Adjusted some values
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@@ -162,7 +162,7 @@ def predict_latest_probability(
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max_age_days: int = 1,
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max_age_days: int = 1,
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api_key: str | None = None,
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api_key: str | None = None,
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secret_key: str | None = None,
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secret_key: str | None = None,
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fetch_recent_data: bool = False,
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fetch_recent_data: bool = True,
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) -> PredictionResult:
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) -> PredictionResult:
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"""Return the latest predicted probability for the next SPY move."""
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"""Return the latest predicted probability for the next SPY move."""
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@@ -26,7 +26,7 @@ DEFAULT_SYMBOL = "SPY"
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DEFAULT_MODEL_PATH = "notebooks/models/spy_xgb_v1.json"
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DEFAULT_MODEL_PATH = "notebooks/models/spy_xgb_v1.json"
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DEFAULT_METADATA_PATH = "notebooks/models/spy_xgb_v1_meta.json"
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DEFAULT_METADATA_PATH = "notebooks/models/spy_xgb_v1_meta.json"
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DEFAULT_MIN_ORDER_DOLLARS = 25.0
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DEFAULT_MIN_ORDER_DOLLARS = 25.0
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DEFAULT_SENSITIVITY = 15.0
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DEFAULT_SENSITIVITY = 25.0
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@dataclass(frozen=True)
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@dataclass(frozen=True)
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@@ -186,7 +186,7 @@ def rebalance_alpaca_portfolio(
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min_order_dollars: float = DEFAULT_MIN_ORDER_DOLLARS,
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min_order_dollars: float = DEFAULT_MIN_ORDER_DOLLARS,
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sensitivity: float = DEFAULT_SENSITIVITY,
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sensitivity: float = DEFAULT_SENSITIVITY,
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max_age_days: int = 1,
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max_age_days: int = 1,
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fetch_recent_data: bool = False,
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fetch_recent_data: bool = True,
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) -> tuple[AlpacaPortfolioSummary, Order | dict[str, Any] | None]:
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) -> tuple[AlpacaPortfolioSummary, Order | dict[str, Any] | None]:
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client = create_alpaca_trading_client(api_key=api_key, secret_key=secret_key, paper=paper)
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client = create_alpaca_trading_client(api_key=api_key, secret_key=secret_key, paper=paper)
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summary = fetch_alpaca_portfolio_summary(
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summary = fetch_alpaca_portfolio_summary(
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