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JerBouma

Finance Toolkit

by JerBouma

risk

Read-onlyIdempotent

Compute financial risk indicators like Value at Risk, Conditional VaR, GARCH volatility, and drawdown duration. Input tickers, select period frequency, and choose rolling windows.

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, 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. Does NOT support period='daily'; use weekly, monthly, quarterly, or yearly instead.

Available indicators: get_autocorrelation, get_coefficient_of_variation, get_conditional_drawdown_at_risk, get_conditional_value_at_risk, get_downside_deviation, get_entropic_value_at_risk, get_ewma_volatility, get_excess_volatility, get_garch, get_garch_forecast, get_hurst_exponent, get_kurtosis, get_maximum_drawdown, get_maximum_drawdown_duration, get_maximum_drawdown_recovery_time, get_mean_absolute_deviation, get_skewness, get_tail_ratio, get_ulcer_index, get_value_at_risk, get_variance, get_volatility.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lagNoNumber of periods to lag when computing growth rates.
lagsNoValue for lags.
alphaNoValue for alpha.
fisherNoValue for fisher.
growthNoReturn period-over-period growth rates instead of absolute values.
periodNoObservation frequency, e.g. 'monthly', 'quarterly', or 'annual'.
lambda_NoValue for lambda_.
max_lagNoValue for max_lag.
rollingNoRolling 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.
tickersNoComma-separated ticker symbols, e.g. 'AAPL,MSFT,GOOGL'.
end_dateNoEnd of the date range in YYYY-MM-DD format.2026-07-14
indicatorYesName of the specific metric to calculate, e.g. 'get_asset_turnover_ratio'. Required — omitting it returns the list of available indicators.
quarterlyNoReturn quarterly data instead of annual when True.
start_dateNoStart of the date range in YYYY-MM-DD format.2021-07-15
time_stepsNoValue for time_steps.
standardizeNoReturn 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.
distributionNoValue for distribution.historic
show_columnsNoComma-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.
within_periodNoValue for within_period.
optimization_tNoValue for optimization_t.
benchmark_tickerNoTicker used as the market benchmark, e.g. 'SPY' or '^GSPC'.SPY
threshold_percentileNoOnly 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_returnNoThe minimum acceptable return (MAR) threshold below which returns are considered downside, e.g. 0.0 for downside relative to a zero return.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true, so the description adds value by detailing constraints (no daily period) and rolling behavior. However, it does not disclose potential pitfalls, output format, or error conditions beyond what annotations provide. No contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is information-dense and lists all indicators and many constraints. It front-loads the main purpose but could be more structured (e.g., bullet points). Some redundancy exists between the description and the schema descriptions. It is functional but not optimally concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (23 parameters, many indicators), the description covers the main purpose, key constraints, and parameter behavior. An output schema exists (not shown) which likely handles return values. The description lists all available indicators and explains rolling and not-daily constraints, making it fairly complete for a risk metrics tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptions for all 23 parameters, so baseline is 3. The description adds extra meaning by explicitly stating that period does not support daily and explaining the rolling parameter behavior in more detail than the schema. It also mentions that omitting indicator returns a list of available indicators.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool computes risk metrics, listing many specific indicators like VaR, CVaR, GARCH, drawdowns, etc. It is specific about the resource (risk metrics) and verb (compute/list). However, it does not explicitly distinguish from sibling tools like 'volatility', which may overlap, though it includes volatility as one of many metrics.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides key usage constraints: requires tickers, does not support period='daily', and explains rolling behavior. It also lists all available indicators. However, it does not explicitly state when to use this tool versus alternatives (e.g., 'volatility' or 'performance'), nor when not to use it beyond the daily period restriction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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