Bitcoin Price Predictor

📋 Overview

The Bitcoin Price Predictor is an Apify actor that leverages machine learning algorithms to forecast Bitcoin (BTC) prices based on historical market data. Perfect for traders, researchers, and crypto enthusiasts who want to analyze market trends and make data-driven predictions.

What does this actor do?

This actor fetches real-time Bitcoin price data from CoinGecko's free API and uses statistical models to predict future price movements. It analyzes historical patterns, calculates market volatility, and generates price forecasts for up to 30 days into the future.

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✨ Features

📊	Real-time Data	Fetches current Bitcoin prices and historical data automatically from CoinGecko API
🤖	Dual Prediction Models	Choose between Linear Regression (trend-based) or Moving Average (volatility-adjusted) algorithms
📈	Flexible Timeframes	Predict anywhere from 1 to 30 days into the future
📉	Comprehensive Analytics	Includes volatility calculations, weekly change percentages, and trend analysis
🎯	Monthly Predictions	Optional 30-day long-term forecast for extended planning
💾	Structured Output	Returns clean, organized data in multiple views for easy analysis
🆓	No API Keys	Uses free CoinGecko API with no authentication required
⚡	Fast Execution	Typically completes in 10-30 seconds

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🚀 Quick Start

Using Apify Console

1. Open the actor in Apify Console
2. Configure inputs:
   • Set prediction timeframe (1-30 days)
   • Choose historical data range (7-365 days)
   • Select prediction model
3. Click "Start" to run the actor
4. View results in organized tabs

Using API

curl -X POST https://api.apify.com/v2/acts/YOUR_USERNAME~bitcoin-price-predictor/runs \
  -H "Authorization: Bearer YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "predictionDays": 7,
    "historicalDays": 30,
    "modelType": "linear",
    "includeMonthlyPrediction": true
  }'

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⚙️ Configuration

Input Parameters

Parameter	Type	Default	Range	Description
predictionDays	Integer	7	1-30	Number of days into the future to predict
historicalDays	Integer	30	7-365	Days of historical data to analyze for training the model
modelType	String	"linear"	"linear", "moving_average"	Prediction algorithm to use
includeMonthlyPrediction	Boolean	true	true/false	Generate additional 30-day forecast

Prediction Models

Linear Regression (linear)

Moving Average (moving_average)

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📊 Output

Output Views

The actor provides four organized views of the prediction data:

Sample Output

{
  "timestamp": "2026-01-15T01:28:44.109Z",
  "currentPrice": "96580.96",
  "weeklyChangePercent": "-0.68",
  "volatility": "367.56",
  "historicalDays": 30,
  "predictionDays": 7,
  "modelType": "linear",
  "predictions": [
    {
      "date": "2026-01-16",
      "predictedPrice": "92776.64",
      "changeFromCurrent": "-3.94%"
    },
    {
      "date": "2026-01-17",
      "predictedPrice": "92785.85",
      "changeFromCurrent": "-3.93%"
    }
  ],
  "monthlyPrediction": {
    "date": "2026-02-14",
    "predictedPrice": "93043.89",
    "changeFromCurrent": "-3.66%",
    "daysAhead": 30
  },
  "historicalData": [
    {
      "date": "2026-01-14",
      "price": "97258.43"
    }
  ],
  "disclaimer": "This prediction is for educational purposes only. Cryptocurrency investments carry significant risk."
}

Output Fields

Field	Type	Description
timestamp	String	ISO 8601 timestamp when prediction was generated
currentPrice	String	Current Bitcoin price in USD
weeklyChangePercent	String	Price change over the last 7 days
volatility	String	Standard deviation of price movements (in USD)
predictions	Array	Daily predictions with dates and prices
monthlyPrediction	Object	30-day forecast (if enabled)
historicalData	Array	Last 10 days of actual prices

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💡 Use Cases