Python Strategy Report: Keltner ADX Volatility Breakout Strategy

PYTHON Replication Script

import yfinance as yf
import pandas as pd
import vectorbt as vbt

# Set parameters
symbols = ['QQQ', 'AAPL', 'MSFT', 'NVDA']
start_date = '2023-08-29'
end_date = '2026-08-27'

# Download historical data
prices = yf.download(symbols, start=start_date, end=end_date)['Adj Close']

# Calculate indicators
ema20 = prices.ewm(span=20).mean()
upper_band = prices.rolling(window=20).mean() + (prices.rolling(window=20).std() * 1.5)
lower_band = prices.rolling(window=20).mean() - (prices.rolling(window=20).std() * 1.5)
adx = vbt.ADX.run(prices, window=14).adx

# Define entry and exit signals
long_entry = (prices > upper_band) & (adx > 25)
long_exit = prices < ema20

# Create portfolio
portfolio = vbt.Portfolio.from_signals(prices, long_entry, long_exit, init_cash=100000)

# Print portfolio stats
print(portfolio.stats())