Natural language market intelligence

Command the market

One line to analysis, simulation, stress tests & decisions.|

Output

Awaiting signal

Listening…

Market lens

Confidence

Data pulse

Result state

Awaiting signal

What is Talos?

Talos is a natural-language market intelligence terminal that brings professional-grade quantitative analysis to everyday investors. Rather than navigating a maze of disconnected tools and paying high fees for data, you type a single command and Talos runs the full analytical pipeline: it resolves tickers and intent, fetches live market data, computes technical indicators and risk metrics, and presents the results in a clean, focused terminal interface.

Whether you are evaluating a single stock, comparing multiple tickers, stress-testing a portfolio, or generating probabilistic price scenarios, Talos combines standard quantitative finance formulas with machine learning to surface the signals that matter most. All analysis is for informational and educational purposes only — not financial advice.

Core Capabilities

Technical Analysis

RSI, MACD, VWAP, Bollinger Bands, moving averages, and volatility metrics from historical price and volume data. Each indicator includes trend detection and signal classification.

Monte Carlo Simulation

Thousands of randomized price paths via geometric Brownian motion calibrated to historical volatility and drift. Includes 5th, 50th, and 95th percentile bands for probabilistic forecasts.

Risk & Drawdown

Sharpe ratio, Sortino ratio, maximum drawdown, beta, and stress testing. The Black Swan command overlays a COVID-style drawdown to model tail-risk and compute Value-at-Risk at 95% confidence.

Portfolio Optimization

Maximum Sharpe and minimum volatility allocations via covariance-matrix optimization. Black-Litterman adds investor views in a Bayesian framework. HRP uses correlation clustering for regime-robust diversification.

News Sentiment

NLP on recent financial headlines to score aggregate market sentiment. Article titles and scores are surfaced for transparency, helping you understand the narrative backdrop.

Macro & Valuation

GDP growth, CPI inflation, Federal Funds rate, unemployment, and Treasury yields provide economic context. ML-powered expected return predictions incorporate technical, fundamental, and macro features for forward-looking forecasts.

Methodology & Data Sources

All indicators are computed using standard quantitative finance formulas applied to historical price and volume data. Technical indicators use common default parameters (RSI 14 periods, MACD 12/26/9, Bollinger Bands with 20-period SMA and 2 standard deviations). Risk-adjusted return metrics use a 252-trading-day annualization convention with the 3-month Treasury bill as the risk-free rate.

Data is sourced from market data feeds including Alpha Vantage, SEC EDGAR filings, Federal Reserve Economic Data (FRED), and Bloomberg News. Machine learning models are trained on historical features using LightGBM and are evaluated for out-of-sample performance. All data is cached and refreshed on each request; past performance does not guarantee future results.