The 2-Period RSI: A Simple System That Still Earns Its Keep

---

Larry Connors put the 2-period RSI on the map in his 2008 book Short Term Trading Strategies That Work, co-authored with Cesar Alvarez. The core idea was disarmingly simple: use an absurdly short RSI lookback to catch deeply oversold stocks within an uptrend. Unconventional at the time but it stuck.

The Setup

Thanks for reading Trading Time Machine! Subscribe for free to receive new posts and support my work.

Entry requires three conditions:

• Price closes above the 200-period moving average (trend filter)

• Price closes below the 5-period moving average (pulled back)

• The 2-period RSI closes below 10 (oversold)

Exit is even simpler: close back above the 5-period moving average.

Here are a couple of recent examples in FANG.

The Backtest

I ran this against 20 years of Nasdaq 100 constituents (the stocks that make up QQQ), using a four-slot portfolio. When multiple symbols trigger on the same day, the system ranks by lowest RSI(2) value and chooses the ones with the lowest value.

The results:

The white line is QQQ. The green path is the system. It kept pace with the market over two decades and noticeably cushioned the 2008 drawdown; not bad for four rules and an exit signal.

Trade-Level Statistics

• Win Percentage: 64.33%

• Average Winner: 2.33%

• Average Loser: -3.02%

• Profit Factor: 1.45

• Annual Return: 17.84%

• Maximum Drawdown: 29.15%

• Sharpe Ratio: 1.10

The Sharpe above 1.0 is encouraging — it says the system earns its return without taking on the full volatility of the market. The annual return is solid.

My one concern is the Profit Factor. I generally want to see 1.65 or higher. At 1.45, the system works, but the margin isn’t wide. The math is straightforward:

(Win% × Avg Winner) ÷ (Loss% × Avg Loser) (0.6433 × 2.33%) ÷ (0.3567 × 3.02%) = 1.45

Why does this matter? A lower Profit Factor means the sequence of your trades carries more weight. If luck goes against you early, your real-world equity curve can diverge meaningfully from the backtested version. The system still works, but it has less cushion when things go sideways.

Monte Carlo: Testing the Range of Outcomes

I recently added a Monte Carlo simulator to the Trader Tools page (scroll below the news widget). Plug in your Win%, average winner, and average loser, and it plots 1000 potential equity paths.

And the plot of those:

Running our trade stats through the simulator:

• Median Profit Factor: 1.39 (slightly below backtest - expected)

• Risk of Ruin (defined as a 50% peak-to-trough decline): 1.6%

• Median Max Drawdown: 30.9% (vs. 29.15% in the backtest - nearly identical)

That close match between the simulated and backtested drawdown is a good sign. The system is behaving consistently.

What you’ll also notice in the chart: the range of final outcomes after 1000 trades is fairly wide. Better systems produce tighter fans of potential paths. A wide spread means more uncertainty about which version of the future you’ll actually experience.

Current Positions and Signals

We can take a look at the holdings it has currently and recently closed positions.

CMCSA would be an exit tomorrow as it closed above its 5 period moving average.

This would leave only one slot to add a position.

KLAC would be the selection to fill that slot based on having the lowest 2 period RSI reading of symbols that are above the 200 moving average and have the 2 period RSI below 10.

Bottom Line

The Connors settings hold up well. For a four rule system, it’s delivered an edge over two decades. But there’s room to improve We should aim for a higher Sharpe Ratio and a narrower outcome distribution. In a future post, we’ll try to build something better.

Dave Johnson - Quantitative System Designer at

TradingTimeMachine.com

Thanks for reading Trading Time Machine! Subscribe for free to receive new posts and support my work.

Via https://backtest.substack.com/p/the-2-period-rsi-a-simple-system