Add Asset Filtering, Normalized Log Returns (y), and Advanced Technical Analysis Indicators

This updated Python script now applies a refined filtering process to remove unstable or unwanted crypto assets before conducting any price analysis. It then calculates a normalized y value using the logarithmic percentage change of closing prices, allowing for a more nuanced representation of market movements. On top of that, it integrates advanced technical indicators—such as moving average crosses, RSI, KDJ, and MACD structures—using talib and polars for efficient, CPU-parallelized computations. The careful handling of numeric conversions, data cleansing, and error avoidance (like preventing division-by-zero) ensures that the resulting dataset is both high-quality and analysis-ready for deeper quantitative strategies.

https://github.com/PythonCryptoDev369/trade/blob/1c1ce9f058eb81e7cccb24b34873d7f3f9f96906/trade.py

BTC -> bc1qm9f4qt0fvmf08x9fq7kaw0jm9p470cvhvv9amj
ETH -> 0x168973848BC0f159f0cac1313564176002e4d93D
XRP -> rsCmjwyXKg4QjLFwKcNUnyc7nCr6m6ti22