Algorithmic Trading with Python and Google Colab (1)

Can Markets Be Predicted? — Session 1 🔧 Put the random-walk benchmark to the test — autocorrelation diagnostics, Ljung–Box tests, and a linear OLS signal model with vectorized backtesting, all in Google Colab. 📂 GitHub repo: https://github.com/yhilpisch/algocolab 🎁 Use our community discount code SPECIAL5 when enrolling in any of our programs (5% off). In this first session of our free 3-part webinar series "Algorithmic Trading with Python and Google Colab", Dr. Yves J. Hilpisch asks whether daily EUR/USD returns carry statistically detectable structure — and whether any of it survives transaction costs. 📐 Topics in this session: • Research environment: frozen EUR/USD snapshot with 2,513 daily observations • Scoped null: weak-form EMH and the random-walk benchmark • Null-model laboratory: seeded independent and AR(1) controls matched on mean and volatility • Test suite: moments, sample ACF with Bartlett bands, Ljung–Box Q(h) with p-values • Granger-style nested regressions and incremental effect size • Lagged-return OLS signal model with 0.5 bp one-way FX costs • Train/validation/test backtesting and why signal decay occurs out of sample • Why the fixed 60/20/20 chronology is a classroom scaffold, not a deployment recipe 🔗 Resources: 📑 Slides: https://tpq.io/tpq_colab_trading_1.pdf 📂 Code & notebooks: https://github.com/yhilpisch/algocolab 📊 TDS: https://thedatascientist.dev 📈 CPF: https://python-for-finance.com 🤖 TAE: https://theaiengineer.dev ₿ TCE: https://thecryptoengineer.dev 📌 Disclaimer: This content is provided solely for illustration and educational purposes. It does not constitute financial, investment, legal, or professional advice, nor an offer or solicitation to buy or sell any security, financial instrument, or trading strategy. Past performance, whether simulated, backtested, or real, is no guarantee of future results. Algorithmic trading involves substantial risk, including the possible loss of principal capital. No warranties or guarantees of any kind are given. Use at your own risk. #AlgorithmicTrading #Python #QuantFinance #Finance #EMH #RandomWalk #TimeSeries #Statistics #GoogleColab #Backtesting #EURUSD #OLS #LjungBox #Trading #ThePythonQuants