--- name: fintech-algorithms description: Compute market-data, trading and quantitative analytics with the `fintech-algorithms` npm package — 675 zero-dependency TypeScript algorithms covering statistics and financial-mathematics foundations (mean, median, percentiles, standard deviation, correlation, regression, distributions, z-scores, log returns, volatility, drawdown, Sharpe, value at risk), technical indicators (RSI, MACD, moving averages, Bollinger Bands, ATR, OBV, Stochastic), candlestick and chart patterns, market breadth, bar construction from tick data, OHLC validation and cleaning, corporate actions, index and benchmark construction, market microstructure, matching engines, execution and TCA, statistical time series, credit risk and probability of default, classifier and score validation (ROC, AUC, Brier, calibration), on-chain metrics and EPS analytics. Use when asked to analyse a price series, compute a statistic or summary, compute or explain an indicator, detect a candlestick or chart pattern, build bars from ticks, validate or clean market data, score or validate a model, wire up a market-data provider, or when writing code that needs any of these calculations to be correct rather than approximated. metadata: version: 0.13.0 --- # fintech-algorithms 675 pure functions for market, financial and statistical calculations. Plain arrays and objects in, plain values out. Zero runtime dependencies, Node >= 22, ESM. **Docs:** https://docs.thefintechbuilder.com · **Authoritative agent guide:** https://docs.thefintechbuilder.com/guides/ai-agents/ ## Non-negotiables Four rules. Breaking any one produces output that looks right and is wrong. 1. **Never invent an import path, a function name, or a parameter.** Every subpath mirrors its docs URL exactly, which makes a plausible guess wrong in a way that reads as correct. Look it up — `scripts/lookup.mjs` or the resolution order below. If the topic does not exist, say so and stop. 2. **Never guess a returned field name.** Return-key casing is not consistent across the library: `bollingerBands` returns `percent_b`, `macd` rows return `fastEma`. Read the captured example output for that topic. See `references/pitfalls.md`. 3. **State the verification tier** on any numeric claim. `verified` (601 topics) means the arithmetic is replayed and asserted on every build against expected values the catalog computed with a Python implementation written alongside the TypeScript — cross-language parity, not an independent third-party figure. Say it that way if asked. `contract` (74 topics) means the signature and shape are checked but nothing asserts the numbers. 4. **Analysis, not advice.** These functions compute quantities. An indicator crossing is an observation about a series — not a prediction, not a signal, and never a recommendation for a specific person's money. Report what was computed, on what input, at which tier. If asked what to buy or sell, say that is a question for a licensed adviser. ## The library does not fetch data There is no HTTP client, no vendor SDK, no API key, no `node:fs`. If a task needs prices, the caller supplies them. This is deliberate: vendor APIs get rewritten every few years and algorithms do not. When a user wants "live analysis", the shape is always: **their feed → their adapter → validate → compute → report.** Only the middle two steps are this library. Load `references/ingestion.md` for the adapter pattern and the canonical `Trade` / `Bar` shapes. ## Which surface answers which question Five things carry this library's name. Sending a question to the wrong one is the most common way to end up guessing. | Surface | Answers | Do not use it for | |---|---|---| | `node_modules/fintech-algorithms/docs.json` | signature, contract, worked example, verification tier | — **prefer this for everything** | | `docs.thefintechbuilder.com` | the same reference, over the network | prose about why an algorithm exists | | `thefintechbuilder.com` | the article — what the algorithm is and when to reach for it | signatures or field names; it teaches, it does not specify | | the npm package | the code you import | discovering what exists — the registry does that | | this skill | how to look any of it up | as a substitute for looking it up | Two relationships matter and are enforced, not conventional: - **A docs URL and an import path are the same string.** Swap `https://docs.thefintechbuilder.com/` for `fintech-algorithms/`, drop the trailing slash. A test fails if that ever stops being true. - **The docs can be ahead of npm.** The site rebuilds from `main` without a release. If a documented topic will not import, the installed version is older than the page — check `https://docs.thefintechbuilder.com/version.json` before concluding anything is broken. A topic may ship a hand-written implementation from the repository's `optimised/` tree instead of the catalog's. It is asserted to return identical values and throw identical errors, so it changes nothing you report — but the code in the article and the code in the package can legitimately differ. ## Resolution order Stop at the first step that answers the question. 1. **Installed package** — if `fintech-algorithms` is a dependency, read `node_modules/fintech-algorithms/docs.json`. Every signature, contract and worked example, no network. **Prefer this.** `scripts/lookup.mjs` uses it automatically. 2. **Domain index** — `https://docs.thefintechbuilder.com/{domain-slug}/llms.txt` (3–11 KB each). The map of all seventeen is the `## Per-domain indexes` block at the top of `/llms.txt`; one root fetch gives a permanent routing table. 3. **Topic markdown** — append `index.md` to any docs URL. The full contract in 3–11 KB instead of 68–114 KB of HTML. 4. **Full payload** — `https://docs.thefintechbuilder.com/reference/payload.json` (~2.6 MB). For ingestion, not for answering one question. Turn a docs URL into an import: swap `https://docs.thefintechbuilder.com/` for `fintech-algorithms/` and drop the trailing slash. Check the installed version matches the docs with `https://docs.thefintechbuilder.com/version.json` (under 1 KB). ## Workflow **1. Identify the quantity.** What is actually being asked for? "Is this overbought" → RSI. "Smooth this" → which moving average, and why that one. **2. Narrow by archetype before fetching anything.** Five input shapes cover all 675 topics, and the archetype is on every index line: | Archetype | Takes | Returns | Count | |---|---|---|---| | `series-transform` | `(number \| null)[]` + numeric params | same-length array | 137 | | `tape-aggregate` | `Trade[]` + config | `Bar[]` | 7 | | `row-classify` | rows | one verdict per row | 24 | | `snapshot-evaluate` | one snapshot + decision time | one verdict | 6 | | `record-transform` | domain-specific | domain-specific | 501 | `record-transform` is the residual bucket — read that topic's own contract. Details and executed examples: `references/archetypes.md`. **3. Read the contract.** Signature, params, returns, **warm-up**, errors. ```bash node scripts/lookup.mjs show rsi ``` **4. Shape the data.** Map the user's payload into the documented input. Run the boundary validator first when the input is bars, ticks or quotes. **5. Compute and report.** Say what was computed, on what input, at which tier, and how many leading values are warm-up rather than signal. ## Quick start ```bash npm install fintech-algorithms ``` Algorithms are **subpath-only**. The root export carries metadata and lookups (`topics`, `topic`, `byDomain`, `byFamily`, `byArchetype`, `load`, `runner`) and re-exports no algorithm. A sibling topic's function is never re-exported from another subpath — import each from its own. ```js import { calculateSma } from "fintech-algorithms/technical-indicators/trend-smoothing/sma"; calculateSma([44.34, 44.09, 44.15, 43.61, 44.33, 44.83], 5); // → [null, null, null, null, 44.104, 44.202] // ^^^^ four warm-up nulls: window - 1 ``` The `require` condition resolves to the same ES module — there is no separate CommonJS build, so `require()` needs a runtime supporting `require(esm)`. ## The lookup script `scripts/lookup.mjs` sits next to this file. The working directory is the user's project, not the skill, so always invoke it by absolute path. **These files write `${SKILL_DIR}` for the directory containing this SKILL.md.** In Claude Code that is `${CLAUDE_SKILL_DIR}`, which the harness substitutes for you. In any other agent, substitute the real path before running the command. ```bash node "${CLAUDE_SKILL_DIR}/scripts/lookup.mjs" search "moving average" ``` Commands: | Command | Does | |---|---| | `search ` | find topics by name, slug, family or entry | | `show ` | full contract, warm-up, errors, executed example | | `archetype ` | every topic sharing an input shape, plus its caveat | | `domain ` | every topic in a domain, grouped by family | | `domains` | the seventeen domains with their index URLs | | `version` | the reference version vs the published one | Reads `node_modules/fintech-algorithms/docs.json` when the package is installed anywhere above the working directory; otherwise fetches and caches the published payload for a day. Set `FINTECH_DOCS_JSON` to point it at a specific file. Accepts a slug (`rsi`), a catalog id (`D07-F03-A01`), a full path, or a docs URL. If `show` cannot find the topic it says so rather than guessing — that failure is the correct answer, not an obstacle to route around. ## Load a reference when - **`references/archetypes.md`** — mapping user data into an input shape, or deciding how much adapter code a task needs. - **`references/ingestion.md`** — the user has a provider, a CSV, a websocket or a broker API and asks how to connect it. - **`references/recipes.md`** — an end-to-end task: clean a feed, build bars, compute a multi-indicator report. - **`references/pitfalls.md`** — before finalising any numeric answer. Short, and every entry is a real failure mode with a real cause. ## Coverage 17 domains: Financial Mathematics, Statistics, and Data Foundations (120) · Market Data Engineering (31) · Corporate Actions and Security Master Data (20) · Index and Benchmark Engineering (40) · Market Breadth and Internals (28) · Price Action and Candlesticks (52) · Technical Indicators (137) · Geometric Chart Patterns (64) · Statistical Time Series (37) · Market Microstructure (29) · Matching Engines and Venue Logic (21) · Execution and Transaction Cost Analysis (9) · Fundamental Analysis and Valuation (52) · Credit Risk and Default (7) · Digital Assets and On-Chain Finance (10) · Model Validation and Backtesting (10) · Earnings and Per-Share Analytics (8). Technical Indicators, Price Action and Geometric Chart Patterns are complete for the first time in 0.13.0 — every topic in the catalog is installable. **Reach for the foundations domain first.** Financial Mathematics, Statistics, and Data Foundations is the base layer the rest of the library is built on — one implementation each of mean, median, percentile, standard deviation, correlation, regression, z-score, log return, volatility, drawdown, Sharpe and value at risk, rather than a private copy inside every indicator. When a task needs a plain statistic, import it from there instead of hand-rolling one or borrowing an indicator's internals. It is intentionally absent from the package README, which indexes the market-facing algorithms; it is fully present here and in the docs. Not a backtester, an execution system, a portfolio manager, or a source of market data. It computes quantities, places no orders, and holds no state between calls.