Porfolio-manager

AI to check portfolios

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Inspiration

Manually managing investments can be time-consuming and dangerous. Using free tools, I want to develop an intelligent, AI-powered application that mimics actual financial decision-making through risk analysis, portfolio balance, and real-time news.

What it does

This project mimics an AI-based financial portfolio manager that: - Retrieves current financial news - Uses natural language processing (NLP) to assess news content for sentiment and risk (TextBlob) It logs simulated trading actions, rebalances a simulated stock portfolio according to risk scores, and shows trade, risk, and portfolio data in real time. Dashboard powered by Firebase

How we built it

Real-time database management using Firebase Firestore For backend agents, Python: A script called news_monitor.py retrieves financial news.

  • risk_analysis.py - uses sentiment to assign risk ratings Asset weights are rebalanced via rebalancer.py. The trade_executor.py script mimics purchasing and selling.
    • HTML, CSS, and JS for a live dashboard with Firebase hosting
    • NewsAPI to retrieve items about financial news TextBlob for sentiment analysis (offline natural language processing) ## Challenges we ran into Managing erroneous or unnecessary news material; securely connecting Python agents with Firebase; and simulating portfolio logic to represent realistic rebalancing
    • Using Firebase Hosting to deploy a live data dashboard Uploading Firebase keys by mistake has been fixed with .gitignore and key safety best practices.

Accomplishments that we're proud of

created from the ground up a completely functional AI-powered financial portfolio simulator. A smooth pipeline was created by integrating several technologies, including Python, Firebase, and APIs. NLP sentiment analysis  was used to evaluate risk and impact portfolio choices. A Firebase-hosted live-updating web dashboard was created. Used GitHub Actions to automate the entire agent pipeline. I didn't use any paid cloud services; I solely used free and open-source tools.

What we learned

How to utilise Firebase Firestore as a real-time database in the cloud. Using TextBlob to perform basic NLP sentiment analysis and learning how to evaluate financial news. Scheduling and integrating cloud services with Python scripts. Using Firebase Hosting to deploy a static frontend.

What's next for Porfolio-manager

Use Chart.js or D3.js to add interactive graphs and charts. To forecast asset movement based on news, apply machine learning algorithms. Present actual asset prices via CoinGecko or Yahoo Finance APIs. To limit access to private dashboards, use Firebase authentication. Include email warnings for high-risk or trade action scenarios. Add commodities and cryptocurrency to the portfolio.

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