HKUDS/Vibe-Trading · error · ValueError

steps_per_year must be >= 1, got {steps_per_year}

Error message

steps_per_year must be >= 1, got {steps_per_year}

What it means

monte_carlo_gbm discretizes time as dt = 1/steps_per_year and needs steps_per_year >= 1 (e.g. 252 for daily, 12 for monthly, 1 for annual). Values below 1 would imply steps longer than a year via division by a fraction, breaking the intended convention, and 0 would divide by zero.

Source

Thrown at agent/src/quantlib/risk.py:565

            Defaults to the 252-day trading year.

    Returns:
        Price matrix of shape ``(n_paths, n_steps + 1)``. Column 0 is exactly
        ``s0`` on every path, so ``paths[:, -1] / paths[:, 0] - 1`` is the total
        return over the whole simulation.

    Raises:
        ValueError: If ``s0`` is not positive, ``sigma`` is negative, or any of
            ``n_steps`` / ``n_paths`` / ``steps_per_year`` is below 1.
    """
    if s0 <= 0.0:
        raise ValueError(f"s0 must be > 0, got {s0}")
    if sigma < 0.0:
        raise ValueError(f"sigma must be >= 0, got {sigma}")
    if n_steps < 1 or n_paths < 1:
        raise ValueError(f"n_steps and n_paths must be >= 1, got {n_steps} and {n_paths}")
    if steps_per_year < 1:
        raise ValueError(f"steps_per_year must be >= 1, got {steps_per_year}")

    dt = 1.0 / steps_per_year
    rng = np.random.default_rng(seed)
    shocks = rng.standard_normal((n_paths, n_steps))
    log_returns = (mu - 0.5 * sigma**2) * dt + sigma * np.sqrt(dt) * shocks
    paths = np.empty((n_paths, n_steps + 1), dtype=float)
    paths[:, 0] = s0
    paths[:, 1:] = s0 * np.exp(np.cumsum(log_returns, axis=1))
    return paths


def analyze_mc_results(paths: np.ndarray, confidence: float = 0.95) -> dict:
    """Summarise the terminal distribution of a simulated price matrix.

    Args:
        paths: Price matrix of shape ``(n_paths, n_steps + 1)`` as returned by
            ``monte_carlo_gbm``; column 0 is the starting price.
        confidence: Confidence level for the VaR/CVaR of the terminal return.

View on GitHub (pinned to 80ffdda44c)

Solutions

1. Pass the frequency: 252 for daily, 52 weekly, 12 monthly, 1 annual
2. If you have a step size dt, pass steps_per_year=1/dt (guarding dt > 0)
3. Validate steps_per_year is an integer >= 1 in config

Example fix

// before
paths = monte_carlo_gbm(s0=100, mu=0.05, sigma=0.2, n_steps=252, steps_per_year=1/252)
// after
paths = monte_carlo_gbm(s0=100, mu=0.05, sigma=0.2, n_steps=252, steps_per_year=252)

steps_per_year = max(1, int(round(steps_per_year)))

def is_valid_steps_per_year(x) -> bool:
    return isinstance(x, (int, float)) and not isinstance(x, bool) and x >= 1

try:
    paths = monte_carlo_gbm(..., steps_per_year=spy)
except ValueError as e:
    if "steps_per_year" in str(e):
        paths = monte_carlo_gbm(..., steps_per_year=int(round(1 / spy)) if 0 < spy < 1 else int(spy))
    else:
        raise

When it happens

Trigger: monte_carlo_gbm(..., steps_per_year=0), or passing a fractional/intraday-miscomputed value like steps_per_year=1/252 (inverting the convention, i.e. passing step size instead of frequency).

Common situations: Confusing 'step size in years' with 'steps per year' — passing 1/252 instead of 252; deriving the value from an empty trading calendar.

Related errors

• s0 must be > 0, got {s0}
• sigma must be >= 0, got {sigma}
• n_steps and n_paths must be >= 1, got {n_steps} and {n_paths
• paths must be 2-D with >= 2 columns, got shape {matrix.shape
• paths column 0 (the starting price) must be strictly positiv

AI-assisted analysis of HKUDS/Vibe-Trading@80ffdda44c (2026-08-28). Data as JSON: /api/errors/69c4619ffce6f796. Report an issue: GitHub.