How It Works

THE MODELS, ALGORITHMS & TRICKS BEHIND AEQUITAS, IN PLAIN ENGLISH

Every number on this site comes from a real algorithm, not a hardcoded placeholder. Here's what's actually running under the hood - tap a card to open it up.

A price, on its way to becoming a decision

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Market Data

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Signals & Risk

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ML Models

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AI Agents

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Your Thesis

RSI is a speedometer for buying pressure - it says whether a stock has been bought up too fast ("overbought") or beaten down too hard ("oversold"). MACD checks whether the fast-moving average and the slow-moving average agree on direction. Bollinger Bands watch whether the price has stretched outside its normal comfort zone. Combine all three into one score from -1 (bearish) to +1 (bullish) and you get a quick read on the crowd's mood.

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Quick Glossary

RSI

Relative Strength Index - momentum speedometer, 0-100.

MACD

Moving Average Convergence/Divergence - trend-following momentum.

VaR

Value at Risk - your likely worst-case loss on a normal bad day.

Sharpe ratio

Return per unit of bumpiness - higher is smoother sailing.

SHAP

Explains which input features drove a model's prediction, and by how much.

HMM

Hidden Markov Model - infers an unseen state from observable clues.

GIL

Python's Global Interpreter Lock - normally lets only one thread run Python at a time; C++ code can release it.

TWAP / VWAP

Ways to split a big order into smaller pieces over time so you don't move the price against yourself.