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TradeAutopsy
IN PROGRESS 3
Strategy Analysis...
Generating
Trade Import...
Generating
READY FOR REVIEW 3
Behavioral Analysis15m
+162 -37
Time-Based Patterns45m
+37 -0
P&L Breakdown1h
+135 -21

Trade Analysis Results

Add comprehensive trade analysis with loss prevention insights, behavioral pattern detection, and time-based performance tracking.

analysis_report.py
+24 -6

Now let me update the evaluation module to save results and generate a detailed report:

behavioral_detection.py
+29

Let me create behavioral pattern detection with revenge trading and overtrading alerts:

Done, configurable analysis framework with performance metrics and alerts.

  • Analysis: Strategy breakdown, time-based patterns, behavioral detection
  • Metrics: Win rate, avg P&L, drawdown tracking, risk:reward ratios
  • Alerts: Critical loss patterns, revenge trading detection, time-based warnings
analysis.py
patterns.py
import
import pandas as pd
import numpy as np
from datetime import datetime
class TradeAnalyzer:
def __init__(self, trades):
self.trades = trades
self.df = pd.DataFrame(trades)
def analyze_patterns(self):
# Detect behavioral patterns
revenge_trades = self._detect_revenge()
time_losses = self._time_analysis()
return {patterns...}
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Upstox
Angel One
ICICI Direct
Kotak Securities
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Groww

Strategy Breakdown

Automatically classify trades: Breakout, Mean Reversion, Options Selling, etc. See which strategies make you money and which bleed your account.

Time-Based Analysis

Discover you're losing ₹18K/month after 2pm? Stop trading afternoons. Data-driven discipline that compounds into lakhs saved.

Behavioral Detection

Catch revenge trading, holding losers too long, and overtrading. These patterns cost traders lakhs but are invisible without data.

Peer Benchmarking

Compare your win rate, risk:reward, and drawdown to traders with similar capital. Know exactly where you stand.

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