Portfosis is a free web platform that gives retail investors and small portfolio managers institutional‑grade analytics for their holdings. It runs up to 50,000 Monte Carlo simulations, stress‑tests portfolios, provides AI‑driven risk decomposition, rebalancing suggestions and a chat‑based advisor, and includes tools like backtesting, macro scenario analysis, real‑time news and a stock screener.
Funding
Funding not disclosed
Founders
Product
Problem
Individual investors and small portfolio managers often lack access to advanced analytics tools such as Monte Carlo simulations, stress testing, and AI-driven insights, which are typically expensive or require specialized software. This limits their ability to assess risk, evaluate strategies, and stay informed about market developments.
Solution
Portfosis offers a web‑based platform that provides institutional‑grade portfolio analytics at no cost. Users can upload their holdings via Excel or manual entry, after which the system runs up to 50,000 Monte Carlo simulations, performs risk decomposition, and evaluates drawdowns and sector exposures. An integrated AI advisor, powered by Claude, answers questions, suggests hedges, and generates actionable recommendations. The platform also includes stress‑testing against six historical crisis scenarios, AI‑driven rebalancing suggestions with drift tracking, and what‑if analysis for macro events. Additional tools such as backtesting, a live news digest, macro intelligence briefings, and a fundamental/technical stock screener help users monitor and refine their portfolios in real time.
Target Audience
Portfosis is aimed at retail investors, independent traders, and small‑to‑mid‑size portfolio managers who need sophisticated analytics without incurring high software costs.
Features
- 50,000‑run Monte Carlo simulations to model portfolio outcomes and tail risk
- AI Portfolio Advisor chat interface for hedging ideas and actionable insights
- Risk decomposition with attribution, correlation clustering, drawdown analysis, and sector exposure
- Stress testing against six historical crisis scenarios
- AI‑powered rebalancing recommendations with drift tracking
- What‑if scenario analysis for macro shocks (e.g., “Fed raises rates 1%”)
- Backtesting of strategies using historical market data
- Real‑time news digest filtered to the user’s specific holdings
- Macro intelligence briefings on rates, inflation, and geopolitics generated by AI
- Stock screener supporting fundamental and technical metric filters