TickDB API development tutorials, WebSocket integration and SDK examples
In the autumn of 2019, a quant team at a London prop shop reportedly extracted approximately £340,000 in riskless profit over a single trading week by systematically exploiting a recurring mispricing
--- "Quants lose money for two reasons," the senior portfolio manager told me during my first week at a systematic fund. "They either overfit their models or underestimate the market." Three years and
Every quant trader who has ever run a backtest that worked beautifully in simulation and catastrophically in production has asked the same question: What went wrong? The answer, in roughly 40% of case
Every quant developer hits the same wall eventually. You're running a strategy that monitors 50 symbols. Each one needs a WebSocket connection. You're making REST calls to fetch historical data for ba
--- The Problem: AI Assistants Cannot Read Your API Documentation You have spent hours writing a comprehensive API reference for TickDB. You have documented every endpoint, every parameter, every erro
The problem with most Python trading systems isn't the strategy. It's the architecture. I learned this the hard way at 3:47 AM on a Tuesday, staring at a frozen terminal while my mean-reversion strate
--- The strategy returned 34.7% annualized in backtest. The live account lost 2.1% over the same period. That gap is almost never about the alpha signal deteriorating. It is almost always about execut
A developer once spent three weeks building a high-frequency mean-reversion strategy on US equity tick data—only to discover, at 2 AM during a live deployment, that the data source did not support tic
--- The first time I watched a production trading system fail, it wasn't because of a bad algorithm. The backtest looked perfect. The code was clean. The signal was sound. What collapsed was the plumb
Two artificial intelligence companies. One listed on NASDAQ. One listed in Hong Kong. NVIDIA (NVDA) at $900+ per share, and SenseTime (0020.HK) trading at approximately HK$2.80 — numbers so different
In distributed systems, the choice between REST and WebSocket is rarely a matter of preference. It is a matter of architectural physics. Consider a quant researcher who wants to backtest a mean-revers
When a solo quant quant becomes a quant team, the first thing that breaks is never the strategy. It is the workflow. You have been running your mean-reversion strategy from a single laptop for eightee
--- The Order Book Tells You Who Is Winning Before the Price Moves In every market microstructure textbook, there is a moment of quiet revelation: the price you see is a lagging indicator. The order b
Raw market data is a mess. A CSV export from a brokerage's API will have split-adjusted close prices that don't match your reference terminal. A websocket stream will send timestamps in UTC while your
--- When the market opened on a Tuesday morning, the strategy executed 847 trades. None of them were lost to connectivity failures. This is not a story about extraordinary infrastructure budgets. It i
A large institution wants to buy 500,000 shares of a mid-cap stock. Placing the full order at once would move the market by 2–3%, alerting HFT firms and other participants within milliseconds. Instead
--- The $0.04 That Nearly Cost Me a Strategy The trade looked perfect on paper. My mean-reversion strategy had fired a buy signal for AAPL at $182.50. The backtest showed entry at $182.52 — a 2-cent s
--- When large language models first gained the ability to call functions, developers faced a new class of engineering problem: how do you give an AI the precise vocabulary it needs to interact with d
--- "The best quantitative hedge funds spend millions on data infrastructure. Here's how to build something genuinely useful for zero dollars." In 2019, the median cost of institutional market data fo
--- The Question Every Quant Must Answer A strategy that returned 18% last year looks impressive — until you realize the market benchmark returned 22%. The strategy underperformed by 400 basis points,