feat: 3-tier outcome scoring + options P&L simulation in Pattern Lab
Backend (pattern_lab.py): - Replace binary HIT/MISS with FULL / PARTIAL / MISS scoring FULL: right direction AND ≥ 50% of expected move PARTIAL: right direction AND ≥ 15% of expected move (was always MISS before) MISS: wrong direction or negligible move - Add direction_correct, direction_ratio, hit_type fields to all outcomes - Add Black-Scholes ATM options P&L simulation (_bs_price, _ncdf, _sigma_for) Normalised to S₀=K=100, per-asset-class vol heuristic (FX 8%, indices 16%, crypto 65%) Supports: long call/put, straddle, strangle, call spread, put spread - estimated_options_pnl_pct shows what the strategy would have returned Frontend (PatternLab.tsx): - OutcomeRow component: FULL HIT (green) / PARTIAL (amber) / MISS (red) - Shows direction tick/cross + ratio % of target achieved - Shows estimated options P&L with DollarSign icon - Hit rate header shows full hits + partial count separately - Card border: emerald = full, amber = partial, red = miss Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
OpenSquared
@@ -9,6 +9,7 @@ Workflow:
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import json
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import logging
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from datetime import datetime, timedelta
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from math import log, sqrt, exp, erf
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from typing import Optional
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import numpy as np
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@@ -18,6 +19,140 @@ import yfinance as yf
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_log = logging.getLogger(__name__)
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# ── Options P&L helpers ────────────────────────────────────────────────────────
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def _ncdf(x: float) -> float:
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return 0.5 * (1.0 + erf(x / sqrt(2.0)))
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def _bs_price(S: float, K: float, T: float, r: float, sigma: float, opt_type: str) -> float:
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"""Black-Scholes European option price. T in years. At expiry (T≤0) returns intrinsic."""
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if T <= 0:
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return max(S - K, 0.0) if opt_type == "call" else max(K - S, 0.0)
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d1 = (log(S / K) + (r + 0.5 * sigma ** 2) * T) / (sigma * sqrt(T))
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d2 = d1 - sigma * sqrt(T)
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if opt_type == "call":
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return S * _ncdf(d1) - K * exp(-r * T) * _ncdf(d2)
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return K * exp(-r * T) * _ncdf(-d2) - S * _ncdf(-d1)
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def _sigma_for(ticker: str) -> float:
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"""Rough annualised vol estimate by asset class (ATM premium sizing)."""
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t = ticker.upper()
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if t.endswith("=X"): return 0.08 # FX pairs
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if "VIX" in t: return 0.80 # volatility index
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if t.startswith("^"): return 0.16 # equity indices
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if t.endswith("-USD") or "-USD" in t: return 0.65 # crypto
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if t.endswith("=F"): return 0.25 # commodity futures
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return 0.20 # ETFs / default
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def _options_pnl_pct(
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strategy: str, ticker: str,
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actual_move_pct: float, horizon_days: int,
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expected_direction: str,
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) -> Optional[float]:
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"""
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Estimate % P&L on the suggested options strategy assuming ATM entry,
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full-horizon hold, and actual_move_pct underlying move by expiry.
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Normalised to S₀ = K = 100.
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"""
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try:
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sigma = _sigma_for(ticker)
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T = max(horizon_days / 365.0, 1 / 365.0)
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r = 0.03
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S0 = 100.0
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K = 100.0
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S1 = S0 * (1.0 + actual_move_pct / 100.0)
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strat = strategy.lower()
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if "straddle" in strat:
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cost = _bs_price(S0, K, T, r, sigma, "call") + _bs_price(S0, K, T, r, sigma, "put")
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exit_v = _bs_price(S1, K, 0, r, sigma, "call") + _bs_price(S1, K, 0, r, sigma, "put")
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elif "strangle" in strat:
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Kc, Kp = K * 1.05, K * 0.95
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cost = _bs_price(S0, Kc, T, r, sigma, "call") + _bs_price(S0, Kp, T, r, sigma, "put")
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exit_v = _bs_price(S1, Kc, 0, r, sigma, "call") + _bs_price(S1, Kp, 0, r, sigma, "put")
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elif "call spread" in strat or "bull call" in strat:
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Kh = K * 1.10
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cost = _bs_price(S0, K, T, r, sigma, "call") - _bs_price(S0, Kh, T, r, sigma, "call")
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exit_v = _bs_price(S1, K, 0, r, sigma, "call") - _bs_price(S1, Kh, 0, r, sigma, "call")
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elif "put spread" in strat or "bear put" in strat:
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Kl = K * 0.90
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cost = _bs_price(S0, K, T, r, sigma, "put") - _bs_price(S0, Kl, T, r, sigma, "put")
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exit_v = _bs_price(S1, K, 0, r, sigma, "put") - _bs_price(S1, Kl, 0, r, sigma, "put")
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elif "long call" in strat or ("call" in strat and "put" not in strat):
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cost = _bs_price(S0, K, T, r, sigma, "call")
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exit_v = _bs_price(S1, K, 0, r, sigma, "call")
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elif "long put" in strat or ("put" in strat and "call" not in strat):
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cost = _bs_price(S0, K, T, r, sigma, "put")
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exit_v = _bs_price(S1, K, 0, r, sigma, "put")
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else:
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# Unknown strategy: fallback based on direction
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if expected_direction == "down":
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cost = _bs_price(S0, K, T, r, sigma, "put")
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exit_v = _bs_price(S1, K, 0, r, sigma, "put")
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elif expected_direction == "up":
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cost = _bs_price(S0, K, T, r, sigma, "call")
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exit_v = _bs_price(S1, K, 0, r, sigma, "call")
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else:
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cost = _bs_price(S0, K, T, r, sigma, "call") + _bs_price(S0, K, T, r, sigma, "put")
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exit_v = _bs_price(S1, K, 0, r, sigma, "call") + _bs_price(S1, K, 0, r, sigma, "put")
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if cost <= 0.01:
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return None
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return round((exit_v - cost) / cost * 100.0, 1)
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except Exception:
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return None
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def _score_outcome(
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actual_move: float,
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expected_move: float,
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expected_dir: str,
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strategy: str,
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ticker: str,
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horizon_days: int,
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) -> dict:
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"""
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3-tier scoring:
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FULL — right direction AND ≥ 50% of expected magnitude
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PARTIAL — right direction AND ≥ 15% of expected magnitude
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MISS — wrong direction or negligible move
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`hit` (bool) = True only for FULL (for backtest_hits counter compatibility).
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"""
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em = abs(float(expected_move))
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if expected_dir == "up":
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direction_correct = actual_move > 0
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direction_ratio = (actual_move / em) if em > 0 else 0.0
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elif expected_dir == "down":
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direction_correct = actual_move < 0
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direction_ratio = (-actual_move / em) if em > 0 else 0.0
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else: # "any" / volatility
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direction_correct = True
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direction_ratio = (abs(actual_move) / em) if em > 0 else 0.0
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direction_ratio = round(direction_ratio, 3)
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if direction_correct and direction_ratio >= 0.50:
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hit_type = "full"
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elif direction_correct and direction_ratio >= 0.15:
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hit_type = "partial"
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else:
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hit_type = "miss"
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options_pnl = _options_pnl_pct(strategy, ticker, actual_move, horizon_days, expected_dir)
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return {
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"hit": hit_type == "full",
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"hit_type": hit_type,
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"direction_correct": direction_correct,
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"direction_ratio": direction_ratio,
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"estimated_options_pnl_pct": options_pnl,
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}
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# ── Context builder ────────────────────────────────────────────────────────────
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def _fetch_ticker(ticker: str, start: str, end: str) -> Optional[pd.DataFrame]:
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@@ -207,25 +342,20 @@ def evaluate_outcomes(run: dict) -> list:
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outcomes.append({"pattern_name": pat.get("name"), "underlying": ticker, "error": "insufficient history"})
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continue
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entry_price = float(entry_sub["Close"].dropna().iloc[-1])
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exit_price = float(exit_sub["Close"].dropna().iloc[-1])
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actual_move = round((exit_price / entry_price - 1) * 100, 2)
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entry_price = float(entry_sub["Close"].dropna().iloc[-1])
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exit_price = float(exit_sub["Close"].dropna().iloc[-1])
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actual_move = round((exit_price / entry_price - 1) * 100, 2)
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expected_dir = pat.get("expected_direction", "any")
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expected_move = float(pat.get("expected_move_pct", 0))
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threshold = max(expected_move * 0.5, 3.0) # at least 50% of expected, min 3%
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strategy = pat.get("strategy", "")
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if expected_dir == "up":
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hit = actual_move >= threshold
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elif expected_dir == "down":
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hit = actual_move <= -threshold
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else: # any / volatility
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hit = abs(actual_move) >= threshold
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score = _score_outcome(actual_move, expected_move, expected_dir, strategy, ticker, horizon_days)
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outcomes.append({
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"pattern_name": pat.get("name"),
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"underlying": ticker,
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"strategy": pat.get("strategy", ""),
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"strategy": strategy,
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"signal_direction": pat.get("signal_direction", ""),
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"expected_direction": expected_dir,
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"expected_move_pct": expected_move,
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@@ -234,8 +364,8 @@ def evaluate_outcomes(run: dict) -> list:
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"exit_price": round(exit_price, 4),
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"entry_date": analysis_date,
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"exit_date": eval_dt.strftime("%Y-%m-%d"),
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"hit": hit,
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"confidence": pat.get("confidence", 0),
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**score,
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})
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return outcomes
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@@ -395,25 +525,20 @@ def evaluate_instrument_outcomes(run: dict) -> list:
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"analysis_date": pat_date, "error": "insufficient history"})
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continue
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entry_price = float(entry_sub["Close"].dropna().iloc[-1])
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exit_price = float(exit_sub["Close"].dropna().iloc[-1])
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actual_move = round((exit_price / entry_price - 1) * 100, 2)
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entry_price = float(entry_sub["Close"].dropna().iloc[-1])
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exit_price = float(exit_sub["Close"].dropna().iloc[-1])
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actual_move = round((exit_price / entry_price - 1) * 100, 2)
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expected_dir = pat.get("expected_direction", "any")
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expected_move = float(pat.get("expected_move_pct", 0))
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threshold = max(expected_move * 0.5, 3.0)
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strategy = pat.get("strategy", "")
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if expected_dir == "up":
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hit = actual_move >= threshold
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elif expected_dir == "down":
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hit = actual_move <= -threshold
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else:
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hit = abs(actual_move) >= threshold
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score = _score_outcome(actual_move, expected_move, expected_dir, strategy, ticker, pat_horizon)
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outcomes.append({
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"pattern_name": pat.get("name"),
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"underlying": ticker,
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"strategy": pat.get("strategy", ""),
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"strategy": strategy,
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"signal_direction": pat.get("signal_direction", ""),
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"expected_direction": expected_dir,
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"expected_move_pct": expected_move,
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@@ -423,8 +548,8 @@ def evaluate_instrument_outcomes(run: dict) -> list:
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"analysis_date": pat_date,
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"entry_date": pat_date,
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"exit_date": eval_dt.strftime("%Y-%m-%d"),
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"hit": hit,
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"confidence": pat.get("confidence", 0),
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**score,
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})
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return outcomes
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@@ -5,9 +5,9 @@ import {
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useInstrumentScan, useEvaluateInstrumentScan,
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} from '../hooks/useApi'
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import {
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FlaskConical, Play, CheckCircle2, XCircle,
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FlaskConical, Play, CheckCircle2, XCircle, MinusCircle,
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Trash2, Save, RefreshCw, Search, CalendarDays,
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TrendingUp, TrendingDown, Zap, BarChart2, ScanLine,
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TrendingUp, TrendingDown, Zap, BarChart2, ScanLine, DollarSign,
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} from 'lucide-react'
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import clsx from 'clsx'
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import { INSTRUMENTS, INSTRUMENT_CATEGORIES } from '../constants/instruments'
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@@ -85,6 +85,62 @@ function MoveBadge({ move, dir }: { move: number; dir: string }) {
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)
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}
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function OutcomeRow({ out }: { out: any }) {
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const hitType = out.hit_type ?? (out.hit ? 'full' : 'miss')
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const borderCls = hitType === 'full' ? 'border-emerald-700/30'
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: hitType === 'partial' ? 'border-amber-700/30' : 'border-red-700/30'
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return (
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<div className={clsx('mt-2 pt-2 border-t flex flex-wrap items-center gap-x-3 gap-y-1 text-[10px]', borderCls)}>
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{/* Hit type */}
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{hitType === 'full' && (
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<span className="flex items-center gap-1 text-emerald-300 font-semibold">
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<CheckCircle2 className="w-3.5 h-3.5" /> FULL HIT
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</span>
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)}
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{hitType === 'partial' && (
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<span className="flex items-center gap-1 text-amber-300 font-semibold">
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<MinusCircle className="w-3.5 h-3.5" /> PARTIAL
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</span>
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)}
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{hitType === 'miss' && (
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<span className="flex items-center gap-1 text-red-300 font-semibold">
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<XCircle className="w-3.5 h-3.5" /> MISS
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</span>
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)}
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{/* Direction */}
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<span className="text-slate-500">
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Dir: <span className={out.direction_correct ? 'text-emerald-400 font-semibold' : 'text-red-400 font-semibold'}>
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{out.direction_correct ? '✓' : '✗'}
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</span>
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{out.direction_correct && out.direction_ratio != null && (
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<span className="text-slate-500 ml-0.5">({Math.round(out.direction_ratio * 100)}% of target)</span>
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)}
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</span>
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{/* Actual move */}
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<span className="text-slate-400">Actual:</span>
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<MoveBadge move={out.actual_move_pct} dir={out.expected_direction} />
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<span className="text-slate-600">
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vs {out.expected_direction === 'up' ? '+' : out.expected_direction === 'down' ? '-' : '±'}{out.expected_move_pct}%
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</span>
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{/* Options P&L estimate */}
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{out.estimated_options_pnl_pct != null && (
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<span className={clsx(
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'flex items-center gap-0.5 font-semibold font-mono',
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out.estimated_options_pnl_pct >= 0 ? 'text-emerald-400' : 'text-red-400'
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)}>
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<DollarSign className="w-3 h-3" />
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{out.estimated_options_pnl_pct > 0 ? '+' : ''}{out.estimated_options_pnl_pct.toFixed(0)}% P&L
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</span>
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)}
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<span className="text-slate-600">{out.entry_date} → {out.exit_date}</span>
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</div>
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)
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}
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// ── Main page ──────────────────────────────────────────────────────────────────
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// ── Shared instrument picker ───────────────────────────────────────────────────
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@@ -310,18 +366,20 @@ export default function PatternLab() {
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const outcomeForPattern = (name: string) =>
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outcomes.find((o: any) => o.pattern_name === name)
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const hitRate = hasOutcomes
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? outcomes.filter((o: any) => o.hit === true).length / outcomes.filter((o: any) => 'hit' in o).length
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: null
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const scoredOutcomes = outcomes.filter((o: any) => 'hit_type' in o || 'hit' in o)
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const fullHits = outcomes.filter((o: any) => (o.hit_type ?? (o.hit ? 'full' : 'miss')) === 'full').length
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const partialHits = outcomes.filter((o: any) => (o.hit_type ?? '') === 'partial').length
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const hitRate = scoredOutcomes.length > 0 ? fullHits / scoredOutcomes.length : null
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// ── Instrument mode helpers
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const instPatterns: any[] = instRun?.ai_result?.patterns ?? []
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const instOutcomes: any[] = instRun?.outcome ?? []
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const instHasOut = instOutcomes.length > 0
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const instOutcomeFor = (name: string) => instOutcomes.find((o: any) => o.pattern_name === name)
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const instHitRate = instHasOut
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? instOutcomes.filter((o: any) => o.hit === true).length / instOutcomes.filter((o: any) => 'hit' in o).length
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: null
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const instScored = instOutcomes.filter((o: any) => 'hit_type' in o || 'hit' in o)
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const instFull = instOutcomes.filter((o: any) => (o.hit_type ?? (o.hit ? 'full' : 'miss')) === 'full').length
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const instPartial = instOutcomes.filter((o: any) => (o.hit_type ?? '') === 'partial').length
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const instHitRate = instScored.length > 0 ? instFull / instScored.length : null
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return (
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<div className="flex h-screen bg-dark-900 text-slate-200 overflow-hidden">
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@@ -480,9 +538,15 @@ export default function PatternLab() {
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</div>
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<div className="flex items-center gap-2">
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{instHasOut && instHitRate !== null && (
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<span className={clsx('text-sm font-bold', instHitRate >= 0.6 ? 'text-emerald-400' : instHitRate >= 0.4 ? 'text-yellow-400' : 'text-red-400')}>
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{Math.round(instHitRate * 100)}% hit rate
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</span>
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<div className="flex items-center gap-2">
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<span className={clsx('text-sm font-bold', instHitRate >= 0.6 ? 'text-emerald-400' : instHitRate >= 0.4 ? 'text-yellow-400' : 'text-red-400')}>
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{Math.round(instHitRate * 100)}% full
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</span>
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{instPartial > 0 && (
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<span className="text-xs text-amber-400">+{instPartial} partial</span>
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)}
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<span className="text-xs text-slate-600">({instFull}/{instScored.length})</span>
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</div>
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)}
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{!instHasOut && (
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<button onClick={handleInstEvaluate} disabled={evalInst}
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@@ -502,9 +566,11 @@ export default function PatternLab() {
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const dirCol = pat.signal_direction === 'bullish' ? 'text-emerald-400' : pat.signal_direction === 'bearish' ? 'text-red-400' : 'text-violet-400'
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return (
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<div key={idx} className={clsx('border rounded-lg p-3',
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out?.hit === true ? 'border-emerald-700/60 bg-emerald-900/10' :
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out?.hit === false ? 'border-red-700/40 bg-red-900/10' :
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'border-slate-700/40 bg-dark-700/30')}>
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(() => { const ht = out?.hit_type ?? (out?.hit ? 'full' : out ? 'miss' : null)
|
||||
return ht === 'full' ? 'border-emerald-700/60 bg-emerald-900/10'
|
||||
: ht === 'partial' ? 'border-amber-700/40 bg-amber-900/10'
|
||||
: ht === 'miss' ? 'border-red-700/40 bg-red-900/10'
|
||||
: 'border-slate-700/40 bg-dark-700/30' })())}>
|
||||
<div className="flex items-start gap-3">
|
||||
<div className="flex-1">
|
||||
<div className="flex items-center gap-2 mb-0.5">
|
||||
@@ -523,18 +589,7 @@ export default function PatternLab() {
|
||||
<span>Confidence: <span className={clsx('font-semibold', pat.confidence >= 70 ? 'text-emerald-400' : pat.confidence >= 50 ? 'text-yellow-400' : 'text-slate-400')}>{pat.confidence}</span></span>
|
||||
</div>
|
||||
{pat.rationale && <p className="text-[10px] text-slate-500 mt-1 italic">{pat.rationale}</p>}
|
||||
{out && (
|
||||
<div className={clsx('mt-2 pt-2 border-t flex items-center gap-3 text-[10px]',
|
||||
out.hit ? 'border-emerald-700/30 text-emerald-300' : 'border-red-700/30 text-red-300')}>
|
||||
{out.hit ? <CheckCircle2 className="w-3.5 h-3.5 text-emerald-400" /> : <XCircle className="w-3.5 h-3.5 text-red-400" />}
|
||||
<span className="font-semibold">{out.hit ? 'HIT' : 'MISS'}</span>
|
||||
<span className="text-slate-400">Actual:</span>
|
||||
<span className={clsx('font-mono font-semibold', out.actual_move_pct > 0 ? 'text-emerald-400' : 'text-red-400')}>
|
||||
{out.actual_move_pct > 0 ? '+' : ''}{out.actual_move_pct?.toFixed(1)}%
|
||||
</span>
|
||||
<span className="text-slate-500">{out.entry_date} → {out.exit_date}</span>
|
||||
</div>
|
||||
)}
|
||||
{out && <OutcomeRow out={out} />}
|
||||
</div>
|
||||
<div className="flex-shrink-0">
|
||||
{isSaved
|
||||
@@ -705,11 +760,14 @@ export default function PatternLab() {
|
||||
)}
|
||||
{hasOutcomes && hitRate !== null && (
|
||||
<div className="flex items-center gap-2">
|
||||
<span className="text-xs text-slate-500">Hit rate:</span>
|
||||
<span className="text-xs text-slate-500">Full hits:</span>
|
||||
<span className={clsx('text-sm font-bold', hitRate >= 0.6 ? 'text-emerald-400' : hitRate >= 0.4 ? 'text-yellow-400' : 'text-red-400')}>
|
||||
{Math.round(hitRate * 100)}%
|
||||
</span>
|
||||
<span className="text-xs text-slate-600">({outcomes.filter((o: any) => o.hit).length}/{outcomes.filter((o: any) => 'hit' in o).length})</span>
|
||||
{partialHits > 0 && (
|
||||
<span className="text-xs text-amber-400">+{partialHits} partial</span>
|
||||
)}
|
||||
<span className="text-xs text-slate-600">({fullHits}/{scoredOutcomes.length})</span>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
@@ -728,9 +786,11 @@ export default function PatternLab() {
|
||||
return (
|
||||
<div key={idx} className={clsx(
|
||||
'border rounded-lg p-3 transition-colors',
|
||||
out?.hit === true ? 'border-emerald-700/60 bg-emerald-900/10' :
|
||||
out?.hit === false ? 'border-red-700/40 bg-red-900/10' :
|
||||
'border-slate-700/40 bg-dark-700/30'
|
||||
(() => { const ht = out?.hit_type ?? (out?.hit ? 'full' : out ? 'miss' : null)
|
||||
return ht === 'full' ? 'border-emerald-700/60 bg-emerald-900/10'
|
||||
: ht === 'partial' ? 'border-amber-700/40 bg-amber-900/10'
|
||||
: ht === 'miss' ? 'border-red-700/40 bg-red-900/10'
|
||||
: 'border-slate-700/40 bg-dark-700/30' })()
|
||||
)}>
|
||||
<div className="flex items-start gap-3">
|
||||
<div className="flex-1">
|
||||
@@ -753,25 +813,7 @@ export default function PatternLab() {
|
||||
<p className="text-[10px] text-slate-500 mt-1.5 italic">{pat.rationale}</p>
|
||||
)}
|
||||
{/* Outcome row */}
|
||||
{out && (
|
||||
<div className={clsx(
|
||||
'mt-2 pt-2 border-t flex items-center gap-4 text-[10px]',
|
||||
out.hit ? 'border-emerald-700/30 text-emerald-300' : 'border-red-700/30 text-red-300'
|
||||
)}>
|
||||
{out.hit
|
||||
? <CheckCircle2 className="w-3.5 h-3.5 text-emerald-400" />
|
||||
: <XCircle className="w-3.5 h-3.5 text-red-400" />}
|
||||
<span className="font-semibold">{out.hit ? 'HIT' : 'MISS'}</span>
|
||||
<span className="text-slate-400">Actual move:</span>
|
||||
<MoveBadge move={out.actual_move_pct} dir={out.expected_direction} />
|
||||
<span className="text-slate-500">{out.entry_date} → {out.exit_date}</span>
|
||||
{out.entry_price && (
|
||||
<span className="text-slate-500">
|
||||
{out.entry_price} → {out.exit_price}
|
||||
</span>
|
||||
)}
|
||||
</div>
|
||||
)}
|
||||
{out && <OutcomeRow out={out} />}
|
||||
</div>
|
||||
|
||||
{/* Save button */}
|
||||
@@ -843,11 +885,12 @@ export default function PatternLab() {
|
||||
<span className="text-[10px] text-slate-600">{run.horizon_days}d</span>
|
||||
{run.status === 'evaluated' && run.outcome && (() => {
|
||||
const outs: any[] = Array.isArray(run.outcome) ? run.outcome : []
|
||||
const hits = outs.filter(o => o.hit === true).length
|
||||
const total = outs.filter(o => 'hit' in o).length
|
||||
return total > 0 ? (
|
||||
<span className={clsx('text-[10px] font-semibold', hits / total >= 0.6 ? 'text-emerald-400' : 'text-red-400')}>
|
||||
{Math.round(hits / total * 100)}% hit
|
||||
const scored = outs.filter(o => 'hit_type' in o || 'hit' in o)
|
||||
const full = outs.filter(o => (o.hit_type ?? (o.hit ? 'full' : 'miss')) === 'full').length
|
||||
const partial = outs.filter(o => (o.hit_type ?? '') === 'partial').length
|
||||
return scored.length > 0 ? (
|
||||
<span className={clsx('text-[10px] font-semibold', full / scored.length >= 0.6 ? 'text-emerald-400' : 'text-red-400')}>
|
||||
{Math.round(full / scored.length * 100)}%{partial > 0 ? ` +${partial}p` : ''}
|
||||
</span>
|
||||
) : null
|
||||
})()}
|
||||
|
||||
Reference in New Issue
Block a user