# ForexFactory Leaderboard Trader Tracker & Trading Signals (`brilliant_gum/forexfactory-signals`) Actor
Analyzes ForexFactory leaderboard traders' open positions across major currency pairs and gold. Generates LONG/SHORT signals based on top vs. poor performer positioning. Includes economic calendar with impact filtering.
- **URL**: https://apify.com/brilliant\_gum/forexfactory-signals.md
- **Developed by:** [Yuliia Kulakova](https://apify.com/brilliant_gum) (community)
- **Categories:** Developer tools, Automation, Other
- **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, NaN bookmarks
- **User rating**: No ratings yet
## Pricing
from $0.20 / trader analyzed
This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.
Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use 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
## ForexFactory Leaderboard Trader Tracker & Trading Signals
**Stop guessing. Trade with the crowd — or against it.**
This actor analyzes **real traders on ForexFactory's public leaderboard**, studies their open positions across major currency pairs, and generates **directional trading signals** based on where the best (and worst) performers are positioned right now.
---
### 💡 What You Get
- **Trading signals** (LONG / SHORT / NEUTRAL) for major forex pairs and gold — updated every run
- **Trader profiles** with full performance stats: return, win rate, profit factor, Sharpe ratio
- **Economic calendar** with high/medium/low impact events and affected currency pairs
- **Contrarian confirmation** — when top performers go long AND poor performers go short, the signal is flagged as **STRONG**
---
### 🚀 How It Works
ForexFactory hosts thousands of traders who publicly share their live trades. This actor:
1. Scrapes the **live trades feed** to identify active traders
2. Visits each trader's **profile** to collect performance statistics and open positions
3. **Classifies traders** — top 25% (Winners) vs bottom 25% (Losers) by composite score
4. **Aggregates positions** per currency pair with weighted scoring
5. Generates **actionable signals** — if Winners are long and Losers are short → **LONG signal**
6. Fetches **live prices** for all pairs from ForexFactory's market data API
7. Optionally scrapes the **economic calendar** for upcoming market-moving events
> The more traders analyzed, the more reliable the signal. We recommend **50–200 traders** for production use.
---
### 🎯 Modes
| Mode | What it does | Speed |
|------|-------------|-------|
| `signals` | Full leaderboard analysis → trading signals | 5–15 min |
| `traders` | Profile stats for specific usernames | 1–3 min |
| `calendar` | Economic calendar with impact filter | ~30 sec |
| `full` | Signals + calendar combined | 6–16 min |
---
### ⚙️ Input Examples
**Generate signals for major pairs:**
```json
{
"mode": "signals",
"pairs": ["EURUSD", "GBPUSD", "USDJPY", "XAUUSD"],
"maxTraders": 100
}
````
**Track specific traders:**
```json
{
"mode": "traders",
"trackUsernames": ["toptrader1", "forexking", "goldmaster"]
}
```
**Economic calendar — today, high impact only:**
```json
{
"mode": "calendar",
"calendarDays": "today",
"calendarImpact": ["high"]
}
```
**Full analysis — signals + calendar:**
```json
{
"mode": "full",
"pairs": ["EURUSD", "GBPUSD", "XAUUSD"],
"maxTraders": 50,
"calendarDays": "today",
"calendarImpact": ["high", "medium"]
}
```
***
### 📊 Output Example
**Trading Signal:**
```json
{
"type": "signal",
"pair": "EURUSD",
"signal": "LONG",
"strength": "STRONG",
"score": 64.54,
"contrarian": true,
"rationale": "LONG | top traders: 105L/57S | confirmed by poor performers",
"price": 1.16744,
"traderCount": 8,
"timestamp": "2026-05-14T15:11:17Z"
}
```
**Trader Profile:**
```json
{
"type": "trader",
"username": "hbanna",
"allTimeReturn": 716.7,
"weekReturn": 3.7,
"profitFactor": 2.58,
"sharpeRatio": 0.92,
"winRate": 86.8,
"openPairs": ["GBPUSD", "ETHUSD"]
}
```
**Calendar Event:**
```json
{
"type": "calendar",
"date": "Thu May 14",
"time": "1:30pm",
"currency": "USD",
"impact": "high",
"event": "Core Retail Sales m/m",
"forecast": "0.7%",
"previous": "1.9%",
"affectedPairs": ["EURUSD", "GBPUSD", "USDJPY", "XAUUSD"]
}
```
***
### 📋 Output Fields
#### Signal fields
| Field | Description |
|-------|-------------|
| `pair` | Currency pair (EURUSD, XAUUSD, etc.) |
| `signal` | LONG / SHORT / NEUTRAL |
| `strength` | STRONG / MODERATE / WEAK / N/A |
| `score` | Weighted net position score |
| `contrarian` | True if losers confirm the signal |
| `rationale` | Human-readable signal explanation |
| `price` | Current live price |
| `traderCount` | Number of traders with positions in this pair |
#### Trader fields
| Field | Description |
|-------|-------------|
| `allTimeReturn` | All-time account return (%) |
| `weekReturn` | This week's return (%) |
| `profitFactor` | Gross profit / gross loss ratio |
| `sharpeRatio` | Risk-adjusted return |
| `winRate` | Winning trades percentage |
| `openPairs` | Currently open currency pairs |
***
### 💰 Pricing
This actor uses **pay-per-event** billing — you only pay for what you scrape.
| Event | Price |
|-------|-------|
| Trader profile analyzed | **$0.20** |
| Calendar event | **$0.05** |
**Estimated run cost:**
- Calendar only (today, high impact) → **~$0.25–0.50**
- 3 specific traders → **~$0.60**
- Signals with 30 traders → **~$6**
- Signals with 100 traders → **~$20**
> 💡 For regular trading use, run with 30–50 traders on a schedule. Best value, reliable signals.
***
### 🎯 Use Cases
- **Algorithmic trading** — feed signals into your trading bot via API
- **Market research** — understand retail positioning on major pairs
- **Sentiment analysis** — track how the crowd is positioned before major news
- **Trader monitoring** — follow specific ForexFactory users and their open trades
- **News trading** — combine calendar events with positioning data for high-probability setups
***
### ⏰ Scheduling Tips
Run this actor on a schedule for fresh signals:
- **Signals** — every 4–8 hours for intraday positioning updates
- **Calendar** — once per day (morning) to plan your trading session
- **Full mode** — before major news events (NFP, CPI, FOMC)
***
### ⚠️ Notes
- ForexFactory uses Cloudflare protection — **residential proxies are required** and are included in the cost
- Signals reflect **current open positions**, not price predictions — always use with your own analysis
- More traders analyzed = more reliable signal. Minimum recommended: **20 traders**
# Actor input Schema
## `mode` (type: `string`):
signals — Scrape /trades feed, analyze trader profiles, generate signals per pair.
traders — Profile stats for specific usernames.
calendar — Economic calendar with impact levels.
full — Signals + calendar combined.
## `pairs` (type: `array`):
Pairs to generate signals for. Only trades on these pairs are counted.
## `maxTraders` (type: `integer`):
Maximum number of unique traders to analyze. More traders = more accurate signals.
💡 Recommended: 50–200. Larger samples reduce noise and improve signal reliability.
## `signalMinWNet` (type: `number`):
Minimum signal confidence threshold. Lower values produce more signals but with higher noise. Recommended: 1.5–3.0.
## `winnersPercent` (type: `integer`):
Top N% of traders by performance score classified as top performers.
## `losersPercent` (type: `integer`):
Bottom N% of traders by performance score classified as poor performers.
## `trackUsernames` (type: `array`):
ForexFactory usernames to scrape profile data for. Required for traders mode.
## `calendarImpact` (type: `array`):
Which impact levels to include in calendar output.
## `calendarDays` (type: `string`):
Which days to scrape from the economic calendar.
## `proxyConfiguration` (type: `object`):
Residential proxies are required — ForexFactory uses Cloudflare protection that blocks datacenter IPs.
## Actor input object example
```json
{
"mode": "signals",
"pairs": [
"EURUSD",
"GBPUSD",
"USDJPY",
"XAUUSD",
"XAGUSD",
"USDCHF",
"EURGBP"
],
"maxTraders": 20,
"signalMinWNet": 1.5,
"winnersPercent": 25,
"losersPercent": 25,
"calendarImpact": [
"high"
],
"calendarDays": "today",
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
]
}
}
```
# Actor output Schema
## `results` (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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"maxTraders": 20,
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
]
}
};
// Run the Actor and wait for it to finish
const run = await client.actor("brilliant_gum/forexfactory-signals").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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {
"maxTraders": 20,
"proxyConfiguration": {
"useApifyProxy": True,
"apifyProxyGroups": ["RESIDENTIAL"],
},
}
# Run the Actor and wait for it to finish
run = client.actor("brilliant_gum/forexfactory-signals").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"maxTraders": 20,
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
]
}
}' |
apify call brilliant_gum/forexfactory-signals --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=brilliant_gum/forexfactory-signals",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "ForexFactory Leaderboard Trader Tracker & Trading Signals",
"description": "Analyzes ForexFactory leaderboard traders' open positions across major currency pairs and gold. Generates LONG/SHORT signals based on top vs. poor performer positioning. Includes economic calendar with impact filtering.",
"version": "0.1",
"x-build-id": "wcuxjNt4Mj5VewtgV"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/brilliant_gum~forexfactory-signals/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-brilliant_gum-forexfactory-signals",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/brilliant_gum~forexfactory-signals/runs": {
"post": {
"operationId": "runs-sync-brilliant_gum-forexfactory-signals",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/brilliant_gum~forexfactory-signals/run-sync": {
"post": {
"operationId": "run-sync-brilliant_gum-forexfactory-signals",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"properties": {
"mode": {
"title": "🎯 Mode",
"enum": [
"signals",
"traders",
"calendar",
"full"
],
"type": "string",
"description": "signals — Scrape /trades feed, analyze trader profiles, generate signals per pair.
traders — Profile stats for specific usernames.
calendar — Economic calendar with impact levels.
full — Signals + calendar combined.",
"default": "signals"
},
"pairs": {
"title": "💱 Currency pairs",
"type": "array",
"description": "Pairs to generate signals for. Only trades on these pairs are counted.",
"default": [
"EURUSD",
"GBPUSD",
"USDJPY",
"XAUUSD",
"XAGUSD",
"USDCHF",
"EURGBP"
],
"items": {
"type": "string"
}
},
"maxTraders": {
"title": "👥 Max traders",
"minimum": 5,
"maximum": 500,
"type": "integer",
"description": "Maximum number of unique traders to analyze. More traders = more accurate signals.
💡 Recommended: 50–200. Larger samples reduce noise and improve signal reliability.",
"default": 20
},
"signalMinWNet": {
"title": "📊 Signal sensitivity",
"minimum": 0.5,
"maximum": 10,
"type": "number",
"description": "Minimum signal confidence threshold. Lower values produce more signals but with higher noise. Recommended: 1.5–3.0.",
"default": 1.5
},
"winnersPercent": {
"title": "🏆 Top performers (%)",
"minimum": 5,
"maximum": 50,
"type": "integer",
"description": "Top N% of traders by performance score classified as top performers.",
"default": 25
},
"losersPercent": {
"title": "📉 Poor performers (%)",
"minimum": 5,
"maximum": 50,
"type": "integer",
"description": "Bottom N% of traders by performance score classified as poor performers.",
"default": 25
},
"trackUsernames": {
"title": "👤 Track usernames",
"type": "array",
"description": "ForexFactory usernames to scrape profile data for. Required for traders mode.",
"items": {
"type": "string"
}
},
"calendarImpact": {
"title": "⚡ Calendar impact filter",
"type": "array",
"description": "Which impact levels to include in calendar output.",
"default": [
"high"
],
"items": {
"type": "string"
}
},
"calendarDays": {
"title": "📅 Calendar range",
"enum": [
"today",
"week"
],
"type": "string",
"description": "Which days to scrape from the economic calendar.",
"default": "today"
},
"proxyConfiguration": {
"title": "🔒 Proxy configuration",
"type": "object",
"description": "Residential proxies are required — ForexFactory uses Cloudflare protection that blocks datacenter IPs."
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```