Collections
Curated reading paths through the blog, ordered from basics to advanced.
Backtesting Without Fooling Yourself
A step-by-step path from what your backtest really optimizes to proving an edge survives overfitting, multiple testing, and live execution. Read top to bottom — each part builds on the last.
- 01 目标函数设计：你优化的那个指标，正悄悄替你选好了策略
- 02 Walk-Forward 优化：唯一诚实的策略测试方法
- 03 平台分析：如何区分稳健最优与过拟合
- 04 蒙特卡洛自助法：如何用10行代码获取回测的置信区间
- + 3 more
High-Performance Backtest Engines
How to build a backtest engine that runs hundreds of times faster without changing a single PnL number — data layout, caching, adaptive resolution, and architecture, from first speedups to production internals.
- 01 回测引擎速度阶梯：笔记本 CPU 上 298 倍提速，PnL 精确到最后一笔交易
- 02 聚合 Parquet 缓存：如何将多时间框架回测加速数百倍
- 03 自适应下钻：从分钟到原始交易的可变粒度回测
- 04 IPC 税：把回测引擎放到 socket 背后会损失 13%——而这几乎与 socket 无关
Complex Arbitrage in Rust
A six-part build-up of multi-leg crypto arbitrage — from negative-cycle detection to the linear algebra, copulas, and machine learning behind it, ending in low-latency Rust execution.
- 01 套利检测的图算法：从 Bellman-Ford 到 RICH
- 02 期货-现货套利：从期现套利到 DeFi-CeFi
- 03 矩阵、张量与热带代数：用于套利检测的线性代数
- 04 套利中的 Vine Copulas：高维依赖关系建模
- + 2 more
Order Book & Market Microstructure
How the order book really works — accessing the data, reading queue position, rebuilding bars from order flow, and modeling it with deep learning and Hawkes processes.
- 01 CCXT：WebSocket 订单簿方法实际工作原理
- 02 算法交易中的订单类型：从追价限价单到虚拟订单
- 03 墙内排队：订单簿密集区的挂单位置分析
- 04 算法交易的K线类型与聚合方法
- + 2 more
Portfolio Construction & Risk
From Markowitz to production HRP + CVaR: how to allocate across crypto assets, model tail dependence with copulas, and size positions without blowing up.
- 01 马科维茨投资组合理论之加密货币篇：从零到英雄
- 02 12种投资组合优化算法比较：HRP、Black-Litterman、NCO及其他
- 03 我们的内部算法揭秘：HRP + 多空 + 基于Hull-White的CVaR
- 04 Copula模型：加密投资组合联合风险建模
- + 1 more
Statistical Arbitrage & Pairs Trading
Trade the spread between correlated assets — from the distance approach to cointegration and Kalman filters, then dynamically combining mean reversion with momentum.
- 01 配对交易中的距离法：Rust实现与分析
- 02 加密货币市场的统计套利与配对交易：从协整到卡尔曼滤波
- 03 统计套利中均值回归与动量策略的动态结合：数学基础与实践实现
Deep Learning for Markets
Neural forecasting for crypto — transformers, diffusion models, and foundation models, and how conformal prediction keeps their uncertainty honest.
- 01 用于多时间跨度组合预测的时序融合 Transformer
- 02 扩散模型对抗加密货币无政府状态：为什么DDPM比你的占星师更能预测比特币崩盘
- 03 Kronos：让K线图说Transformer语言的基础模型
- 04 用于风险感知仓位管理的保形预测
AI Agents for Trading
The agentic-AI stack for markets — multi-agent frameworks, open-source hedge funds, and LLMs that mine alpha from earnings calls.
- 01 基于代理型AI的投资组合管理革命
- 02 TradingAgents：模拟对冲基金的多智能体AI交易框架
- 03 AI4Finance Foundation：FinGPT、FinRL和FinRobot量化交易生态系统
- 04 AI Hedge Fund：AI分析师投票决定交易的多智能体基金
- + 1 more
QuestDB for Algorithmic Trading
Stand up a time-series stack for trading on QuestDB — from architecture to the SQL that matters, to a production deployment.
- 01 QuestDB 算法交易实战：读懂市场语言的架构设计
- 02 QuestDB 算法交易实战：改变游戏规则的 SQL 扩展
- 03 QuestDB 算法交易实战：从订单簿到生产架构
Low-Latency Trading Infrastructure
The plumbing under an HFT stack — how components talk (WebSocket, FIX, gRPC, Aeron), messaging on Aeron and Zig, and a C++ FIX/FAST scalper.
- 01 算法交易系统中的数据通信：技术综述
- 02 Aeron：驱动半个HFT行业的消息传递系统揭秘
- 03 ZigBolt：为什么我们用 Zig 从零打造了自己的 Aeron，实现了每条消息 20 纳秒延迟
- 04 使用 FAST/FIX 开发简单 C++ 剥头皮交易机器人：分步指南