TickDB API development tutorials, WebSocket integration and SDK examples
--- "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
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