The Wall Street Algo™

A Cycle-Aware, Agentic Market Framework

What is the Wall Street Algo?

The Wall Street Algo is a systematic investment framework that combines computer-predicted support and resistance levels, rule-based buy and sell signals, and long-term market cycles to guide probabilistic trading decisions.

Developed by John Botti, author of The Agentic Investor: New Ways to Invest in the Age of Agentic AI, MIT EECS graduate & former researcher, and Fintech Application Designer and Programmer.

The Wall Street Algo whitepaper is available here: https://thewallstreetalgo.com/the-wall-street-algo-whitepaper/

The Four Layers

1. Structural Price Engine

Dynamic support and resistance levels defining probabilistic boundaries.

2. Signal Engine

Rule-based buy and sell signals triggered near key price levels.

3. Cycle Intelligence

11-year, weekly, and annual market cycles that constrain risk.

4. Context & Event Layer

News, earnings, macro events, and alternative data affecting volatility.

The Agentic Decision Loop

  1. Observe
  2. Orient
  3. Constrain
  4. Act
  5. Evaluate
  6. Adapt

Human and Autonomous Execution

The Wall Street Algo is designed to be executed by both human traders and autonomous software agents.

Platforms like Algoz.ai implement the Wall Street Algo and deliver signals across these interfaces.

What the Wall Street Algo Is (and Is Not)

The Wall Street Algo is a decision framework, not a prediction engine. It does not claim certainty or guarantee outcomes. Instead, it organizes multiple sources of market information into a structured, probabilistic process for making trading decisions.

The framework is designed to be executed by human traders or autonomous agents and is implementation-agnostic. The complete technical definition is provided in the official whitepaper.

Resources