Explore common Python backtesting pain points, including data quality issues, execution assumptions, and evaluation challenges that can impact the accuracy and reliability of trading strategy results.

Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...

Every investor has a moment when a brilliant idea pops into their head and they’re suddenly convinced they’ve cracked the market’s secret code. But ideas are cheap, and markets are not, so the real ...

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Abstract: I welcome you to the fourth issue of the IEEE Communications Surveys and Tutorials in 2021. This issue includes 23 papers covering different aspects of communication networks. In particular, ...

Functions are the building blocks of Python programming. They let you organize your code, reduce repetition, and make your programs more readable and reusable. Whether you’re writing small scripts or ...

Any trader can build a strategy. The real challenge is proving that it works, not just once, but across different market environments, volatility conditions, and timeframes. That’s where backtesting ...

When backtesting a portfolio strategy, you have to decide how far back to look. Should you use all available data, stretching back decades? Or should you just look at the last few years? There are ...

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