Execution Simulation Demo

IMPORTANT: Execution is modeled at daily close-to-close with simple costs, not an intraday microstructure model. All analysis uses daily OHLCV bars only.

This notebook demonstrates execution cost modeling and simulation capabilities for daily rebalancing.

Overview

We'll explore: 1. Execution cost models (slippage, market impact) - simplified for daily rebalancing 2. Daily execution simulation (not intraday TWAP/VWAP) 3. Transaction cost analysis 4. Regime-aware execution strategies

Note: Execution is modeled at daily frequency with simple transaction costs. True intraday microstructure modeling (order books, tick data) is not used in the current experiment.

# Import required libraries
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from datetime import date, timedelta
import warnings
warnings.filterwarnings('ignore')

# Import Cross-Asset Alpha Engine components
from cross_asset_alpha_engine.data import load_daily_bars
from cross_asset_alpha_engine.utils import setup_logger
from cross_asset_alpha_engine.config import (
    DEFAULT_PARTICIPATION_RATE, 
    DEFAULT_SLIPPAGE_COEFFICIENT,
    DEFAULT_COMMISSION_RATE
)

# Setup
logger = setup_logger("execution_demo", console_output=True)
print("✅ All imports successful!")
print(f"📊 Default execution parameters:")
print(f"   Participation rate: {DEFAULT_PARTICIPATION_RATE}")
print(f"   Slippage coefficient: {DEFAULT_SLIPPAGE_COEFFICIENT}")
print(f"   Commission rate: {DEFAULT_COMMISSION_RATE}")