TickDB API development tutorials, WebSocket integration and SDK examples
In the summer of 2019, a quantitative researcher at a mid-size hedge fund spent three months building a strategy in Python. The backtests looked exceptional — Sharpe of 2.3, max drawdown under 8%. The
The order book is a window into supply and demand. Every bid, every ask, every withdrawal of liquidity tells a story that price alone cannot. At 9:30:02 AM on a volatile trading day, the bid side of a
"Unlimited subscriptions." Every vendor says it. None of them mean it. When TickDB's documentation states that WebSocket connections support "unlimited" symbol subscriptions, the fine print reads like
--- The Moment Everything Changed It started with a spreadsheet. A former colleague — a senior software engineer with 8 years of experience building distributed systems — decided to automate his stock
The CFO finishes reading the prepared remarks. The call moderator opens the line to analysts. For the next 45 minutes, no script exists — only the unfiltered reactions of executives to questions they
When a developer types "Show me NVIDIA's after-hours price" into an AI coding assistant, most systems draw a blank. The assistant recognizes the intent — but it has no contract specifying what paramet
The first time a solo quant realizes their data costs will exceed their strategy returns is not a gradual awakening. It is a number on a spreadsheet that stops you cold. You have backtested a strategy
--- "The opportunity expires before most trading terminals finish rendering the quote." At 14:32:07.341 UTC on a quiet Thursday, a cross-rate anomaly appeared between EUR/USD, GBP/USD, and EUR/GBP. Th
--- On any given trading day, the Shanghai Stock Exchange processes over 200 billion shares with a combined turnover exceeding ¥600 billion. Beneath that headline figure lies a quieter battle: the war
--- A junior researcher commits a new mean-reversion strategy at 11 PM on a Friday. Six months later, when the strategy underperforms by 15%, nobody can explain why. The historical data used for backt
--- The Problem Nobody Tells You About You write a beautiful mean-reversion strategy. It backtests well. You deploy it. And then, on a high-volatility day, your WebSocket feed delivers 50,000 ticks pe
--- For quant developers building systematic strategies on Chinese equities, the data decision is rarely simple. Tushare has long occupied the role of default choice for A-share researchers — a well-w
A production strategy blew up last week. Not because the alpha decayed — but because nobody remembered that the entry signal used a data feed that had quietly changed its timestamp format six months e
--- Network partitions happen. A fiber cut at your data center's upstream provider, a brief BGP flap, a momentary cloud infrastructure hiccup — these events last seconds or minutes. When your WebSocke
--- You pull your favorite stock's five-year daily OHLCV from a public data source. You run a moving average crossover backtest. The strategy returns 340% annualized. You are confident. You deploy cap
Every quant developer remembers the first time they opened PyPI and searched for "trading." The results were staggering: 847 packages with "trading" in the name. Pandas, NumPy, Backtrader, Zipline, Py
--- The Moment Everything Stopped At 10:02 AM ET on December 7, 2021, a routine configuration change in an AWS availability zone triggered a cascading failure across US-East-1. Within minutes, the new
"Price is not data. Price plus context is data. Price plus context plus history is a strategy." For quant traders and systems traders, this distinction matters more than it might first appear. A singl
The moment you try to query a decade of 1-minute OHLCV data for a single stock symbol — roughly 3.5 million rows — against a naive MySQL installation, you will watch a spinner for 90 seconds or longer
A trading system built on faulty latency assumptions does not fail dramatically. It fails quietly — slipping into a 200 ms disadvantage on every tick, compounding silently until the drawdown curve tel