Trading Cycle Overview
The easiest way to understand Cortiq is to think in terms of one session running one repeatable trading cycle.
That cycle is not just an AI prompt. It is a controlled operating loop built from:
- a session
- one or more playbooks
- one data package
- optional support layers such as preparation, instrument profile, and sentiment
- the live MT5 account state
- the current open trades and trade history
The Core Loop
Section titled “The Core Loop”At a customer level, the cycle works like this:
Session Context -> Market Data Gather -> Prompt Build -> AI Decision -> Trade Execution or Management -> Logging and Review
Each pass through that loop is one trading cycle.
Why The Session Sits In The Middle
Section titled “Why The Session Sits In The Middle”The session is the operating container for the cycle.
It decides:
- which MT5 account is used
- which symbol or symbol-selection method is active
- which AI provider and integration mode are used
- which playbooks must be evaluated
- which data package defines the market payload
- which support layers should be attached
- when the session is allowed to run
That is why the trading cycle is best explained from the session outward rather than from the AI inward.
How The Pieces Fit Together
Section titled “How The Pieces Fit Together”| Layer | Role In The Cycle | Typical Question It Answers |
|---|---|---|
| Session | Operating container | What is this workflow allowed to do? |
| Playbooks | Strategy rules | What setups are valid? |
| Data package | Live market payload | What information does the AI see every cycle? |
| Trade ideas | Specific theses | What special opportunities are being tracked right now? |
| Preparation package | Cached analysis | What slower-moving structure should already be known? |
| Instrument profile | Long-lived market behavior | How does this instrument typically behave? |
| Sentiment report | News and macro context | What external pressure or event risk matters right now? |
| Session trades and timeline | Execution record | What happened, and why? |
What Supporting Information Can Be Added
Section titled “What Supporting Information Can Be Added”Many users understand playbooks and data packages quickly, but the support layers are where Cortiq becomes more disciplined.
You can add:
- session instructions for desk-specific rules or cautions
- preparation outputs for higher-timeframe or pre-session analysis
- an instrument profile for persistent symbol behavior
- a sentiment report for macro and news context
- trade ideas for specific discretionary theses that should be watched separately from general playbooks
These layers help the AI work with more structure and less improvisation.
Where Customers Usually Need More Detail
Section titled “Where Customers Usually Need More Detail”The two areas that most strongly affect documentation quality inside a real Cortiq setup are:
- how the playbook sections are written
- how the data package is scoped, especially when screenshots are involved
Use these guides next:
Why This Matters For Real Use
Section titled “Why This Matters For Real Use”Without a structured cycle, AI trading usually breaks in one of two ways:
- the AI has too little structure and improvises too much
- the AI sees too much noise and loses decision quality
Cortiq’s trading-cycle model is designed to control both problems.
Best Reading Order
Section titled “Best Reading Order”- Session Architecture
- Supporting Context
- Playbook Design Guide
- Data Package Design Guide
- The entity pages in this section, starting with Sessions