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Thesis · thesis_mpct3ts7_kgid55
PYTH

PYTH

 shortLOSS 1-3d

Generated 14d ago · 2026-05-19T15:47:30Z · expires 2026-05-22

Conviction
74/100
Bull / Bear
46/78
Analyst scores
Realized PnL
-0.04%
peak -0.04% · MAE -0.27%
R:R
2.0:1
Reward over risk
Post-mortem
SHORT · auto-derived

Thesis invalidated — closed -3.76%.

  • Conviction was high (74/100) but the trade lost — a calibration miss the reflection loop should weight.
  • Max adverse excursion hit -26.85% — the stop did its job containing downside at the planned invalidation level.
  • Planned at 2.0:1 R:R — one loss at this ratio is expected variance; the edge is in the aggregate, not any single call.

Derived deterministically from stored entry/target/stop levels, peak PnL, and max adverse excursion. No model inference — every line maps to a number in the ledger.

Price levels
Entry low
$0.0383
Entry high
$0.0388
Target 1
$0.0367
Target 2
$0.0356
Stop loss
$0.0400
PYTH · 1h candles · last 121
Entry / Target / Stop overlaid
0.04310.04120.03920.03720.03520.03875/29 01:005/30 07:005/31 13:006/1 19:006/3 01:00
Technical analysis · 4h
Open in Chart Lab
Trend · bearishMomentum · neutralVolatility · highSMA · death cross
RSI 14
49.4
Neutral
ADX 14
13.8
No trend / chop
ATR 14
0.000000
0.00% of price
Bollinger 20 · 2σ
Upper 0.0400
Lower 0.0400
inside
SMA stack
200.0400
500.0400
2000.0500
TA Workspace · PYTH
Full workspace

Candles + Bollinger bands (20·2σ) + SMA 20/50 overlays + price-action arrows (engulf / breakout / reclaim / reject) + support and resistance zones. Toggle layers from the panel controls. For the full workspace with presets and split timeframes, click "Full workspace".

PYTH · 4H4H technical map
Syncing
Layers
Drawing technical layers...
Follow this thesis· pre-filled trade plan
Inputs
Mark $0.040135 · max 5x
$
$
$
$
$
%
x
Trade plan
Position size
68,965.5172 PYTH
$2.66K
Leverage
0.27x
≤ 5x cap
Effective risk
$100.00
1.00% of account
Liq estimate
—
approx · verify on HL
Stop P&L
-$100.00
1.00% of account
R:R potential
1 : 2.03
T2
Scenarios
T1 hit @ 0.0367
+1.28R$127.59(+1.28%)
T2 hit @ 0.0356
+2.03R$203.45(+2.03%)
Stop hit @ 0.04
-1.00R-$100.00(-1.00%)
Open PYTH on HyperliquidSet the side / leverage / order type yourself in HL — this calculator does not auto-execute.
Bull case
  • ADX is near 50.6, so trend force is present but follow-through still needs monitoring.
  • The stop band sits near $0.0400, and any failure to move cleanly away from entry should be treated as an early warning.
  • ATR missing; using Bollinger range as volatility proxy.
Bear case
  • 1d ADX confirms trend strength.
  • 4h RSI is washed out inside a weak trend.
  • 4h ADX confirms trend strength.
  • Candidate quality is 93.2 and the desk still classifies the setup as ready for publication.
  • VOLUME TREND replay (latest asset) scored 18.2, returned 12.24%, win rate 100.0%.
  • FredAI promotes this setup. VOLUME TREND is graded B in current memory. Policy confidence 97.0.
Oracle Debate

See the bull vs bear showdown

Side-by-side debate with score visualizer, individual argument cards, and verdict synthesis. The marketing-grade view of how the thesis was built.

Open Oracle Debate
Debate transcript
Commander verdict
constructive

The desk sees a credible setup, but still wants disciplined execution rather than chasing. Simulation leadership still looks competitive. Strategy command is still warming.

Final thesis
PYTH Short: constructive command backs the directional case

The desk sees a credible setup, but still wants disciplined execution rather than chasing. Simulation leadership still looks competitive. Strategy command is still warming. PYTH cleared the desk with the SHORT case leading on structure, while the opposing case remains tactical rather than dominant.

Technical analyst memo
Asset
PYTH
Price0.04
Timestamp1779205647833
Indicators
{
  "rsi14": 21.1,
  "macd": {
    "macd": 0,
    "signal": 0,
    "histogram": 0
  },
  "bollingerBands": {
    "upper": 0.05,
    "middle": 0.04,
    "lower": 0.04,
    "width": 14.15
  },
  "sma20": 0.04,
  "sma50": 0.05,
  "sma200": 0.05,
  "ema12": 0.04,
  "ema26": 0.04,
  "atr14": 0,
  "stochastic": {
    "k": 1.98,
    "d": 22.62
  },
  "adx14": 50.57,
  "obv": 2381521.780440001
}
Signals
{
  "trend": "bearish",
  "momentum": "oversold",
  "volatility": "high",
  "macdCross": "bearish_cross",
  "bbPosition": "below_lower",
  "smaTrend": "none",
  "patterns": []
}
Composite
{
  "bullScore": 7,
  "bearScore": 9.5,
  "overallBias": "bear"
}
Timeframes
{
  "15m": {
    "asset": "PYTH",
    "timestamp": 1779205647832,
    "price": 0.03852,
    "indicators": {
      "rsi14": 18.44,
      "macd": {
        "macd": 0,
        "signal": 0,
        "histogram": 0
      },
      "bollingerBands": {
        "upper": 0.04,
        "middle": 0.04,
        "lower": 0.04,
        "width": 15.44
      },
      "sma20": 0.04,
      "sma50": 0.04,
      "sma200": 0.04,
      "ema12": 0.04,
      "ema26": 0.04,
      "atr14": 0,
      "stochastic": {
        "k": 3.65,
        "d": 2.52
      },
      "adx14": 47.87,
      "obv": -2282471.30536
    },
    "signals": {
      "trend": "bearish",
      "momentum": "oversold",
      "volatility": "high",
      "macdCross": "none",
      "bbPosition": "inside",
      "smaTrend": "death_cross",
      "patterns": [
        "Bullish Harami",
        "Bullish Marubozu"
      ]
    },
    "composite": {
      "bullScore": 6,
      "bearScore": 8.5,
      "overallBias": "bear"
    }
  },
  "1h": {
    "asset": "PYTH",
    "timestamp": 1779205647832,
    "price": 0.03852,
    "indicators": {
      "rsi14": 22.02,
      "macd": {
        "macd": 0,
        "signal": 0,
        "histogram": 0
      },
      "bollingerBands": {
        "upper": 0.05,
        "middle": 0.04,
        "lower": 0.04,
        "width": 16.05
      },
      "sma20": 0.04,
      "sma50": 0.04,
      "sma200": 0.05,
      "ema12": 0.04,
      "ema26": 0.04,
      "atr14": 0,
      "stochastic": {
        "k": 2.31,
        "d": 15.08
      },
      "adx14": 32.11,
      "obv": -2758286.0487700007
    },
    "signals": {
      "trend": "bearish",
      "momentum": "oversold",
      "volatility": "high",
      "macdCross": "none",
      "bbPosition": "below_lower",
      "smaTrend": "death_cross",
      "patterns": [
        "Doji"
      ]
    },
    "composite": {
      "bullScore": 7,
      "bearScore": 8.5,
      "overallBias": "bear"
    }
  },
  "4h": {
    "asset": "PYTH",
    "timestamp": 1779205647833,
    "price": 0.03852,
    "indicators": {
      "rsi14": 21.1,
      "macd": {
        "macd": 0,
        "signal": 0,
        "histogram": 0
      },
      "bollingerBands": {
        "upper": 0.05,
        "middle": 0.04,
        "lower": 0.04,
        "width": 14.15
      },
      "sma20": 0.04,
      "sma50": 0.05,
      "sma200": 0.05,
      "ema12": 0.04,
      "ema26": 0.04,
      "atr14": 0,
      "stochastic": {
        "k": 1.98,
        "d": 22.62
      },
      "adx14": 50.57,
      "obv": 2381521.780440001
    },
    "signals": {
      "trend": "bearish",
      "momentum": "oversold",
      "volatility": "high",
      "macdCross": "bearish_cross",
      "bbPosition": "below_lower",
      "smaTrend": "none",
      "patterns": []
    },
    "composite": {
      "bullScore": 7,
      "bearScore": 9.5,
      "overallBias": "bear"
    }
  },
  "1d": {
    "asset": "PYTH",
    "timestamp": 1779205647833,
    "price": 0.03852,
    "indicators": {
      "rsi14": 31.28,
      "macd": {
        "macd": 0,
        "signal": 0,
        "histogram": 0
      },
      "bollingerBands": {
        "upper": 0.06,
        "middle": 0.05,
        "lower": 0.04,
        "width": 44.43
      },
      "sma20": 0.05,
      "sma50": 0.05,
      "sma200": 0.06,
      "ema12": 0.05,
      "ema26": 0.05,
      "atr14": 0,
      "stochastic": {
        "k": 0.57,
        "d": 5.87
      },
      "adx14": 27.04,
      "obv": -33567836.11894999
    },
    "signals": {
      "trend": "bearish",
      "momentum": "oversold",
      "volatility": "high",
      "macdCross": "none",
      "bbPosition": "below_lower",
      "smaTrend": "death_cross",
      "patterns": [
        "Bearish Engulfing"
      ]
    },
    "composite": {
      "bullScore": 6,
      "bearScore": 8.5,
      "overallBias": "bear"
    }
  }
}
Sentiment analyst memo
Funding Rate-0.00
Open Interest943585.42
Price0.04
Risk officer memo
Approvedyes
Risk rating
medium
Max position %3.08
Leverage2
Stop loss0.04
Take profit0.04
Risk:Reward
2.0:1
Max drawdown %3.84
Warnings
  • ATR missing; using Bollinger range as volatility proxy.
  • RSI 21.1 is stretched; follow-through may fade quickly.
  • Model risk fallback used after: scheduler fast path
Adjustments
Deterministic fallback risk for PYTH; keep size conservative until model risk manager confirms the setup.
Directional decision
Direction
short
Spread25
Dominant Conviction78
Threshold10
Calibrated debate
Bull Conviction25
Bear Conviction78
Notes
  • Scheduler fast path used deterministic thesis synthesis to preserve execution speed.
  • Fast-path direction gate: strategy_commander_conflict at 38.
  • Strategy commander: Strategy lab is usable, but AI should command conservatively while evidence builds.
  • Strategy lab: Strategy lab is warming and should support only measured AI command while the winner stabilizes.
  • Live learning: Desk recently blocked PYTH mostly because: Risk manager rejected the setup (extreme).
  • FredAI promote state
  • Desk edge is weak, so provisional relaxation is disabled
  • Strategy commander conflicts with the desk direction
  • VOLUME_TREND is graded B in current memory
  • replay remains supportive with score 18.2
  • SHORT desk bias has 100 confidence
  • multi-timeframe TA aligns with the desk bias
FredAI policy
State
promote
Score97
Conviction Adjustment6
Risk Adjustment2
Confidence85.40
Reasons
  • VOLUME_TREND is graded B in current memory
  • replay remains supportive with score 18.2
  • SHORT desk bias has 100 confidence
  • multi-timeframe TA aligns with the desk bias
Note
FredAI promotes this setup. VOLUME_TREND is graded B in current memory. Policy confidence 97.0.
Live-learning brain
State
cooling
Score0
Note
Desk recently blocked PYTH mostly because: Risk manager rejected the setup (extreme).
Strategy commander brain
State
warming
Score59
Note
Strategy lab is usable, but AI should command conservatively while evidence builds.
Strategy lab brain
State
warming
Evidence Grade
C
Note
Strategy lab is warming and should support only measured AI command while the winner stabilizes.
Market snapshot at generation
Mark price
$0.0385
Funding rate
-0.0026%
Open interest
$0.9M
Macro regime
balanced_drift_bear_lowvol
Replay regime
balanced_drift_bear_lowvol
Replay strategy
VOLUME_TREND · latest_asset
FredAI policy
promote
Strategy command
warming
Strategy lab
warming
Desk posture
standard
Brain mode
fast
See PYTH chart with overlay More thesesAll PYTH theses