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 Maqsad funksiyasini loyihalash: siz optimallashtirgan metrika strategiyangizni yashirincha tanlaydi
- 02 Ko'p vaqt oralig'idagi bektestlarda kelajakka qarash yo'qligini isbotlash: kelajakni buzib, o'tmish uni ko'ra olmasligini isbotlash
- 03 Walk-Forward Optimization: The Only Honest Strategy Test
- 04 Plato tahlili: barqaror optimumni overfitting-dan qanday ajratish kerak
- + 5 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 Backtest tezligi zinapoyasi: laptop CPU'sida 298x, oxirgi bitimigacha bir xil PnL
- 02 Freymvork solig'i: qachonki backtest kutubxonangiz oddiy pandas siklidan sekinroq bo'ladi
- 03 Yig'ilgan Parquet Kesh: Ko'p Vaqt Oralig'idagi Backtestlarni Yuzlab Marta Tezlashtirish
- 04 Ikki oʻqli parametr fazosi: nega sweepingizning katta qismi deyarli bepul boʻlishi kerak
- + 6 more
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 Arbitrajni aniqlash uchun graf algoritmlari: Bellman-Forddan RICH gacha
- 02 Fyuchers-Spot Arbitraji: Cash-and-Carry-dan DeFi-CeFi-gacha
- 03 Matritsalar, tenzorlar va tropik algebra: arbitrajni aniqlash uchun chiziqli algebra
- 04 Arbitraj uchun Vine Copulas: yuqori o'lchamli bog'liqliklarni modellashtirish
- + 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 order book metodlari aslida qanday ishlaydi
- 02 Algoritmik Treydingda Order Turlari: Chasing bilan Limitdan Virtual Orderlargacha
- 03 Queue Inside the Wall: Analyzing Order Position in Order Book Density
- 04 Algoritmik treyding uchun bar turlari va agregatsiya usullari
- + 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 Kripto uchun Markowitz portfel nazariyasi: noldan qahramongacha
- 02 12 Portfolio Optimization Algorithms, Compared: HRP, Black-Litterman, NCO and Beyond
- 03 Inside Our House Algorithm: HRP + Long/Short + CVaR with Hull-White
- 04 Kripto portfellarida birgalikdagi xavfni modellashtirish uchun kopula modellari
- + 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 Juftlik savdosida masofa yondashuvi: Rust yordamida amalga oshirish va tahlil
- 02 Statistical Arbitrage and Pairs Trading in Crypto Markets: From Cointegration to the Kalman Filter
- 03 Statistik Arbitrajda O'rtaga Qaytish va Momentum Strategiyalarini Dinamik Birlashtirish: Matematik Asoslar va Amaliy Qo'llanma
Deep Learning for Markets
Neural forecasting for crypto — transformers, diffusion models, and foundation models, and how conformal prediction keeps their uncertainty honest.
- 01 Temporal Fusion Transformers for Multi-Horizon Portfolio Forecasting
- 02 Diffuzion Modellar va Kriptovalyuta Tartibsizligi: Nega DDPM Bitcoin Qulashini Munajjimdan Ko'ra Yaxshiroq Bashorat Qila Oladi
- 03 Kronos: sham (candlestick) grafiklarini transformer tilida gapirishga o'rgatuvchi asos model
- 04 Xavf-xatarni Hisobga Oluvchi Pozitsiya Hajmini Belgilash uchun Konformal Bashorat
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 Agentic AI yordamida investitsiya portfelini boshqarishdagi inqilob
- 02 TradingAgents: Multi-Agent AI Framework That Models a Hedge Fund
- 03 AI4Finance Foundation: Algo-treyding uchun FinGPT, FinRL va FinRobot ekotizimi
- 04 AI Hedge Fund: sun'iy intellekt tahlilchilari savdolar bo'yicha ovoz beradigan ko'p agentli fond
- + 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 for Algorithmic Trading: Architecture That Speaks the Language of Markets
- 02 QuestDB for Algorithmic Trading: SQL Extensions That Change the Game
- 03 QuestDB for Algorithmic Trading: From Order Books to Production Architecture
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 Algo Treyding Tizimlarida Ma'lumotlar Aloqasi: Texnologik Sharh
- 02 Aeron: HFT sohasining yarmini harakatga keltiruvchi xabar almashish tizimining ichki tuzilishi
- 03 ZigBolt: Why We Built Our Own Aeron in Zig and Hit 20 Nanoseconds Per Message
- 04 Developing a Simple C++ Scalper Using FAST/FIX: Step-by-Step Guide