Quantitative Finance Dashboard Project

This is a dashboard that I have built to work on my (vibe) coding skills and general finance knowledge before I begin my trading role next summer. Let me know if you have any tips, features, or general suggestions for how I can utilize this. /https://finance-terminal.fly.dev/.

287 WSO Academy Sales & Trading Session Reviews: 4.86/5

Class of '26 Apr 2025 Cohort

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Sales & Trading Mock Interview

“Aman is very knowledgeable in his domain specific knowledge. But what was striking was his ability to explain in very simple layman terms. He is so open and forthcoming in sharing his knowledge to somebody like me who is new and not exposed to such an industry. He gave actionable takeways and wise advice that I will follow through on. After talking with him, my mind has become more clear that I want to take up trading, and not quantitative researchers or sales roles. He is positive regarding my situation and I look forward to working with him in the near future.”

Class of '27 Jun 2025 Cohort

4.92/5

Sales & Trading Mock Interview

“Quentin was really helpful and was so willing to help. He was able to accommodate my time very easily. He asked me lots of questions and even mentioned sending me more problem solving activities to help me ahead of my interview. I would be very willing to working with him again as he gave me good advice.”

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Based on the most helpful WSO content, here are some tips and suggestions to enhance your Quantitative Finance Dashboard project:

1. Expand Data Manipulation and Analysis

Python Libraries: Incorporate Pandas for advanced data manipulation and NumPy for numerical computations. These are essential for handling financial datasets effectively.
Visualization: Use Seaborn or Matplotlib for creating insightful visualizations. If you want to go further, explore Plotly for interactive dashboards.
Portfolio Analysis: Integrate Pyfolio for portfolio risk management and performance analysis.

2. Data Sourcing

Learn to write connection strings and use tools like MySQL, pyodbc, or cx_Oracle to pull data from databases.
Consider adding APIs for market data (e.g., Alpha Vantage, Yahoo Finance, or Quandl) to fetch real-time or historical financial data.

3. Automation Features

Add functionality to email reports or updates using win32com. This could include daily P&L summaries or risk metrics.
Automate repetitive tasks with for/while loops or macros if you integrate Excel.

4. Advanced Features

Backtesting: Build a simple backtesting module to test trading strategies. This will help you understand the mechanics of trading and improve your coding skills.
Risk Metrics: Include calculations for VaR (Value at Risk), Sharpe Ratio, and other key financial metrics.
Machine Learning: If you’re feeling ambitious, explore basic machine learning models for predictive analytics (e.g., predicting stock prices or volatility).

5. User Interface

Enhance the UI with Tableau or Power BI for better visualization and interactivity.
If sticking to Python, consider using Dash or Streamlit to make your dashboard more user-friendly.

6. Coding Environment

Work in a Linux environment (e.g., Ubuntu) for better performance and debugging capabilities. You can set this up via dual boot or a virtual machine.
Learn to use the command line for efficiency—it only takes about 30 minutes to get started.

7. Documentation and Sharing

Document your code thoroughly to make it easier for others (and your future self) to understand.
Share your project on platforms like GitHub to get feedback and showcase your skills to potential employers.

8. Focus on Relevance

Tailor your project to align with your trading role. For example, if you’ll be working with derivatives, include modules for options pricing or Greeks calculations.
Avoid spending time on features that don’t directly enhance your understanding of trading or finance.

By implementing these suggestions, you can make your dashboard a powerful tool for both learning and practical application in your upcoming trading role.

Sources: 0 to pseudo quant real quick - analytical skills for juniors with finance background, Programming/Technical Skills for Finance: SQL and Python, Programming/Technical Skills for Finance: SQL and Python, https://www.wallstreetoasis.com/forum/trading/move-to-tech-in-search-of-better-wlb?customgpt=1

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