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What is the Trading Analysis Dashboard?

The Trading Analysis Dashboard is a Flask-based web application designed to track and analyze stock trading performance. It provides real-time portfolio management, historical trade analysis, and comprehensive reporting to help understand trading patterns and portfolio performance.

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Core Components

Tracks current holdings including stocks, ETFs, and mutual funds with real-time price updates from Finnhub API. Displays allocation charts, performance metrics, and gain/loss analysis.Key capabilities:
  • Add/edit/delete holdings
  • Real-time price refresh
  • Allocation visualization
  • Performance tracking
Analyzes historical trading performance using a hybrid matching algorithm that combines broker-provided realized gains/losses with transaction history for broker-level accuracy.Key capabilities:
  • Monthly P&L breakdown
  • Trade-by-trade details
  • Win/loss ratios
  • Dividend tracking
Allows custom date range analysis to compare trading performance across different periods and identify trends.Key capabilities:
  • Custom date ranges
  • Period comparison
  • Trend identification
  • Performance reports
Visual calendar view showing daily trading activity with heat maps to quickly identify profitable and losing periods.Key capabilities:
  • Monthly calendar view
  • P&L heat mapping
  • Pattern recognition
  • Activity tracking
Supports bulk data import via CSV files for both portfolio holdings and transaction history with drag-and-drop interface.Key capabilities:
  • Drag-and-drop upload
  • Real-time processing feedback
  • Upload history tracking
  • Format validation

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Application Flow

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User Authentication

The application uses Google OAuth 2.0 for secure authentication. Users must be authorized (configured in environment variables) to access the system. Each user’s data is completely isolated.

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Data Structure

The application maintains three primary data entities:
EntityDescriptionKey Fields
UsersAuthentication and profileemail, brokerage_account, google_id
HoldingsCurrent portfolio positionssymbol, shares, cost_basis, current_price
TransactionsHistorical trading activitysymbol, action, shares, price, date

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Hybrid Matching Algorithm

The trading analysis uses a sophisticated matching system:
  1. Broker Realized Gains/Losses - Pre-calculated lot matches from broker statements provide definitive P/L for closed positions
  2. Transaction History - Complete buy/sell transaction records for verification and detail
  3. Hybrid Approach - Combines both sources to achieve broker-level accuracy while maintaining transaction-level detail
See Hybrid Matching for technical details.

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API Architecture

The application exposes a RESTful API with the following endpoint categories:

Trading Data

Access monthly trading data, individual trades, and P/L information

Portfolio

Manage holdings and trigger price refresh operations

Authentication

OAuth endpoints and session management

Timeframe Analysis

Query performance across custom date ranges

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Technology Stack

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Backend

  • Flask - Python web framework handling routing, templating, and business logic
  • SQLAlchemy - ORM for database operations
  • PostgreSQL - Relational database for data persistence
  • Flask-Dance - OAuth integration for Google authentication

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Frontend

  • Bootstrap 5 - Responsive UI framework
  • Chart.js - Interactive charts and visualizations
  • jQuery - DOM manipulation and AJAX requests
  • DataTables - Enhanced table functionality

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External Services

  • Finnhub API - Real-time stock price data
  • Google OAuth 2.0 - User authentication

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Data Models

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Portfolio Holdings

class Holding:
    id: int
    user_id: int
    symbol: str
    shares: float
    average_cost: float
    type: str  # stock, etf, mutual_fund
    current_price: float
    last_updated: datetime

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Trading Transactions

class Transaction:
    id: int
    user_id: int
    symbol: str
    action: str  # buy, sell
    shares: int
    price: float
    date: datetime
    account_number: str

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Realized Gains

class RealizedGain:
    id: int
    user_id: int
    symbol: str
    date_acquired: datetime
    date_sold: datetime
    proceeds: float
    cost_basis: float
    gain_loss: float

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Configuration

The application is configured via environment variables:
VariablePurpose
FINNHUB_API_KEYAPI key for price data
GOOGLE_CLIENT_IDOAuth client ID
GOOGLE_CLIENT_SECRETOAuth client secret
AUTHORIZED_USERSComma-separated email list
FLASK_SECRET_KEYSession encryption key
DATABASE_URLPostgreSQL connection string

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Features Deep Dive

Portfolio Management

Learn about tracking holdings and price updates

Trading Analysis

Understand P&L calculations and reporting

CSV Upload

Import data from your broker

Hybrid Matching

How the matching algorithm works