Portfolio Chimera

Inspired by the creation of a new entity from disparate parts in 'Frankenstein', the misdirection and secret methodology of 'The Prestige', and the data aggregation power of a 'Web Analytics' scraper, Portfolio Chimera is a niche FinTech solution for sophisticated retail investors.

The Concept (The Frankenstein Method):
Traditional stock analysis relies on siloed data: financial statements, market charts, or news sentiment. Portfolio Chimera operates on the premise that a truer picture emerges when you stitch together all the scattered, publicly available 'body parts' of a company's digital footprint into a single, coherent entity—a 'Chimera'. The platform continuously scrapes and aggregates a wide array of data sources, including:
- Formal Data: SEC filings (10-Ks, 10-Qs), insider trading reports.
- Media Data: Financial news articles, press releases, C-suite interviews.
- Social Data: Sentiment and volume from platforms like Twitter, Reddit (e.g., WallStreetBets), and StockTwits.
- Operational Data: Job postings (e.g., a sudden increase in R&D roles), patent filings, changes to executive LinkedIn profiles.

This aggregated data forms the 'Chimera'—a multi-faceted, living profile of the asset that is far richer than any single data source.

How It Works (The Prestige Framework):
The user experience is designed like a three-act magic trick:

1. The Pledge: The investor presents an ordinary object—a stock ticker they are interested in (e.g., TSLA, AAPL).

2. The Turn: This is the secret. Our system takes the 'Chimera' of data and applies a proprietary algorithm. It doesn't just measure positive or negative sentiment; it actively searches for dissonance and contradictions between the different data sets. For example, it might flag a high-priority alert if a CEO is promoting the stock heavily in interviews ('Media Data') while insiders are quietly selling off large quantities of shares ('Formal Data'). Or it might spot a quiet surge in engineering job posts for a new product line ('Operational Data') long before it's mentioned in an earnings call.

3. The Prestige: The platform produces the extraordinary result. Instead of a simple 'buy/sell' recommendation, it generates a 'Dissonance Score' and a visual dashboard that reveals the hidden narrative. It presents the conflicting evidence side-by-side, empowering the investor with a unique insight that others miss. It reveals the 'trick' behind the market's perception, allowing the user to make a decision based on a deeper, more fundamental truth.

Implementation & Monetization:
- Low-Cost: The core of the project is a web scraping engine built with Python (Scrapy, BeautifulSoup) and a data analysis backend, which can be developed by a single person and run cheaply on cloud servers. It intentionally avoids expensive, proprietary data feeds.
- Niche: It targets prosumer retail investors who want an analytical edge, not a get-rich-quick scheme.
- High Earning Potential: A tiered SaaS subscription model. A free tier allows analysis of a few stocks with limited data sources, while a premium tier (~$30/month) unlocks unlimited analyses, real-time dissonance alerts, and access to all scraped data sets.