https://blog.lynxflow.co/en/tags/vectorbt/Recent content in Vectorbt on Lynx Tech BlogHugo -- gohugo.ioenSun, 06 Sep 2026 10:00:00 +0800https://blog.lynxflow.co/en/posts/lynxcrypto-pandas-6step/Sun, 06 Sep 2026 10:00:00 +0800https://blog.lynxflow.co/en/posts/lynxcrypto-pandas-6step/You can&rsquo;t do crypto quant without pandas. Your market data is a table, your indicators are columns, and backtest engines eat DataFrames with a time index — vectorbt, Freqtrade, the strategy classes in your strategy/ directory all consume exactly this data structure. But most people learn pandas the wrong way: they chew through syntax books and memorize APIs, then still can&rsquo;t handle a single candlestick afterward. This post is the pandas crash course I put together for myself, and ithttps://blog.lynxflow.co/en/posts/lynxcrypto-tools-roadmap/Sun, 06 Sep 2026 05:41:00 +0800https://blog.lynxflow.co/en/posts/lynxcrypto-tools-roadmap/<img src="https://blog.lynxflow.co/images/lynxcrypto-tools-roadmap-v2.png" alt="Featured image of post LynxCrypto Tools Edition: From Setting Up the Environment to Professional-Grade Quant Researcher — My Roadmap and Every Tutorial" /> Three most valuable conclusions up front: Nobody at a top quant firm uses TradingView for strategy research. Jane Street writes OCaml firm-wide; Two Sigma/Citadel use Python+Java+Spark; HFT is Python research + C++ execution. TradingView is only the &ldquo;eyes&rdquo; (charts + watchlist + alerts), not the &ldquo;brain.&rdquo; The right division of labor for a solo researcher: Jupyter+vectorbt as the brain (strategy discovery), a self-written engine or Freqtrade as the hands (trustworthy backte