Transaction Cost Analysis

Transaction Cost Analysis

> Transaction cost analysis (TCA) — slippage, market impact, benchmarks for measuring execution quality.

When to Activate

• User needs to measure and decompose execution costs
• Evaluating broker or algorithm performance
• Building market impact models (Almgren-Chriss, square-root model)
• Comparing execution against benchmarks (VWAP, arrival price, close)
• Conducting pre-trade cost estimation for portfolio rebalancing

Core Concepts

What TCA Measures

TCA quantifies the total cost of transforming an investment decision into executed trades. This includes everything from the moment a portfolio manager decides to trade until the last share is filled.

Cost Taxonomy

Explicit Costs (directly observable):

• Commissions: $0.001-0.005/share for institutional equity (declining toward zero)
• Exchange fees: $0.0003-0.003/share (varies by venue, maker/taker)
• Stamp duty / FTT: 0.5% UK, 0.1% HK, varies by jurisdiction
• Clearing fees: negligible for equities, meaningful for derivatives

Implicit Costs (estimated from market data):

• Bid-ask spread cost: half-spread on average for market orders
• Market impact: permanent price movement caused by the trade
• Timing cost: price drift between decision and execution
• Opportunity cost: cost of not executing (unexecuted portion)

Implementation Shortfall Decomposition

Perold (1988) defined implementation shortfall as the difference between paper portfolio return and actual portfolio return:

IS = Paper Return - Actual Return

Decomposed into:
IS = Delay Cost + Market Impact + Spread Cost + Opportunity Cost + Commissions

Where:
- Delay Cost = price move from decision to order release
- Market Impact = price move from order release to execution (attributable to our trading)
- Spread Cost = half the bid-ask spread at execution
- Opportunity Cost = return on unexecuted shares (for partial fills)
- Commissions = explicit fees

Methodology

Step 1: Single-Order TCA

import pandas as pd
import numpy as np

def implementation_shortfall(decision_price, arrival_price, exec_price,
                              close_price, exec_qty, order_qty,
                              side, commission_per_share=0.003):
    """
    Full IS decomposition for a single order.

    decision_price: price when PM made the decision
    arrival_price: price when order reached the trading desk
    exec_price: volume-weighted average execution price
    close_price: closing price on the day
    """
    direction = 1 if side == 'BUY' else -1
    fill_rate = exec_qty / order_qty

    # Component costs (in bps of notional)
    delay_cost = direction * (arrival_price - decision_price) / decision_price * 10000
    market_impact = direction * (exec_price - arrival_price) / arrival_price * 10000
    spread_cost = abs(exec_price - arrival_price) / arrival_price * 10000  # approximate
    commissions = commission_per_share / exec_price * 10000

    # Opportunity cost: return on unfilled shares
    if fill_rate 30 orders per group)
- [ ] Outlier orders investigated individually (extreme slippage may indicate information leakage)
- [ ] Portfolio-level TCA links costs to alpha — are we paying more to trade than we earn?

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [brainbytes-dev](https://github.com/brainbytes-dev)
- **Source:** [brainbytes-dev/everything-claude-trading](https://github.com/brainbytes-dev/everything-claude-trading)
- **License:** MIT

Install and usage instructions live in the source repository linked above.