The Problem: Candlestick Gaps That Confuse Users and Algorithms
When our team integrated US stock market data into a platform originally built for cryptocurrency traders, we ran into a persistent issue: candlestick charts exhibited ugly jumps around market open and close. Pre-market price moves would disappear from the visual timeline, and low-volume after-hours prints would create phantom volume spikes. The root cause? Most raw data feeds dump all ticks into a single undifferentiated stream, ignoring the fact that US equities trade in three distinct sessions — pre-market (4:00–9:30 ET), regular (9:30–16:00), and after-hours (16:00–20:00). Our users, many of whom are professional advisors and algo traders, demanded a chart that was visually continuous without sacrificing logical accuracy.
Traditional Pains: When Advisors Manually Strip Session Noise
Before we shipped our solution, we spent hours interviewing power users. A recurring complaint: they were forced to manually filter out non-regular-hours data before running technical analysis, because indicators like VWAP and RSI would be skewed by stray trades in thin markets. This manual step was error-prone and impossible to automate at scale. They needed the platform to handle session semantics transparently, leaving them to focus on strategy.
