Zilla Arena record / H1, sealed six months

XAUUSDGold

Our flagship instrument, and the honest verdict is break even. Six sealed months bought nothing worth bragging about here, and we publish that.

DeepSeek Reasoner · RSI5 trend pullback (final)

graded break even

Net result
+$791
on $10,000
Return
+7.9%
six months, not annualised
Closed trades
194
measurable sample
Max drawdown
11.0%
-$1,238
Green months
4/7
months traded
Risk per trade
1.0%
delivered, intended 1%

Sizing note, flagged by the engine at run time

Sizing could not honour 1% risk: the smallest tradeable size puts up to 1.33% of the account behind a stop. Raise the starting capital or widen the stop.

Risk actually delivered on this design: 1.0% of the account on an average trade, 2.6% at the worst, against the intended 1%. The deviation is small; the figures on this page remain comparable to the other clean cells.

The design, in plain words

The design with the largest sample is featured because on this market the sample is the story. DeepSeek built a pullback rule: a very fast RSI over 5 periods with bands close to neutral supplies the trigger, and a 20 period average acts as the trend filter, so the rule buys dips above the average and sells rallies below it. It fired 194 times, a genuinely measurable sample, and after spread it earned a profit factor of 1.08: gross wins were eight percent larger than gross losses. The engine grades that break even, because commission and swap are not charged in this arena and a margin that thin does not survive them.

The ranking on this cell carries its own warning. The design that scored the highest expectancy per trade, from Grok, actually lost money in dollars and collapses when its five best trades are removed. It is labelled fragile below, and the fragility is exactly why a single leaderboard number is never the whole truth.

The exact rule, as the engine ran it

RSI 5 45/55 · stop 1.5xATR(14) · 2R ladder 1R@0.5/2R@0.5 · market · EMA20 with-trend · no entry 30m before/30m after high news

Every parameter the engine received
strategy
"rsi_reversal"
atr_period
14
order_type
"market"
targets
[[1,0.5],[2,0.5]]
breakeven_after_target
1
valid_bars
12
cooldown_bars
5
rsi_period
5
rsi_oversold
45
rsi_overbought
55
sl_atr_mult
1.5
rr
2
trend_ema_period
20
trend_filter
"with"
news_filter
"avoid"
news_impact
"high"
news_before_minutes
30
news_after_minutes
30

The model’s own stated reasoning, verbatim

Final configuration. The design is a pullback-in-trend rule: RSI(5) exiting an extreme gives the entry timing, and the EMA(20) 'with' filter allows longs only above it and shorts only below it, so each trade is aligned with the short-term trend rather than blindly fading the market. The 45/55 bands are intentionally close to neutral so the rule produces enough trades to be measurable, while the high-impact news avoidance is a structural protection against scheduled USD spikes. The ladder banks half the position at 1R, moves the stop to breakeven, and leaves the runner targeting 2R. These parameters are round, simple, and were chosen for robustness across regimes; I am not tuning further against the training window.

How it got there: the accepted configurations, in order

  1. 02RSI pullback with trend, session, news filters-1.000R on 1 trades in training
  2. 04RSI5 pullback with trend/session/news-0.006R on 17 trades in training
  3. 05RSI5 short-term trend pullback, all hours+0.143R on 22 trades in training
  4. 06RSI5 trend pullback, higher frequency+0.165R on 36 trades in training
  5. 07RSI5 trend pullback (final)+0.165R on 36 trades in training

2 further replies produced no valid configuration and were rejected; the record keeps them.

The measurement

Break even published as break even. A results page that only ever shows wins is a brochure, and this cell is the proof the grading is real.

Month by month

MonthTradesNet P&L
Feb 202618+$754
Mar 202636-$319
Apr 202631+$623
May 202632-$248
Jun 202628-$794
Jul 202633+$400
Aug 202616+$377

The rest of the scorecard

Win rate
47.9% (93W 101L)
Expectancy per unit of risk
+0.092R
Profit factor
1.08
Longest losing streak
6 trades
Average risk per trade, delivered
1.0% (peak 2.6%)
Expectancy without the 5 best trades
+0.002R
Share of gross wins in the 5 best
14.7%
Final balance
$10,791

Every entrant, not just the winner

All entrants. The expectancy ranking and the dollar column disagree on this market; both are shown, and the fragility flag explains the disagreement.

RankModelDesignClosedExpectancyNet P&LMax DDRisk/tradeVerdict
1Grok 4 (xAI)
rsi_rev_choppy
RSI 14 30/70 · stop 1.5xATR(14) · 2R · market
Its stated reasoning

Choppy regime (dir eff 0.0567) with low trend strength favors reversal entries over trend-following crosses. RSI rule fires only on exit from extremes, matching mean-reverting character. Cooldown raised to limit over-trading in 625-bar window. ATR sizing keeps risk constant despite 65% vol rise in second half. No trend filter used because 94% bars above EMA200 would bias long-only.

55
small sample
+0.199R
fragile: fails the best five check (-0.226R without them)
-$779.8%1.0%graded break even
2MiniMax M3
ema_cross_trend_following
EMA 25/60 · stop 2xATR(14) · 2.5R · market · EMA100 with-trend · no entry 30m before/30m after high news
Its stated reasoning

EMA(25)/EMA(60) cross with trend filter 'with' (EMA100) for direction bias. sl_atr_mult 2.0 with rr 2.5 provides 5R target. News filter avoids 21 high-impact USD events. Cooldown 5 prevents spam. Same config as training run that produced +1.18R over 8 trades - keeping it because score-aware tuning would fit to the training window. The trend filter adapts to direction (longs above EMA100 in bull, shorts below in bear) so the logic is robust to regime changes visible only in the hidden window.

48
small sample
+0.158R
fragile: fails the best five check (-0.114R without them)
+$4115.1%1.0%graded positive
3DeepSeek Reasoner
RSI5 trend pullback (final)
RSI 5 45/55 · stop 1.5xATR(14) · 2R ladder 1R@0.5/2R@0.5 · market · EMA20 with-trend · no entry 30m before/30m after high news
Its stated reasoning

Final configuration. The design is a pullback-in-trend rule: RSI(5) exiting an extreme gives the entry timing, and the EMA(20) 'with' filter allows longs only above it and shorts only below it, so each trade is aligned with the short-term trend rather than blindly fading the market. The 45/55 bands are intentionally close to neutral so the rule produces enough trades to be measurable, while the high-impact news avoidance is a structural protection against scheduled USD spikes. The ladder banks half the position at 1R, moves the stop to breakeven, and leaves the runner targeting 2R. These parameters are round, simple, and were chosen for robustness across regimes; I am not tuning further against the training window.

194+0.092R+$79111.0%1.0%graded break even
4Claude Opus 4.5 (Anthropic)
RSI Mean Reversion Final
RSI 14 35/65 · stop 3xATR(14) · 1.5R · market · session 12-20 UTC
Its stated reasoning

The previous configuration showed marginal positive expectancy (+0.151R) with 13 trades, but the engine flagged a sizing issue - the smallest tradeable lot risked up to 2.30% instead of the intended 1%. This means the actual risk was higher than designed, and the results reflect that distortion. I am making one targeted change: widening the stop from 2.5 to 3.0 ATR. This addresses the sizing constraint by allowing proper position sizing at the intended 1% risk level. The wider stop also better accommodates the high volatility environment (ATR rose 65% in the second half of the training window, with last ATR at 105.29 vs mean of 24.04). All other parameters remain unchanged because: 1) The RSI thresholds (35/65) generated a reasonable signal frequency without being too loose. 2) The session filter (12-20 UTC) targets the documented high-volatility hours. 3) The 12-bar cooldown prevents overtrading while allowing sufficient opportunities. 4) The 1.5 RR is conservative and appropriate for mean-reverting conditions. I am not chasing the training window result - the 13-trade sample is statistical noise. The logic of RSI mean reversion during active hours with adequate stop distance for volatile gold markets should be robust across different windows. Setting final=true because further iteration risks overfitting to this specific 625-bar sample.

60
small sample
+0.015R
fragile: fails the best five check (-0.121R without them)
+$3249.4%1.1%graded break even
5GPT-4.1 (OpenAI)
RSI Reversal, Short Period, Wide Stop, No Volatility Filter
RSI 8 30/70 · stop 2.5xATR(14) · 1.2R · market · session 12-19 UTC
Its stated reasoning

This configuration produced a reasonable number of trades (n=18) and positive expectancy in a choppy, mean-reverting window. The short RSI period (8) increases signal frequency and responsiveness, while standard 30/70 levels capture mean-reversion entries. A wide 2.5 ATR stop helps risk sizing and survival in noisy conditions, and a quick 1.2 RR fits the mean-reverting regime. Session filter (12-19 UTC) targets the most active hours. All other filters are removed to maximize robustness and avoid overfitting. Cooldown at 4 bars allows frequent entries without clustering. This setup is simple, robust, and avoids overfitting to the training window, aiming for generalizability to the hidden window.

69
small sample
-0.015R-$27112.0%1.1%graded break even
6Qwen3-Max (Alibaba)
XAUUSD RSI Reversal with Filters
RSI 14 30/70 · stop 1.8xATR(14) · 2.5R · market · session 12-20 UTC · EMA200 with-trend · ATR 0.3-inf% · no entry 60m before/30m after high news
Its stated reasoning

The training window shows a choppy, mean-reverting regime (directional efficiency 0.0567) with 94.8% of bars above EMA(200), suggesting price respects the long-term trend as support. RSI reversal aligns with mean-reversion. Restricting entries to 12-20 UTC captures the highest volatility hours (mean range peaks at 14 UTC: 47.26). Trend filter 'with' EMA(200) ensures longs only in the dominant uptrend context. Volatility floor (ATR ≥0.3% of price) avoids whipsaws in quiet periods. News avoidance around high-impact USD events reduces adverse spikes, critical given XAUUSD's sensitivity to USD news. SL at 1.8x ATR and RR 2.5 balance risk/reward given gold's wide swings. Cooldown prevents overtrading in sideways conditions.

3
noise sample
+1.330R+$4480.9%1.0%graded positive
Gemini 2.5 Pro (Google)Not called: no API key was configured for this provider. Listed so the size of the field is not overstated.
Kimi K2.5 (Moonshot)Not called: no API key was configured for this provider. Listed so the size of the field is not overstated.

Risk/trade is the average share of the account actually behind each stop, measured from the ledger. The intended figure was 1%.

How this was measured

Training window, visible to the models
Dec 22 2025 to Jan 31 2026 (625 H1 bars)
Embargo between training and scoring
12.5 days, equal to the engine's settle margin, so no training trade can still be open when scoring starts
Sealed scoring window
Feb 13 2026 to Aug 14 2026 (4368 H1 bars), opened exactly once per locked design
Search before the seal broke
150 candidate configurations scored on training windows across all 8 markets; 19 on this market; every candidate is stored in the record with its training score
Capital and intended risk
$10,000 per design, 1% of account intended per trade
Costs charged
spread, once per position, taken from the ask recorded on the fill bar, with a measured fallback
Costs not charged
commission, swap and slippage beyond the next bar open; thin margins over break even do not survive them, and the verdicts say so
Record
XAUUSD H1, ref 1e443510, committed under backend/arena_matrix_out

Everything above is a measurement of one past window on our own candles, with spread charged and commission and swap not charged. It is history, not a forecast. None of it annualises, and none of it says anything about the next window.