Extracting Market Mood Index (MMI) from TickerTape

Introduction

Market sentiment plays a crucial role in trading and investing decisions. One of the popular indicators for market sentiment is the Market Mood Index (MMI), available on TickerTape. This index, which ranges from 0 to 100, provides insights into whether the market is experiencing Extreme Fear, Fear, Greed, or Extreme Greed.

For algo traders, having access to MMI data can be valuable for integrating sentiment analysis into automated trading strategies. In this article, we will demonstrate how to extract MMI data programmatically using Python and Selenium.

Courtesy : TickerTape.in

What does the Market Mood Index Score Indicate?

Courtesy : TicketTape.in

Why Extract Market Mood Index Programmatically?

TickerTape displays the Market Mood Index on its website, but it does not provide an easily accessible API. To integrate this data into algo trading dashboards, financial models, or market analysis tools, we need to scrape the data using automation.

With Selenium, we can extract this information dynamically, ensuring that our trading models stay updated with the latest market sentiment.

Prerequisites

To follow along, ensure you have the following installed:

• Python (3.x recommended)
• Selenium for web automation
• webdriver-manager to manage the Chrome WebDriver

pip install selenium webdriver-manager

Python Script to Scrape Market Mood Index

Below is a Python script that fetches the MMI Score from TickerTape:

# ---------------------------------------------------------------------------------------
#           Extract Market Mood Index from TickerTape.in website
#
# Usage: Educational Purposes & training use only. Not for commercial redistribution.
# FabTrader Algorithmic Trading - Tutorials
# ---------------------------------------------------------------------------------------

from selenium import webdriver
from selenium.webdriver.chrome.service import Service
from selenium.webdriver.chrome.options import Options
from webdriver_manager.chrome import ChromeDriverManager

# Setup Chrome Options
chrome_options = Options()
chrome_options.add_argument("--headless")  # Run in background

# Initialize WebDriver
service = Service(ChromeDriverManager().install())
driver = webdriver.Chrome(service=service, options=chrome_options)

# Open TickerTape MMI Page
url = "https://www.tickertape.in/market-mood-index"
driver.get(url)

# Wait for page to load
driver.implicitly_wait(5)

# Locate MMI Score Element (Inspect the page to get correct XPath or CSS Selector)
mmi_score_element = driver.find_element("xpath", "//span[contains(@class, 'jsx-3654585993 ')]")

# Extract Text
mmi_score = float(mmi_score_element.text)

# Extract Market Mood
if mmi_score >= 70:
    mmi_mood = "Extreme Greed"
elif mmi_score >= 50:
    mmi_mood = "Greed"
elif mmi_score >= 30:
    mmi_mood = "Fear"
else:
    mmi_mood = "Extreme Fear"
print("Market Mood Index by TickerTape")
print(f"MMI Score: {mmi_score} - Market Mood: {mmi_mood}")

# Close Browser
driver.quit()

How to Use This Data in Algo Trading?

Algo traders can integrate MMI data into their trading strategies in multiple ways:

• AI & Machine Learning Models: Use historical MMI data as a feature for training trading models.
• Filter Trades Based on Sentiment: Avoid aggressive trading during Extreme Greed or Extreme Fear.
• Mean Reversion Strategies: Trade reversals when MMI reaches extreme levels.
• Portfolio Hedging: Adjust hedging strategies based on market sentiment.

Final Thoughts

The Market Mood Index provides valuable insights into market sentiment. By automating the extraction of this data, algo traders and quantitative analysts can enhance their decision-making processes.

With Selenium, fetching live MMI data is now simple. Traders can integrate this script into their trading dashboards, algo trading bots, or market analysis tools to stay updated on real-time market sentiment.

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Disclaimer: The information provided in this article is for educational and informational purposes only and should not be construed as financial, investment, or legal advice. The content is based on publicly available information and personal opinions and may not be suitable for all investors. Investing involves risks, including the loss of principal. Always conduct your own research and consult a qualified financial advisor before making any investment decisions. The author and website assume no liability for any financial losses or decisions made based on the information presented.