Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/skloxo/tidetrading/quant-statisticsnpx skills add skloxo/TideTrading --skill quant-statisticsgit clone --depth 1 https://github.com/skloxo/TideTradingWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/skloxo/tidetrading/quant-statistics)<a href="https://agentmods.dev/skills/skloxo/tidetrading/quant-statistics"><img src="https://agentmods.dev/badge/skills/skloxo/tidetrading/quant-statistics.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00041 | $0.03972 |
| Opus 5 | $0.00020 | $0.01986 |
| Sonnet 5 | $0.00008 | $0.00794 |
| Haiku 4.5 | $0.00004 | $0.00397 |
Grade A, and why
quant-statistics scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 451 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Quantitative Statistical Methods
Overview
Common statistical methodology used in quantitative investing, covering time-series testing, volatility modeling, regression diagnostics, and statistical inference. Provides the statistical foundation for strategy development and factor research.
Time-Series Tests
1. ADF Unit-Root Test (Stationarity Test)
Why it matters: regressing non-stationary series directly can produce spurious regression, making conclusions unreliable.
from statsmodels.tsa.stattools import adfuller
def adf_test(series: pd.Series, significance: float = 0.05) -> dict:
"""
ADF test: H0 = unit root exists (non-stationary), H1 = stationary
Args:
series: Time series
significance: Significance level
Returns:
Test result
"""
result = adfuller(series.dropna(), autolag='AIC')
return {
'adf_statistic': result[0],
'p_value': result[1],
'lags_used': result[2],
'is_stationary': result[1] < significance,
'critical_values': result[4], # 1%, 5%, 10%
}
Decision rules:
| p-value | Conclusion | Action |
|---|---|---|
| < 0.01 | Strongly stationary | Can be used directly for regression / modeling |
| 0.01-0.05 | Stationary | Usable |
| 0.05-0.10 | Weak evidence | Difference the series and retest |
| > 0.10 | Non-stationary | Must difference or handle with cointegration |
Stationarity of common financial series:
| Series | Typical Result | Treatment |
|---|---|---|
| Price series | Non-stationary (unit root) | Use log returns |
| Log returns | Stationary | Can be used directly |
| PE / PB series | Usually non-stationary | Use changes or logs |
| Volatility series | Usually stationary | Can be used directly |
| Volume | May be non-stationary | Use logs or standardization |
2. Cointegration Test
Purpose: determine whether two non-stationary series share a long-run equilibrium relationship (the foundation of pair trading / statistical arbitrage).
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 451 lines · 41 tokens per session scan A 45f3c6d5cd6f
quant-statistics is a skill published in the GitHub repository skloxo/TideTrading (10 stars, last pushed yesterday), licensed MIT. It adds 41 tokens to every session and 3,972 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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