Brazil Energy Intelligence

Executive dashboard for monitoring the market performance, risk and relative positioning of Brazilian energy and infrastructure companies listed on B3.

Business objective

The project demonstrates how financial time-series data can be transformed into decision-oriented indicators through a reproducible Business Intelligence workflow.

It focuses on:

• performance monitoring;
• benchmark comparison;
• risk assessment;
• comparative company analysis;
• automated executive insights.

Features

• Executive KPI cards
• Normalized performance against Ibovespa
• Composite company ranking
• Return, volatility, Sharpe ratio and drawdown
• 30-session momentum
• Correlation heatmap
• Risk-versus-drawdown map
• Automated business insights
• Real-data and demonstration modes

Companies

The initial universe includes Neoenergia, Eletrobras, ENGIE Brasil, CPFL Energia, Equatorial, Cemig, Copel, ISA Energia, Taesa and Petrobras, with Ibovespa as benchmark.

Technology

• Python
• pandas
• NumPy
• Plotly
• Streamlit
• yfinance

Run locally

git clone <YOUR-REPOSITORY-URL>
cd brazil-energy-intelligence

python3 -m venv .venv
source .venv/bin/activate

pip install -r requirements.txt
streamlit run app.py

On Windows:

.venv\Scripts\activate

Deploy on Streamlit Community Cloud

1. Push this folder to a public GitHub repository.
2. Open Streamlit Community Cloud.
3. Select the repository and branch.
4. Set the main file path to app.py.
5. Deploy.

Methodology

The dashboard calculates:

• cumulative return;
• annualized volatility based on 252 trading sessions;
• simplified Sharpe ratio;
• maximum drawdown;
• approximate 30-session momentum;
• a normalized composite score.

The composite score uses:

• 40% return;
• 25% volatility;
• 20% drawdown;
• 15% momentum.

Each component is converted to a percentile ranking before aggregation.

Data disclaimer

Market data is retrieved through yfinance, an open-source library that accesses Yahoo Finance public data. This application is an educational portfolio project and does not constitute investment advice.

Portfolio narrative

Developed an executive intelligence dashboard to monitor the performance of Brazilian energy and infrastructure companies. Built a reproducible Python pipeline, comparative KPIs, benchmark analysis, automated rankings and decision-oriented visualizations.