<aside> <img src="/icons/activity_pink.svg" alt="/icons/activity_pink.svg" width="40px" />

Trading Bot + Workflow

</aside>

You can import this markdown edition into Claude Projects to provide it with custom instructions; however, its contents are succinctly organized below for direct Notion AI execution.

Trading Journal - Text Context #3 - Technical Requirements.md

1. Database Relations Structure

A. Core Databases

1. Trades Database (Primary)

   • Relations:

     • Strategy Database (many-to-one)
     • Market Analysis (many-to-one)
     • Trade Journal (one-to-one)
     • Performance Metrics (one-to-many)

   • Key Properties:

     • Unique trade ID
     • Entry/exit points
     • Position size
     • Trade type
     • Asset class

2. Strategy Database

   • Relations:

     • Trade Database (one-to-many)
     • Performance Metrics (one-to-many)
     • Resource Library (many-to-many)

   • Key Properties:

     • Strategy ID
     • Risk parameters
     • Success metrics
     • Backtesting results

3. Performance Metrics Database

   • Relations:

     • Trades Database (many-to-one)
     • Strategy Database (many-to-one)
     • Journal Database (one-to-many)

   • Key Properties:

     • Time period
     • Performance indicators
     • Risk metrics
     • Profit/loss data

4. Resource Library Database

   • Relations:

     • Strategy Database (many-to-many)
     • Knowledge Base (one-to-many)
     • Community Content (one-to-many)

   • Key Properties:

     • Resource type
     • Content category
     • Affiliate links
     • Usage metrics

2. Formula Requirements

A. Performance Calculations

1. Trade Metrics

   Profit/Loss = (Exit Price - Entry Price) × Position Size × Contract Multiplier
   
   R-Multiple = Realized Profit/Loss ÷ Initial Risk
   
   Win Rate = Count(Winning Trades) ÷ Count(Total Trades)
   

2. Risk Metrics

   Position Size = Account Value × Risk Percentage ÷ Stop Distance
   
   Maximum Drawdown = (Peak Value - Trough Value) ÷ Peak Value
   
   Risk/Reward Ratio = Potential Profit ÷ Initial Risk
   

3. Portfolio Metrics

   Portfolio Return = Sum(Trade P/L) ÷ Starting Balance
   
   Sharpe Ratio = (Portfolio Return - Risk Free Rate) ÷ Portfolio Standard Deviation
   
   Expectancy = (Win Rate × Average Win) - (Loss Rate × Average Loss)
   

B. Custom Formulas

1. Options-Specific
2. Risk Management

3. Integration Capabilities