Paper Review: "A Profitable Day Trading Strategy for the US Equity Market"

Overview

The presenter reviews the academic paper “A Profitable Day Trading Strategy for the US Equity Market” and plans to independently backtest and trade its rules. The paper reports a net return of about 1,600% from 2016–2023, compared with roughly 200% for the S&P 500. The presenter emphasizes that these are historical backtest results, not proof that the strategy will work in live trading.

Strategy Framework

The paper combines a 5-minute opening-range breakout (ORB) with the selection of stocks showing unusually high opening activity:

1. Build the eligible stock universe:
   • Opening price of at least $5.
   • Average daily volume over the prior 14 days above 1 million shares.
   • 14-day ATR above $0.50.
2. Rank eligible stocks by relative opening volume, comparing volume in the first five minutes with the corresponding recent norm, using the prior 14 days as the reference.
3. Select the top 20 stocks with the highest relative opening volume for the day.
4. Enter on a breakout: Go long above the first five-minute range’s high or short below its low.
5. Set a tight stop: The stated stop-loss distance is 10% of the stock’s ATR. If the position is not stopped out, hold it until the end of the day.
6. Size positions by risk: Size each position so that no more than 1% of the account is at risk.

The rationale for the relative-volume filter is that unusual activity may reflect a catalyst—such as earnings news, an FDA decision, a merger, or a technical breakout—that draws institutional attention. The paper also tests longer opening ranges, including 15- and 30-minute versions, but reports that the 5-minute range performed best.

Performance Figures and Examples

• The paper’s basic ORB strategy, without the “stocks in play” selection, reportedly made about $7,500, or roughly 30% over seven to eight years, from $25,000 of starting capital. The presenter says this lagged simply holding the S&P 500.
• The paper says the enhanced strategy’s results include Interactive Brokers Pro commissions of $0.0035 per share.
• The trade profile is highly asymmetric: about 17% of trades win, while 83% are stopped out. The paper’s thesis is that a small number of large winners offset many small losses.
• The presenter shows a live-trading example with a winning trade of about 5.5R—5.5 times the amount risked—as well as examples involving SoFi, Oracle, and SpaceX. He also shows a short trade that was stopped out.
• In the presenter’s visualization, the stock universe starts at more than 5,000 stocks. The $5 price filter leaves about 3,756, and the volume filter leaves about 1,500, before the ATR filter, relative-volume ranking, and selection of the top 20.

Assets and Companies Mentioned

• Indexes and ETFs: S&P 500, QQQ, and TQQQ. The presenter notes that a prior paper by the same authors focused on QQQ and TQQQ.
• Stocks and companies shown or cited: Nvidia, First Solar, Adobe, Twilio, Teladoc, Square, DigitalOcean, Charles Schwab, Vertiv, DFH, SoFi, Oracle, and SpaceX.
• Sector references: Data centers (Vertiv) and solar (First Solar).

Risks, Caveats, and Next Tests

• The presenter says the paper does not account for slippage and may assume better execution than a live brokerage account can deliver. Even a few cents of adverse execution could matter, particularly when stops are described as only a few cents from entry in some examples.
• Backtests based on bar data may miss intrabar price movements that could trigger stops. The presenter plans to test using tick data.
• The presenter questions whether the reported results depend on idealized execution. He also notes that the authors have related day-trading businesses and sell training, raising the possibility that the paper could also serve as marketing.
• The presenter reports trading the strategy for only a few weeks. It was barely profitable over that short period, which he says is not enough evidence to draw conclusions.
• He plans an independent backtest over 2016–2023, an out-of-sample test using data from 2024 through the end of October 2026, and longer-term live testing.
• The strategy is presented for analysis and implementation, not as a proven real-world result. No explicit “not financial advice” disclaimer appears in the subtitles.

Presenters and Sources

• Presenter: Part Time Larry
• Sources discussed: The paper “A Profitable Day Trading Strategy for the US Equity Market,” a QuantConnect C# test, and the presenter’s planned PyBroker backtests and live-trading logs.
• The paper’s authors are not named in the subtitles.