Ultime notizie sul trading algoritmico, avanzamenti nella tecnologia di backtesting, ricerca quantitativa e sviluppi fintech.
Arrow 18 introduces SIMD-accelerated aggregation kernels and improved Parquet read performance, directly benefiting quantitative analysis pipelines.
Retail algorithmic trading volume grew 40% year-over-year, driven by accessible platforms that lower the barrier from 'write code' to 'describe strategy'.
A worked example of sequential train/test windows, data leakage and realistic cost assumptions in walk-forward validation.
Python 3.14's experimental JIT compiler shows promising results for numerical workloads, potentially reducing the performance gap for Python-based backtesting engines.
Use Community AI Studio with direct BYOK or a supported local model, then validate and backtest locally.
