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Config

midas.config

YAML config loading for portfolio and strategy definitions.

load_portfolio(path)

Load portfolio config and allocation constraints from YAML.

Returns (portfolio, constraints) tuple.

Source code in src/midas/config.py 
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def load_portfolio(path: Path) -> PortfolioConfig:
    """Load portfolio config and allocation constraints from YAML.

    Returns (portfolio, constraints) tuple.
    """
    raw = _load_yaml(path)

    holdings = [
        Holding(
            ticker=h["ticker"],
            shares=float(h["shares"]),
            cost_basis=float(h["cost_basis"]) if "cost_basis" in h else None,
        )
        for h in raw["portfolio"]
    ]

    infusion = None
    if "cash_infusion" in raw:
        ci = raw["cash_infusion"]
        next_date = ci["next_date"]
        if isinstance(next_date, str):
            next_date = date.fromisoformat(next_date)
        elif isinstance(next_date, datetime):
            next_date = next_date.date()
        infusion = CashInfusion(
            amount=float(ci["amount"]),
            next_date=next_date,
            frequency=ci.get("frequency"),
        )

    restrictions = None
    if "trading_restrictions" in raw:
        tr = raw["trading_restrictions"]
        restrictions = TradingRestrictions(
            round_trip_days=int(tr.get("round_trip_days", 0)),
        )

    portfolio = PortfolioConfig(
        holdings=holdings,
        available_cash=float(raw["available_cash"]),
        cash_infusion=infusion,
        trading_restrictions=restrictions,
    )

    return portfolio

load_strategies(path)

Load strategy configs and allocation-level knobs from YAML.

Returns (strategies, constraints) tuple. sigmoid_steepness and rebalance_threshold live at the top level of the strategies file because they are meta-strategy knobs (how scores are blended/acted on).

Source code in src/midas/config.py 
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def load_strategies(
    path: Path,
) -> tuple[list[StrategyConfig], AllocationConstraints]:
    """Load strategy configs and allocation-level knobs from YAML.

    Returns (strategies, constraints) tuple.  sigmoid_steepness and
    rebalance_threshold live at the top level of the strategies file
    because they are meta-strategy knobs (how scores are blended/acted on).
    """
    raw = _load_yaml(path)
    configs = []
    for s in raw["strategies"]:
        configs.append(StrategyConfig(
            name=s["name"],
            params=s.get("params", {}),
            tickers=s.get("tickers"),
            weight=float(s.get("weight", 1.0)),
            veto_threshold=float(s.get("veto_threshold", -0.5)),
        ))

    max_pos = raw.get("max_position_pct")
    constraints = AllocationConstraints(
        max_position_pct=float(max_pos) if max_pos is not None else None,
        min_cash_pct=float(raw.get("min_cash_pct", DEFAULT_MIN_CASH_PCT)),
        sigmoid_steepness=float(
            raw.get("sigmoid_steepness", DEFAULT_SIGMOID_STEEPNESS),
        ),
        rebalance_threshold=float(
            raw.get("rebalance_threshold", DEFAULT_REBALANCE_THRESHOLD),
        ),
    )
    return configs, constraints