Case Study: News Impact on Markets after Trumps Precedency

Code file: https://colab.research.google.com/drive/1LpXfMNXcyFuvsatmmBxafyMxJUc5XC3K?usp=sharing

Basic Idea

For this analysis, I used the DXY (US Dollar Index) data spanning from January 20th (when Donald Trump began his presidency) to May 27th.

I focused on daily and session volatility, calculated using the formula:

Volatility =( (High - Low) / Low )× 100

I verified the result by comparing it with TradingView’s daily range, and they matched. After calculating the volatility for each day, I assigned a news impact category to each day.

News Classification

Each trading day was categorized based on its news impact:

• Red Folder – High Impact News
• Orange Folder – Medium Impact News
• Big 3 (Green) – Major News Events (NFP, FOMC, CPI)
• Grey (No News) – Days without scheduled news

Chart 1: Daily Volatility vs News Impact

This chart plots the daily volatility over time, with each day color-coded according to its news classification. It also includes:

• The overall average volatility (horizontal reference line)
• Weekly average volatility, helping us observe patterns across weekdays

https://colab.research.google.com/drive/1LpXfMNXcyFuvsatmmBxafyMxJUc5XC3K#scrollTo=kO0yNITf3JmM&line=1&uniqifier=1