TickDB API development tutorials, WebSocket integration and SDK examples
"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
In 2019, I spent three weeks building a backtesting engine from scratch. I wrote custom data loaders, rolled my own position tracking, and hand-rolled a naive portfolio p&l calculator. It worked. Then
--- "Price is the effect. The order book is the cause." Imagine this: your system is ingesting real-time NVIDIA options flow through a WebSocket stream. At 14:47:23 UTC, a network partition severs the
--- The Problem That Keeps Quant Teams Up at Night Imagine you are a quant researcher. You have spent three months building a mean-reversion strategy that looks spectacular on paper — 1.87 Sharpe rati
--- "Build it and they will come" works for software. It does not work for quantitative trading. In 2019, a talented backend engineer I know spent three months building a mean-reversion strategy on wh
At 3:47 AM Eastern Time on December 7, 2021, a routine deployment in AWS us-east-1 triggered a cascading failure that knocked out Elastic Load Balancing across the entire region for approximately thre
The $2,700 Mistake No One Talks About Your mean-reversion model had been humming along beautifully for eight months. Sharpe of 1.4. Maximum drawdown under 6%. Then NVIDIA announced a 10-for-1 split, a
A retail quant trader in Austin, Texas once showed me his backtest results. The strategy returned 31% annualized over three years with a Sharpe of 1.8. Clean equity curve, low drawdown. He was ready t
--- A junior quant once told me he spent $400 on premium futures data before realizing his strategy had negative expected value after commissions. He had optimized the wrong variable. The math is brut
--- "Price is the effect. The order book is the cause." — This principle guides every quant trader watching real-time market data. But what happens when the cause survives a server reboot, a deploymen
The invoice arrived at 8:47 AM on a Tuesday. The number was wrong — not catastrophically, but wrong enough that the finance team sent a Slack ping, and the engineering manager forwarded it with a sing
Every developer has encountered it: your application runs perfectly in testing, then collapses in production because a third-party API returned an opaque error, and you had no idea whether to retry, w
--- "Price is the effect. Cost allocation is the strategy." When you are running a systematic strategy with $50,000 in capital, every dollar matters. Not because $100 is make-or-break — but because th
--- The Moment the Book Tells You to Move At 9:47 AM on a Tuesday, Apple's order book reads like a calm lake. Bid sizes cluster between 12,000 and 18,000 shares across the first five levels. Ask sizes
The request bounced. Your client logged the response body, parsed it, and found the error details. Within 200 milliseconds, the retry logic fired. The system recovered without human intervention. This
The strategy works. Sharpe 1.4. Max drawdown under 8%. Three years of consistent alpha on live accounts. Then the calls start. Your trading has outgrown your spreadsheets, and friends, former colleagu
"Price is the effect. The order book is the cause." A $12.50 dividend. A 4-for-1 split. A 1980 closing price of $2,375 per share. These are not hypothetical distortions. They are the documented realit
"Twenty dollars," the developer said, staring at his screen. "Twenty dollars for one night of running my mean-reversion strategy." He was not wrong. His Python script had polled a market data API ever