Use this when the user wants scenario ranges, risk, or path statistics for a
ticker (e.g. SPY, AAPL): price/return percentiles, annualized volatility,
max-drawdown percentiles, and loss/gain probabilities at 7d, 30d, 3m, 6m,
1y, 3y, 5y, and 10y trading-day horizons.

Downloads max adjusted daily closes, fits EGARCH(1,1) with leverage
(o=1) and skewed-t innovations (historical mean drift), then simulates
``n_paths`` paths.

Prefer ``inspect_asset_model`` first only when you need fit/data diagnostics
without simulating paths.

Args:
    ticker: Yahoo Finance ticker symbol (e.g. SPY, AAPL).
    n_paths: Number of Monte Carlo paths (default 5000, minimum 100).

Call this when you need to validate data quality or model sanity before (or
instead of) a full Monte Carlo forecast — for example: Is there enough
history? What is today's conditional volatility? Do residuals look heavily
skewed/fat-tailed? What are the fitted EGARCH and skew-t parameters?

Do NOT use this for forward price scenarios, percentiles, drawdowns, or
probabilities — use ``forecast_asset_monte_carlo`` for those.

Returns JSON with history span, last price, fitted parameters, AIC/BIC,
last conditional volatility (daily and annualized), and residual
skewness/excess kurtosis.

Args:
    ticker: Yahoo Finance ticker symbol (e.g. SPY, AAPL).