Building a Forex Portfolio Tracker with Historical Data API

A portfolio tracker helps you monitor your forex positions, calculate profits and losses, and analyze performance over time. In this tutorial, we'll build a simple tracker using the historical data API.

Core Features

• Track open positions with entry prices
• Calculate unrealized P&L in real-time
• Store trade history
• Display performance metrics

Data Structure

class Position:
    def __init__(self, symbol, direction, entry_price, size, entry_time):
        self.symbol = symbol
        self.direction = direction  # 'long' or 'short'
        self.entry_price = entry_price
        self.size = size
        self.entry_time = entry_time

    def calculate_pnl(self, current_price):
        if self.direction == 'long':
            return (current_price - self.entry_price) * self.size
        else:
            return (self.entry_price - current_price) * self.size

Fetching Current Prices

def update_portfolio_values(positions, api):
    total_pnl = 0
    for pos in positions:
        quote = api.get_quote(pos.symbol)
        current_price = quote['price']
        pnl = pos.calculate_pnl(current_price)
        total_pnl += pnl
        print(f"{pos.symbol}: {pnl:.2f}")
    return total_pnl

Performance Metrics

Track these key metrics:

• Total P&L: Sum of all position profits/losses
• Win Rate: Percentage of profitable trades
• Average Win/Loss: Mean profit vs mean loss
• Maximum Drawdown: Largest decline from peak

Storing Historical Data

Use a database (SQLite for simplicity, PostgreSQL for production) to store:

• Trade entries and exits
• Daily portfolio snapshots
• Performance history

This data enables long-term performance analysis and helps identify patterns in your trading.