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https://github.com/newking9088/nasdaq100_hedge_fund_dashboard
LLMs empower hedge funds and investors to leverage NASDAQ-100 insights, making informed decisions with key financial metrics. An LLM-powered app allows uploading financial reports and images for analysis, offering instant insights and trend analysis in a dynamic market. 🚀📊
https://github.com/newking9088/nasdaq100_hedge_fund_dashboard
dashboard-application data-visualization langchain llm rag streamlit
Last synced: 12 days ago
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LLMs empower hedge funds and investors to leverage NASDAQ-100 insights, making informed decisions with key financial metrics. An LLM-powered app allows uploading financial reports and images for analysis, offering instant insights and trend analysis in a dynamic market. 🚀📊
- Host: GitHub
- URL: https://github.com/newking9088/nasdaq100_hedge_fund_dashboard
- Owner: newking9088
- Created: 2024-09-30T04:34:39.000Z (about 1 month ago)
- Default Branch: main
- Last Pushed: 2024-10-24T17:33:45.000Z (14 days ago)
- Last Synced: 2024-10-25T18:58:06.880Z (13 days ago)
- Topics: dashboard-application, data-visualization, langchain, llm, rag, streamlit
- Language: Jupyter Notebook
- Homepage:
- Size: 7.1 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# SmartFinance AI: Intelligent NASDAQ-100 Analytics Platform 🚀
## Quick Links
[View Live Dashboard](https://nasdaq100hedgefunddashboard-paudel.streamlit.app/)
[Blogpost](https://nycdatascience.com/blog/streamlit/optimizing-roi-for-nasdaq-100-companies/?preview_id=99356&preview_nonce=ec4f9efaf8&_thumbnail_id=99358&preview=true&aiEnableCheckShortcode=true)
## Table of Contents
- [Platform Overview](#platform-overview)
- [Key Features](#key-features)
- [Technical Architecture](#technical-architecture)
- [Financial Metrics Guide](#financial-metrics-guide)
- [Future Roadmap](#future-roadmap)
## Platform Overview
Our platform revolutionizes hedge fund operations by combining two powerful capabilities:
1. **NASDAQ-100 Financial Analysis**: Comprehensive analysis of top-performing NASDAQ-100 companies using crucial KPIs and financial metrics
2. **LLM-Powered Intelligence**: Advanced document analysis and financial modeling using state-of-the-art language models
### Value Proposition
- Process vast amounts of financial data efficiently
- Identify high-growth opportunities through KPI analysis
- Make data-driven investment decisions using AI-powered insights
- Track and compare performance trends across NASDAQ-100 companies
## Key Features
### 📊 Document Q&A with Langchain
Transform financial document analysis:
* **Multi-Document Processing**: Analyze multiple PDFs simultaneously
* **Intelligent Extraction**: Process various document types:
- Financial reports
- SEC filings (10-K, 10-Q)
- Market research
- Earnings calls transcripts
### 🤖 Multi-Model LLM Suite
| Model | Specialized Use Cases |
|-------|---------------------|
| GPT-4 | Financial modeling, Strategic analysis |
| Claude (O1) | Research, Compliance verification |
| DALL-E 3 | Data visualization |
| TTS-1-HD | Audio report generation |
### 📈 Financial Metrics Dashboard
#### Core Performance Indicators
- Asset turnover
- YoY revenue growth
- EPS trends
- P/E ratio
- D/E ratio
#### Risk Assessment Metrics
- Altman Z-Score
- Beneish M-Score
- Financial distress indicators
- Piotroski F-Score
#### Liquidity Analysis
- Cash ratio
- Current ratio
- Quick ratio
- Working capital metrics
## Technical Architecture
### Project Structure
```markdown
project_root/
├── .streamlit/
│ └── config.toml
├── app.py
├── data/
│ ├── cleaned_data.csv
│ └── nasdaq_100_metrics_ratios.csv
├── assets/
│ ├── company_assets.png
│ └── daq.png
└── requirements.txt
```
### Key Components
1. **Streamlit Frontend**: Interactive dashboard interface
2. **LLM Integration Layer**: Document processing and analysis
3. **Data Processing Pipeline**: NASDAQ-100 metrics calculation
4. **Visualization Engine**: Interactive charts and metrics display
## Financial Metrics Guide
### Core Metrics Formulas
#### Performance Metrics
```markdown
Asset Turnover = Revenue / Total Assets
YoY Growth = (Current Value - Previous Value) / Previous Value × 100
EPS = Net Income / Outstanding Shares
```
#### Risk Metrics
```markdown
Debt to Equity = Total Debt / Shareholders' Equity
Interest Coverage = EBIT / Interest Expenses
Cash Ratio = Cash / Current Liabilities
```
### Advanced Analysis Tools
#### 1. Valuation Metrics
- Enterprise Value ratios
- Joel Greenblatt's Magic Formula
- Shiller's E10 (CAPE ratio)
#### 2. Efficiency Metrics
- Inventory turnover
- Days inventory outstanding
- Asset utilization ratios
#### 3. Growth Indicators
- Revenue growth trends
- Earnings growth patterns
- Market share evolution
## Future Roadmap
### Near-Term Developments
1. **Enhanced LLM Integration**
- New model implementations
- Improved processing speed
- Custom model fine-tuning
2. **Advanced Analytics**
- Real-time market analysis
- Predictive modeling
- Risk assessment tools
3. **User Experience**
- Customizable dashboards
- Mobile optimization
- Enhanced visualization tools
### Long-Term Vision
- AI-driven portfolio optimization
- Automated risk management
- Real-time market sentiment analysis
- Advanced pattern recognition
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