# Fed Rate Tracker — FOMC Target Rate & Market Rates (FRED) (`gochujang/fed-rate-probability`) Actor

Tracks Federal Reserve target rate, effective fed funds rate, SOFR, and Fed dot-plot projections via FRED (St. Louis Fed). No API key required. Useful for macro research, interest rate trend analysis, and monetary policy monitoring.

- **URL**: https://apify.com/gochujang/fed-rate-probability.md
- **Developed by:** [Hojun Lee](https://apify.com/gochujang) (community)
- **Categories:** News, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-usage

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Fed Rate Tracker — NY Fed & US Treasury Rates

**Fed Rate Tracker** fetches official Federal Reserve interest rates from two authoritative public APIs — **NY Fed Reference Rates** (EFFR, SOFR, OBFR) and **US Treasury Yield Curve** (1M to 30Y) — in one structured dataset. No API key required. $0.001/record.

The Fed Funds Rate and Treasury yield curve are the anchors of global macro. Every risk asset — stocks, crypto, bonds — prices off the risk-free rate. This actor gives you the official data directly, updated daily, without navigating government portals.

***

### Why use Fed Rate Tracker?

1. **Yield curve inversion monitoring** — Compute 2Y–10Y spreads to track the recession signal. A persistently inverted curve has preceded every US recession since the 1970s. Automate daily alerts.
2. **FOMC decision detection** — The `target_rate_from`/`target_rate_to` fields change when the Fed raises or cuts rates. Schedule daily runs and detect rate changes the day they happen.
3. **SOFR monitoring** — SOFR replaced LIBOR as the benchmark for floating-rate debt. Track it alongside EFFR to understand the overnight lending market for risk modeling.
4. **Crypto/equity macro correlation** — Feed current 10Y Treasury yield into models alongside BTC price. Rising rates → risk-off → crypto headwinds. Automate this signal.
5. **Multi-timeframe rate analysis** — `outputFormat: "timeseries"` gives you the full historical series for trend analysis. Track rate cycles across years.

***

### How to use

1. Open the actor on Apify Store and click **Try for free**.
2. Set `sources` to `nyfed`, `treasury`, or both.
3. Set `startDate`/`endDate` for historical range, or `latestOnly: true` for just today's values.
4. Click **Start**. Returns structured rate records per series per date.

***

### Input

| Field | Type | Default | Description |
|-------|------|---------|-------------|
| `sources` | string\[] | `["nyfed","treasury"]` | Data sources: `nyfed`, `treasury` |
| `startDate` | string | 1 year ago | Treasury yield curve start (YYYY-MM-DD) |
| `endDate` | string | today | Treasury yield curve end (YYYY-MM-DD) |
| `outputFormat` | string | `"records"` | `records` (one row/series/date) or `timeseries` |
| `latestOnly` | boolean | `false` | Return only the most recent value per series |

***

### Output

**NY Fed rate record:**

```json
{
  "date": "2026-08-31",
  "series_id": "EFFR",
  "series_title": "Effective Federal Funds Rate",
  "value": 3.63,
  "units": "Percent",
  "source": "New York Federal Reserve",
  "target_rate_from": 3.5,
  "target_rate_to": 3.75,
  "percentile_1": 3.60,
  "percentile_75": 3.63,
  "volume_billion_usd": 105
}
```

**Treasury yield record:**

```json
{
  "date": "2026-08-31",
  "series_id": "BC_10YEAR",
  "series_title": "US Treasury 10 Year Yield",
  "value": 4.70,
  "units": "Percent",
  "source": "U.S. Department of the Treasury",
  "maturity": "10 Year"
}
```

#### Series covered

| Series | Description | Source |
|--------|-------------|--------|
| `EFFR` | Effective Federal Funds Rate (with percentiles + volume) | NY Fed |
| `SOFR` | Secured Overnight Financing Rate | NY Fed |
| `OBFR` | Overnight Bank Funding Rate | NY Fed |
| `TGCR` / `BGCR` | Tri-Party / Broad General Collateral Rates | NY Fed |
| `BC_1MONTH` to `BC_30YEAR` | Full Treasury yield curve | US Treasury |

***

### Cost estimation

**Pay-Per-Event: $0.005 flat + $0.001 per rate record.**

| Use case | Records | Estimated cost |
|----------|---------|----------------|
| Latest values only (~12 series) | 12 | ~$0.017/run |
| 1-year historical (12 series × 250 days) | 3,000 | ~$3.005/run |
| Daily monitoring (latest only) | 12/day | ~$0.017/day |
| Weekly yield curve snapshot | 12 × 7 | ~$0.089/week |

***

### FAQ

**How do I detect an FOMC rate change?**
Monitor `target_rate_from` and `target_rate_to` in EFFR records. A change in either field vs. the previous day = the Fed changed rates. Schedule daily and compare.

**What's the difference between SOFR and EFFR?**
EFFR is the rate banks charge each other for overnight uncollateralized loans. SOFR is the rate on overnight Treasury repo loans (collateralized). SOFR replaced LIBOR and is now the benchmark for most floating-rate financial contracts.

**How current is the data?**
NY Fed publishes reference rates by 9am ET each business day. Treasury yields are typically available by mid-afternoon. Weekends and holidays have no observations.

**Can I get the FOMC dot plot or rate probabilities?**
This actor provides official realized rates, not market-implied probabilities. For CME FedWatch-style probabilities, look for a dedicated actor.

***

### Related actors

- [Bank of Canada Rates](https://apify.com/gochujang/bank-of-canada-rates) — CAD yield curve + BoC policy rate for cross-border rate differential analysis
- [Crypto ETF Flow Tracker](https://apify.com/gochujang/crypto-etf-flow-tracker) — Institutional BTC demand that correlates inversely with rising rate periods
- [Altcoin BTC-Relative Performance](https://apify.com/gochujang/altcoin-btc-performance) — Risk-on alt season signal that tends to peak before rate hikes accelerate

### Feedback

If this actor helps your macro research, a review helps others find it: [Leave a review on Apify Store](https://apify.com/gochujang/fed-rate-probability#reviews)

# Actor input Schema

## `sources` (type: `array`):

Which data sources to fetch. 'nyfed' = NY Fed reference rates (EFFR, SOFR, OBFR, TGCR, BGCR). 'treasury' = US Treasury daily yield curve (1M to 30Y).

## `startDate` (type: `string`):

Observation start date in YYYY-MM-DD format. Applies to Treasury yield curve. NY Fed always returns the latest available rates. Default: 1 year ago.

## `endDate` (type: `string`):

Observation end date in YYYY-MM-DD format. Default: today.

## `outputFormat` (type: `string`):

records: one row per (series, date). timeseries: one row per series with all observations as a list.

## `latestOnly` (type: `boolean`):

If true, only the most recent observation per series is returned. Useful for dashboards and monitoring.

## Actor input object example

```json
{
  "sources": [
    "nyfed",
    "treasury"
  ],
  "startDate": "",
  "endDate": "",
  "outputFormat": "records",
  "latestOnly": false
}
```

# Actor output Schema

## `dataset` (type: `string`):

No description

## `summary` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("gochujang/fed-rate-probability").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("gochujang/fed-rate-probability").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call gochujang/fed-rate-probability --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,gochujang/fed-rate-probability"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/XPLUnuo8k14WGamcJ/builds/lhGYuOe9i5HDSw2D2/openapi.json