Trade Journal Analysis

Purpose

Users upload broker exports (交割单) and get an honest, data-grounded portrait of their own trading. Two layers are live:

• Profile, holding days, frequency, win rate, PnL ratio, cumulative PnL, max drawdown, top symbols, market/hourly distribution.
• Behavior diagnostics, 4 biases, each with severity (low/medium/high) and numeric evidence: disposition effect, overtrading, chasing momentum, anchoring.

Strategy extraction → backtest bridge lands in Phase 4c.

Supported formats (auto-detected):

• 同花顺 (Tonghuashun), A-share CSV, typically GBK-encoded
• 东方财富 (Eastmoney), A-share CSV, typically GBK-encoded
• 富途 (Futu), HK/US CSV, UTF-8
• Generic, any CSV with columns like datetime/symbol/side/qty/price

Usage

Call the analyze_trade_journal tool directly. Never run Python from bash.

analyze_trade_journal(file_path="uploads/xxx.csv")
analyze_trade_journal(file_path="uploads/xxx.csv", analysis_type="profile")
analyze_trade_journal(file_path="uploads/xxx.csv", filter_expr="2026-01 to 2026-03")
analyze_trade_journal(file_path="uploads/xxx.csv", filter_expr="symbol=600519.SH")
analyze_trade_journal(file_path="uploads/xxx.csv", filter_expr="market=china_a")

analysis_type:

• full (default), profile + behavior (strategy still placeholder)
• profile, profile metrics only (fastest)
• behavior, 4 behavior diagnostics only
• strategy, Phase 4c placeholder

filter_expr (optional):

• Date range: "YYYY-MM to YYYY-MM" or "YYYY-MM-DD to YYYY-MM-DD"
• Symbol: "symbol=600519.SH" (exact match on qualified symbol)
• Market: "market=china_a|us|hk|crypto"

Return shape (profile subset)