Connors RSI 2

How this strategy trades, what it scored, and the measurements the score was read from: every symbol and timeframe, on real and resampled history.

At A Glance

47/ 100
Total Score
23of 52
Overall Rank
1of 9
In Mean Reversion
29,379
Trades Taken

Across 24 runs of real history, one for every market and bar size it trades, this strategy scored highest on SOLUSDT · 1h (78 / 100) and lowest on XRPUSDT · 4h (18 / 100).

What A $100.00 Stake Became

Score
Total Score Mean Of Real And Resampled 47 / 100
Real Data 46 / 100
Resampled Data 48 / 100
Overall Rank Top 45% 23 of 52
Rank In Mean Reversion Top 12% 1 of 9
By Metric
Beats Hold Real 19 · Resampled 45 32 / 100
Risk Adjusted Real 50 · Resampled 44 47 / 100
Profitability Real 42 · Resampled 32 37 / 100
Win Rate Real 99 · Resampled 100 99 / 100
Fee Efficiency Real 51 · Resampled 51 51 / 100

Where It Works

How It Trades

  1. Compute a very short 2-bar RSI (a dip detector), a 200-bar SMA (the long-term trend filter), and a 5-bar SMA (the exit line).
  2. Buy when the 2-bar RSI drops below 10 while the close is still above the 200-bar average: a sharp two-bar sell-off inside a market that is in a long-term uptrend.
  3. Sell as soon as the close rises back above its 5-bar average: the dip has bounced; the trade never waits for a big move.

Example Strategy

Pine Script

Paste it into TradingView’s Pine Editor to run these rules on any chart.

//@version=6
// Connors RSI 2 — sort.finance. Fills at the signal bar's close, 0.02% fee a side,
// whole account per trade, as the backtest. History and indicator warm-up
// differ from the site's, so expect close to the same trades, not identical.
strategy("Connors RSI 2", overlay=false,
     initial_capital=100, default_qty_type=strategy.percent_of_equity,
     default_qty_value=100, commission_type=strategy.commission.percent,
     commission_value=0.02, process_orders_on_close=true, pyramiding=0)

// The bar the current position opened on, and the bar the last one closed on.
var int entryBar = na
var int exitBar = -1

// ── Signals ──────────────────────────────────────────────────────────────
rsi = ta.rsi(close, 2)
regime = ta.sma(close, 200)
exitAverage = ta.sma(close, 5)
enterNow = rsi < 10 and close > regime
exitNow = close > exitAverage

// ── Orders ───────────────────────────────────────────────────────────────
// Open on the first bar the entry holds while flat; close on the first
// later bar the exit holds; never reopen on the bar a position closed.
inTrade = strategy.position_size != 0
if inTrade and bar_index > entryBar and exitNow
    strategy.close("Long")
    exitBar := bar_index
else if not inTrade and bar_index > exitBar and enterNow
    strategy.entry("Long", strategy.long)
    entryBar := bar_index

// ── Drawing ──────────────────────────────────────────────────────────────
plot(regime, "SMA 200", color=#8a92a0, force_overlay=true)
plot(exitAverage, "SMA 5", color=#e0a03a, force_overlay=true)
plot(rsi, "RSI 2", color=#4d8dff)
hline(10, "Oversold 10", color=color.new(#8a92a0, 40), linestyle=hline.style_dashed)
Show

Total Score

46 48 / 100

Score = 0.25 Sbeats_hold + 0.35 Srisk + 0.20 Sprofit + 0.10 Swin + 0.10 Sfee

One 0–100 number per symbol × timeframe cell. Every strategy is run on every cell, on both real and resampled price history, and the total beside its name is this number averaged over all of them.

Beats Hold

25% of the total

19 45 / 100

Sbeats_hold = clamp0100(50 + 25 log2EnetEhold)

Compares final net equity to what simply holding the asset would have returned over the same window. 50 is break-even; every doubling versus buy-and-hold adds 25 points.

Read From Net Equity · Price Change %

Net Equity

The account after fees, trade by trade.

Price Change %

What holding the asset made over the same stretch: the hold the account is measured against.

Risk Adjusted

35% of the total

50 44 / 100

Srisk = clamp0100(55 · Sharpe + 5)

A linear read on the rolling annualized Sharpe ratio at the last trade: 0 Sharpe scores 5, roughly 1.7 Sharpe maxes out the scale.

Read From Rolling Sharpe

Rolling Sharpe

The account's annualized Sharpe ratio at each trade's close.

Profitability

20% of the total

42 32 / 100

Sprofit = clamp0100(20 log2EnetE0)

How many times the starting cash multiplied, on a log scale: each doubling of capital is worth 20 points.

Read From Net Equity · Cumulative P&L %

Net Equity

The account after fees, against the cash it started with.

Cumulative P&L %

Not in the formula: every trade's return added up rather than compounded.

Win Rate

10% of the total

99 100 / 100

Swin = clamp0100(2.5 (W% − 20))

The share of trades that closed profitable, rescaled so a 20% win rate scores 0 and a 60% win rate maxes out the scale.

Read From Win Rate % · Trades

Win Rate %

The share of trades so far that closed in profit.

Trades

How many trades that share is taken over.

Fee Efficiency

10% of the total

51 51 / 100

Sfee = clamp0100(Enet/Egross − 0.40.6 × 100)

The share of the fee-free (gross) result that survives after fees: 60% survival scores 0, keeping the full gross result scores 100.

Read From Equity, Net And Gross · Cumulative Fees

Equity, Net And Gross

The account with the fees taken and, fainter, without them.

Cumulative Fees

Not in the formula: what the exchange took, which is the gap between net and gross above.