How to Use the Mboum Screener API to Find High-Volume Stocks

Staff Member

Jan 09, 2026

Financial API , Stock Screener API , mboum api

In the fast-paced world of algorithmic and day trading, timing is everything. With thousands of stocks traded daily across US exchanges, manually scanning for opportunities is not just inefficient—it’s impossible. You need a way to filter the noise and identify the tickers that are actually moving.

This is where the Mboum Screener API becomes an essential tool for developers. Instead of streaming data for 5,000+ tickers and calculating volume spikes locally, you can offload that processing to Mboum and retrieve a curated list of stocks that meet specific criteria, such as high trading volume, technical patterns, or fundamental strength.

Get your API Key here:
https://mboum.com/pages/api

The Screener API Endpoint

To programmatically scan the market, we will use the v2 Screener endpoint. This endpoint is designed to return collections of stocks, ETFs, and mutual funds based on pre-defined market criteria.

Documentation:
https://docs.mboum.com/#stocks-options-GETapi-v2-markets-screener

Endpoint URL

https://api.mboum.com/v2/markets/screener

This endpoint relies heavily on two specific query parameters to refine your results:

metricType – This defines the category of data returned.
Common values include overview (for general price/volume data), technical (for indicators), and fundamental.
filter – This is the most powerful parameter.
It accepts specific presets that filter the market for you. For high-volume trading strategies, the high_volume filter is particularly useful, as it returns stocks with strong volume gains from previous sessions and positive momentum.

Other useful filters available in the documentation include hot_stocks, top_tech, golden_cross, and penny_gap.

Python Example: Finding High-Volume Stocks

Let’s build a Python script that queries the Mboum API to find stocks exhibiting high volume and positive momentum. We will use the requests library to handle the API call.

Ensure you replace {YOUR_AUTH_KEY} with your actual API token from your dashboard.

import requests
import json

# Define the endpoint
url = "https://api.mboum.com/v2/markets/screener"

# Define the parameters
# We want an 'overview' of stocks matching the 'high_volume' criteria
querystring = {
    "metricType": "overview",
    "filter": "high_volume", 
    "page": "1"
}

# Set up authentication
headers = {
    "Authorization": "Bearer {YOUR_AUTH_KEY}",
    "Accept": "application/json"
}

try:
    # Make the GET request
    response = requests.get(url, headers=headers, params=querystring)
    
    # Check if the request was successful
    if response.status_code == 200:
        data = response.json()
        
        # Output the results
        print(f"Found {data['meta']['count']} high-volume stocks:")
        for stock in data['body']:
            print(f"{stock['symbol']} ({stock['symbolName']}): ${stock['lastPrice']} | Vol: {stock['volume']}")
    else:
        print(f"Error: {response.status_code}, {response.text}")

except Exception as e:
    print(f"An error occurred: {e}")

Understanding the Screener Response

When you execute the request above, the API returns a JSON object containing metadata and a body with the list of stocks. Understanding the structure of the body is crucial for parsing the data into your trading algorithm or dashboard.

Here is a breakdown of the key fields returned for each stock object:

symbol – The ticker symbol (e.g., "AAPL", "AMD")
symbolName – The full name of the company
lastPrice – The most recent trading price of the stock
priceChange – The dollar amount change from the previous close
percentChange – The percentage move for the day (critical for gauging momentum)
volume – The total number of shares traded in the current session
symbolCode – Indicates the type of asset (e.g., "STK" for Stock)

The response allows you to immediately see why a stock was picked up by the screener—usually a combination of the percentChange and volume confirming the trend.

Advanced Screening Ideas

The Mboum Screener API is versatile. While the example above focuses on general high volume, you can adjust the filter parameter to suit specific trading strategies:

1. Penny Stock Gap-Ups

If you trade volatility in lower-priced assets, you can use the penny_gap filter. This targets stocks priced under $10 that have significant price gaps and high percentage changes over the last 5 days.

Parameter

filter="penny_gap"

2. Technical Breakouts (Golden Cross)

For traders looking for longer-term bullish reversals, you can filter for stocks where the 50-day moving average has just crossed above the 200-day moving average.

Parameter

filter="golden_cross"

3. Oversold Bounce Plays

Contrarian traders can look for high-volume liquid stocks that have been oversold. The rsi_oversold filter identifies stocks with a 20-Day RSI below 30, signaling a potential reversion to the mean.

Parameter

filter="rsi_oversold"

4. Tech Sector Momentum

If your strategy focuses purely on the technology sector, use the top_tech filter. This isolates computer and technology stocks that are hitting new 6-month highs, indicating strong sector rotation.

Parameter

filter="top_tech"

Final Thoughts

Building a market scanner from scratch requires ingesting massive amounts of data and calculating indicators on the fly. By using the Mboum Screener API, you bypass that infrastructure complexity. You can retrieve a pre-calculated list of high-potential stocks with a single API call, allowing you to focus your development time on trade execution logic rather than data aggregation.

Ready to start scanning?

Get your API Key here:
https://mboum.com/pages/api