Execution And Hedge Analytics

A post-trade analytics project for reviewing execution cost, urgency, hedge effectiveness, and residual risk.

Designed to complement a trader-front-end demo by showing what happens after the trade is sent.

execution analytics hedge review slippage analysis synthetic trade data post-trade workflow

Preview

Overview

This project focuses on the post-trade side of the workflow: execution cost, hedge behavior, venue quality, and residual risk after an order is sent.

Highlights

• implementation shortfall and slippage review
• urgency bucket analysis
• venue quality comparison
• hedge basket effectiveness
• residual beta and time-to-flat analysis
• an order replay panel for reviewing one synthetic order in detail

Quick Start

python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
python -m src.generate_data
python -m src.analysis
streamlit run app.py

Outputs

After running the scripts, you should see:

• data/synthetic_execution_data.csv
• results/top_line_metrics.csv
• results/urgency_summary.csv
• results/hedge_summary.csv
• results/venue_summary.csv
• results/worst_orders.csv
• results/key_findings.md
• figures/slippage_by_urgency.png
• figures/hedge_effectiveness_scatter.png
• figures/daily_execution_trends.png

Project Structure

execution-and-hedge-analytics/
├── app.py
├── README.md
├── requirements.txt
├── data/
├── figures/
├── results/
└── src/
    ├── __init__.py
    ├── analytics.py
    ├── analysis.py
    ├── generate_data.py
    └── ui.py

Why It Fits The Portfolio

This repo extends the trading workflow beyond the front end:

• not just monitoring a live book
• but also measuring how expensive execution was
• how quickly hedges worked
• and where the desk should investigate poor outcomes

Notes

• All trades, symbols, hedge baskets, and metrics in this repo are synthetic.
• The repo focuses on analytics, review workflows, and execution-quality storytelling.