risk
Read-onlyIdempotent
Calculate pre-computed downside metrics like VaR, CVaR, volatility, drawdown, skewness and kurtosis for tickers or weighted portfolios, with rolling windows and daily-to-yearly periods.
Instructions
Pre-computed risk metrics (VaR incl. historic/gaussian/cf/studentt/evt distributions, CVaR, EVaR, GARCH volatility, max drawdown, drawdown duration, drawdown recovery time, Conditional Drawdown at Risk (CDaR), Tail Ratio, skewness, kurtosis, downside deviation, Variance, Volatility incl. close_to_close/parkinson/garman_klass/rogers_satchell/yang_zhang estimators, Excess Volatility). VaR, CVaR, skewness, kurtosis, CDaR, Tail Ratio, downside deviation, Variance, Volatility and Excess Volatility support rolling=N for a rolling N-period value spanning the full history instead of one value per period (e.g. period='monthly', rolling=6 for a rolling 6-month figure). Requires tickers='AAPL' — use comma-separated values for multiple tickers. Supports period='daily' for whole-series calculations; rolling and per-period outputs use weekly, monthly, quarterly, or yearly. get_copula_simulation returns 100 simulated joint draws unless n_simulations= asks for more. get_amihud_illiquidity is the price impact per billion dollars traded (scale=1e9).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| k | No | The number of upper order statistics to use. If a float in (0, 1) it is interpreted as the fraction of the strictly positive observations to use. | |
| q | No | The threshold quantile used for the "empirical" method, in (0.5, 1). | |
| dof | No | The degrees of freedom of the Student-T copula, only used when `method="student-t"`. | |
| lag | No | Number of periods to lag when computing growth rates. | |
| lags | No | The number of lags (past periods) the test or model uses, e.g. 1 or 5. | |
| tail | No | Which tail to estimate, one of "left" (the loss tail) or "right" (the gain tail). | left |
| test | No | Which test(s) to run, one of "kupiec", "christoffersen" or "both". | both |
| alpha | No | The confidence level (e.g., 0.05 for 95% confidence). | |
| limit | No | The rows to return, like head and tail: 5 for the first five, -5 for the last five (the most recent of a time series). A table with its periods as columns (financial statements, ratios) keeps its first or last periods instead. For ETF holdings the largest (or, negative, the smallest) by weight, and for a list (e.g. news or a screener) its length. | |
| scale | No | A multiplier applied to the resulting ratio purely for readability. Leave unset to use the default of the indicator you selected. Defaults are 1000000000 for get_amihud_illiquidity. | |
| column | No | The price column to use, e.g. 'Close' or 'Adj Close'. | Return |
| copula | No | For get_copula_parameters: The copula family to fit, one of "gaussian", "student-t", "clayton", "gumbel" or "frank". For get_copula_simulation: The copula family to fit and simulate from, one of "gaussian", "student-t", "clayton", "gumbel" or "frank". | gaussian |
| fisher | No | Whether to use Fisher's definition of kurtosis (kurtosis = 0.0 for a normal distribution). | |
| growth | No | Return period-over-period growth rates instead of absolute values. | |
| method | No | For get_tail_dependence_coefficient: The estimation method, one of "empirical", "gaussian" or "student-t". For get_volatility: Which Volatility estimator to use, one of "close_to_close", "parkinson", "garman_klass", "rogers_satchell" or "yang_zhang". Leave unset to use the default of the indicator you selected. Defaults are 'close_to_close' for get_volatility; 'empirical' for get_tail_dependence_coefficient. | |
| period | No | Observation frequency, e.g. 'daily', 'weekly', 'monthly', 'quarterly', or 'annual' (supported values differ per method). | |
| ticker | No | The asset whose conditional VaR is being measured. Leave unset to use the default of the indicator you selected. Required by: get_covar. | |
| horizon | No | The number of days ahead to forecast. | |
| lambda_ | No | The decay factor. Higher values weight the past more heavily (slower to react), lower values weight recent returns more heavily (faster to react). RiskMetrics uses 0.94 for daily data. | |
| max_lag | No | The maximum lag to use when estimating the exponent. | |
| rolling | No | Rolling window size in number of periods. When set, the metric is computed over a smoothly overlapping trailing window across the full history (e.g. period='monthly' and rolling=6 gives a rolling 6-month value) instead of one value per period, or (for economics indicators) a simple moving average used to smooth the raw series. Leave unset to use the default of the indicator you selected. Defaults are None for get_conditional_drawdown_at_risk, get_conditional_value_at_risk, get_downside_deviation, get_excess_volatility, get_kurtosis, get_skewness, get_tail_ratio, get_value_at_risk, get_variance, get_volatility; 14 for get_ulcer_index. | |
| tickers | No | Comma-separated ticker symbols, e.g. 'AAPL,MSFT,GOOGL'. | |
| weights | No | The portfolio weight per ticker as an object, e.g. {'AAPL': 0.6, 'MSFT': 0.4}; equal weights when left unset. | |
| end_date | No | End of the date range in YYYY-MM-DD format. | 2026-10-14 |
| ticker_a | No | The first asset. Leave unset to use the default of the indicator you selected. Required by: get_tail_dependence_coefficient. Defaults are None for get_best_fitting_copula, get_copula_parameters, get_copula_simulation. | |
| ticker_b | No | The second asset. Leave unset to use the default of the indicator you selected. Required by: get_tail_dependence_coefficient. Defaults are None for get_best_fitting_copula, get_copula_parameters, get_copula_simulation. | |
| estimator | No | How to construct the daily Realized Variance input, one of "squared_return", "parkinson", "garman_klass" or "rogers_satchell". | squared_return |
| indicator | Yes | Name of the specific metric to calculate, one of the listed values. Required — search_metrics finds the indicator (and its tool) for a metric by name. | |
| quarterly | No | Return quarterly data instead of annual when True. | |
| start_date | No | Start of the date range in YYYY-MM-DD format. | 2021-10-15 |
| time_steps | No | Time steps to calculate GARCH for. Leave unset to use the default of the indicator you selected. Defaults are 10 for get_garch_forecast, get_gjr_garch_forecast; None for get_garch, get_gjr_garch. | |
| n_bootstrap | No | The number of bootstrap resamples used to estimate the Standard Error of Z2. | |
| standardize | No | Return the Z-Score (standard score) instead of the raw values, i.e. how many standard deviations each value is from the mean of its own series. When combined with growth=True, the growth values are standardized instead of the raw values. | |
| window_size | No | For get_acerbi_szekely_test: The rolling window size (in number of return observations) used to estimate each VaR/CVaR value. For get_var_backtest: The rolling window size (in number of return observations) used to estimate each VaR value. | |
| distribution | No | The distribution to use for the rolling VaR estimates, one of "historic", "gaussian", "studentt" or "evt". | historic |
| random_state | No | For get_acerbi_szekely_test: The seed for the bootstrap random number generator. For get_copula_simulation: The seed for the random number generator. | |
| show_columns | No | Comma-separated names to filter the output. For historical data use the key names visible in any response record (e.g. 'Close,Volume,Return'). For financial statements use the 'metric' field values from the response (e.g. 'Revenue,Net Income,EBITDA'). Call the tool once without this parameter to see all available names, then repeat with show_columns to reduce response size and token usage. | |
| n_simulations | No | The number of joint draws to simulate. Leave unset to use the default of the indicator you selected. Defaults are 100 for get_copula_simulation. | |
| weekly_window | No | The trailing window (in trading days) for the weekly RV component. | |
| within_period | No | Whether to calculate GJR-GARCH within each specified period or all at once. | |
| monthly_window | No | The trailing window (in trading days) for the monthly RV component. | |
| optimization_t | No | For get_garch: Time steps to optimize GARCH for. It is only used if no weights are given. For get_garch_parameters, get_gjr_garch_parameters: Time steps of the returns series to use for the optimization. For get_gjr_garch: Time steps to optimize GJR-GARCH for. It is only used if no weights are given. | |
| benchmark_ticker | No | Ticker used as the market benchmark, e.g. 'SPY' or '^GSPC'. | SPY |
| empirical_margins | No | Whether to map the simulated pseudo-observations back to realistic returns via each asset's own empirical (historical) quantile function. When False, the raw pseudo-observations (each in (0, 1)) are returned instead. | |
| show_full_results | No | Only relevant when neither ticker is given. When False (the default), returns a square ticker-by-ticker grid of just the winning copula family per pair. When True, returns one row per pair instead, with the winning family's fitted parameter(s), Lower and Upper Tail Dependence, Log-Likelihood,... | |
| conditioning_ticker | No | The asset (or e.g. a benchmark/index) whose distress `ticker` is conditioned on. Leave unset to use the default of the indicator you selected. Required by: get_covar. | |
| threshold_percentile | No | Only used when distribution='evt'. The percentile of losses above which the Generalized Pareto Distribution is fitted, e.g. 0.95 fits on the worst 5% of losses. | |
| minimum_acceptable_return | No | The minimum acceptable return (MAR) threshold below which returns are considered downside, e.g. 0.0 for downside relative to a zero return. |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |