Estimate a public companys intrinsic value through DCF, relative, and sum-of-the-parts valuation methods.

Research a US equity across fundamentals, valuation, technical context, peers, and current market data.

Create a multi-perspective technology-company earnings memo with evidence standards, valuation lenses, and anti-bias checks.

Analyze a ticker with AlphaGBMs five-pillar framework: fundamentals, technicals, sentiment, flows, and valuation.

Assess business quality, economic moats, management, competitive positioning, and durable value creation.

Research a companys valuation, growth, profitability, balance sheet, competitive moat, and management quality.

Python program that rates stocks out of 100 based on valuation, profitability, growth, and price performance metrics, relative to the company's sector.

A framework for financial systemic risk valuation and analysis.

Stocks and Assets Valuation via Discounted Cash Flow with Python

Real time scrapping of stock data in order to get the most recent available information. Cleaning, structuring and parsing of relevant data to provide an interactive and informative dashboard. Dashboard features include: Price history (chart) Basic information (name, sector, industry, market cap...) Insider and institutional ownership information Share return over the years (absolute growth and cagr) Business summary Earnings & growth analysis (revenue, gross profit. EBITDA, net income, free cash flow...) Profitability analysis (roa, roe, roic, gross profit margin, net income margin...) Financial health analysis (debt to equity, interest coverage, quick ratio, current ratio...) Valuation analysis (p/e, p/s, p/b, p/fcf, peg) + Discounted Cash Flow Model

Automatically performs the DCF calculation, sensitivity analysis and Piotroski f-score analysis for a given company. All financial data collected via the financialmodelingprep API.