TickDB API development tutorials, WebSocket integration and SDK examples
Price is the effect. The order book is the cause. At 9:30:00 AM ET on a typical trading day, Apple's order book sits in relative equilibrium — bid sizes roughly matching ask sizes, the spread compress
--- "Price is the effect. The order book is the cause." In systematic trading, this principle drives every decision. But what happens when your trading system requires market data that no standard API
--- The strategy looked perfect on paper. In 2021, a well-known hedge fund published a paper on a cross-sectional momentum strategy involving sector rotation and mean-reversion filters. The backtests
--- "China's A-share market is the world's second-largest by daily turnover — yet most Western quant tools treat it as a footnote." That asymmetry has real consequences. A quant researcher building a
--- You spent three years building a strategy that works. Your Sharpe ratio holds across bull markets, bear markets, and the 2022 rate-shock regime. You run the backtests yourself. You coded every sig
Every evening around 4:05 PM ET, when US equity markets have closed their regular session, a quiet problem begins. The day's 390 minutes of price action — captured in 1-minute OHLCV candles for every
--- "Forty-seven terabytes. That is the uncompressed size of 10 years of minute-level US equity OHLCV data for the S&P 500 universe — roughly 750,000 trading hours, each recorded at 1-minute intervals
--- The $40,000 Mistake One Quant Made at 2 AM The algorithm was elegant. Six months of backtesting had produced a Sharpe ratio of 2.1. The strategy targeted microstructural anomalies in after-hours t
--- The strategy returned 34.7% annualized in backtesting. Sharpe ratio: 1.82. Maximum drawdown: −6.2%. The equity curve climbed steadily for three years across 847 trades. Confident numbers. Clean eq
At 12:01 AM UTC on December 7, 2021, a single AWS Availability Zone in the us-east-1 region lost power. Within 90 seconds, a cascading failure had knocked out three of the five availability zones in t
A quant strategy that returns 34% annualized in simulation and −12% in live trading almost always has a data problem at its root. The gap is rarely a flawed alpha. It is missing data — gaps during tra
--- Every quantitative trader has been there. You run the backtest. The equity curve climbs smoothly to the right. Sharpe ratio of 1.8. Maximum drawdown of 4.2%. Win rate of 63%. You print the PDF, sh
--- "Show me the slope, not just the volume." A senior market maker once told me this during a late-night calibration session. She had just watched a junior analyst present a beautiful chart of order
--- "Connection reset by peer." If you've ever seen that error at 9:31 AM ET — the single most volatile minute of the trading day — you know the pain is not the disconnect itself. It is the gap: the c
--- Every production market data system experiences it eventually: a brief network hiccup, a momentary cloud infrastructure blip, or a server maintenance window. The WebSocket connection drops. For 5
--- "Price is the effect. The connection is the prerequisite." On a Tuesday morning in March 2025, a systematic trading firm lost $340,000 in potential alpha because their WebSocket connection silentl
Three years ago, a systematic fund with $50M AUM had 12 strategies running in production. Today, with $200M and a team of eight quants, they have 23 strategies — and the ops team cannot tell you with
--- "Price is the effect. Liquidity is the cause." A backtest that ignores slippage is like a flight simulator that never tells you the plane will eventually run out of fuel. You will feel like a hero
--- The Strategy That Should Have Made $2 Million In early 2023, a systematic trader we'll call him "Alex" ran a backtest on a mean-reversion strategy across 15 years of S&P 500 data. The results were
The server sent a event at 14:23:47 UTC. Your client logged it, notified the monitoring system, and initiated a reconnect sequence. By 14:28:52 UTC, the WebSocket was back open and streaming live dat