined walk-forward result, compounded from $25,000: each year's trades are selected by a model trained only on the years before it, then filled at the real bid and ask with a per-trade size cap. It's a modeled backtest that takes every qualifying signal, not a live track record — hover any strategy below to see its share.
Final balance
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Total return
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CAGR
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Max drawdown
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Win rate
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Profit factor
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Beta · vs S&P 500
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Alpha · / yr
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Disclaimers
This site is for educational and informational purposes only. Nothing here is investment, financial, legal, or tax advice. Nothing here is a recommendation, solicitation, or offer to buy or sell any security.
Past performance does not guarantee or predict future results. Backtested and simulated performance has inherent limitations: it benefits from hindsight, may not account for all real-world frictions, and can differ materially from results achieved in live trading.
Trading securities involves substantial risk of loss including the possibility of losing more than the amount invested when margin or leverage is used. Trading is not suitable for every investor.
No representation is being made that any account will or is likely to achieve profits or losses similar to those shown. Hypothetical results are not actual results. Live results will differ from backtested results due to factors including but not limited to slippage, partial fills, liquidity constraints, halts, broker latency, and intraday market regime changes.
Consult a qualified financial professional before making any trading or investment decision. The author of this site assumes no liability for any losses or damages arising from use of the information presented here.