← ConnorsRSI_Composite

ConnorsRSI_Composite — Performance

ENGINEERING COMPLETEAudited 2026-09-13· directional engine· gunbot-quant· spot

Window 3.2 years (2023-07-11 → 2026-09-10, 27,760 bars of 60m) · Markets ADA, BTC, DOGE, ETH, LINK, SOL, XRP Costs 0.10% taker fee + 2 bps slippage on every fill Timeframe declares 60m — tested at its own timeframe Capital 1,000 quote Sizing all-in


How this was measured

Every decision is taken on a bar that has closed, and the resulting market order fills at the next bar's open plus slippage. Resting stop and target orders fill intrabar, and when one bar's range covers both the stop and the target the stop is taken first — the pessimistic reading wherever candle data cannot resolve the order of events inside a bar.

The engine is validated separately by 53 known-answer tests covering accounting, fee arithmetic, determinism and the no-look-ahead boundary. Nothing below means anything unless those pass, so the pipeline aborts if they do not.

Result by market

Market Orders Round trips Return Buy & hold Edge Max DD Sharpe Win rate Profit factor Time in market
ADA 86 42 4.2% -26.6% 30.8% 2.1% 0.82 79% 1.84 0.5%
BTC 143 71 -6.2% 130.8% -137.0% 6.4% -2.10 49% 0.30 0.8%
DOGE 82 41 -1.4% 24.0% -25.4% 3.7% -0.18 66% 0.85 0.4%
ETH 94 47 -0.9% 39.2% -40.1% 3.2% -0.26 51% 0.81 0.5%
LINK 98 49 -0.9% 7.1% -8.0% 2.7% -0.19 61% 0.89 0.5%
SOL 86 43 -3.7% 216.7% -220.5% 6.0% -0.83 60% 0.61 0.4%
XRP 58 29 -2.5% 152.1% -154.6% 3.0% -0.73 62% 0.59 0.3%

Median across markets: -1.4% return, 3.2% max drawdown, Sharpe -0.26.

The median is the honest number, not the best market. Ranking a strategy on its best pair measures which pair was picked, not what the strategy does.

Reading these numbers

One year vs three

The pack was originally ranked on a single year (2025-07 → 2026-07). Three years tells a different story, and the difference is worth more than either number alone.

1 year 3 years
Median return -0.8% -1.4%
Median buy-and-hold -52.1% 39.2%
Median edge vs buy-and-hold 50.8% -40.1%
Median max drawdown 1.0% 3.2%
Profitable on 2 / 7 1 / 7
Beat buy-and-hold on 7 / 7 1 / 7

What happened. In the one-year window buy-and-hold returned a median -52.1% — every market fell. A strategy in cash 99% of the time beats that almost by construction, so the 50.8% edge was substantially a measure of absence, not skill.

Three years includes the advance as well as the fall. Buy-and-hold returns a median 39.2% over it, and the same staying-in-cash behaviour now costs the strategy instead of flattering it: the edge moves from 50.8% to -40.1%.

The strategy did not change. The window did.

Any strategy whose edge comes from not participating looks excellent in a bear window and poor across a full cycle. This is the reason the 3-year data set was built, and the reason single-window rankings in this pack should be read with the buy-and-hold column next to them.

Variant B — no stop loss, never sells below the position average

The same strategy on the same data, with one rule added: no exit may be priced below the position's average cost. That also removes every stop-loss, since a stop sits below the entry by definition. It is the "never realise a loss" version.

A — as shipped B — no-loss exits
Median return -1.4% 9.7%
Median max drawdown 3.2% 7.9%
Profitable markets 1 / 7 6 / 7
Ends still holding — 6 / 7
Exits refused by the rule 0 42,585
Market A return B return A max DD B max DD B ends holding
ADA 4.2% 9.8% 2.1% 4.4% yes
BTC -6.2% -5.4% 6.4% 12.8% yes
DOGE -1.4% 12.3% 3.7% 5.4% yes
ETH -0.9% 5.5% 3.2% 9.1% yes
LINK -0.9% 10.5% 2.7% 8.0% yes
SOL -3.7% 9.7% 6.0% 7.4% yes
XRP -2.5% 5.5% 3.0% 7.9% no

How to read this. Variant B reports the higher return — 9.7% against -1.4% — and that is mostly not an improvement. A loss that is never closed does not disappear, it sits in inventory. That is why max drawdown rises from 3.2% to 7.9%, and why the strategy ends still holding on 6 of 7 markets: B's reported return leaves out the positions it never resolved. The rule refused 42,585 exits over the window.

Read the two together rather than picking one. A is what the strategy does; B is what it looks like with its losses deferred instead of taken, and the gap between them measures how much of A's result comes from cutting.

Why it exited

Every exit the engine executed, attributed to the message the strategy emitted on that bar. One bar is one decision, so an event announced on both the console and the side panel is counted once.

Exit Count Share Mean gain Worst
EXIT 261 81.1% — —
CLOSED OUTSIDE STRATEGY 58 18.0% — —
STOP 3 0.9% — —

Cost sensitivity

The strategy places the same number of orders at 0% fees as at 0.10%. That is a correctness property rather than a performance one: it proves no balance gate becomes unsatisfiable once costs leave the wallet. A strategy that fails this check stops trading silently the moment it meets a real fee schedule.

Market Orders at 0.10% fee Orders at 0% fee Ratio
ADA 44 44 1.00
BTC 72 72 1.00
DOGE 41 41 1.00
ETH 47 47 1.00
LINK 49 49 1.00
SOL 43 43 1.00
XRP 29 29 1.00

Correctness invariants

Invariant Result
runs clean on every market PASS
no phantom chart marks PASS
no negative balances PASS
cost independent (fees change P&L, not the ability to act) PASS
places orders somewhere PASS

Outstanding notes

What this window cannot tell you

Three years covers a full cycle — the 2023 recovery, the 2024-25 advance and the drawdown after it. It is still one history, and a strategy tuned on it can be fitted to it.

The engine models spot, long-only, one price per bar. It carries no order book, so it cannot see spread, queue position or depth, and a strategy whose edge is the spread cannot be measured here at all.


Every number on this page is read from the run record that produced it — the audit pipeline writes the page and the record together, so the two cannot drift apart.