How to Compare Market Data Feeds Without Misreading Timestamps, Sessions and Chart Settings

Two market-data views can describe the same instrument and still show different numbers.
One chart may display a larger price move. Another may show a different volume figure. Historical prices may not line up exactly, or the same trading session may appear to begin and end at different times.
Before treating the discrepancy as a data-quality problem, compare the inputs first.
This post walks through a practical workflow for separating genuine data discrepancies from differences caused by instrument identity, timestamps, chart configuration and session settings.
Start With the Exact Instrument
A company name is not always enough to identify the exact market instrument.
The same company may trade on multiple exchanges. Similar names may refer to different securities, and the same ticker can sometimes exist in different markets.
Before comparing two market-data views, match:

• ticker
• exchange or venue
• currency
• instrument type If those details differ, the charts may be describing different instruments even when the labels look similar. A useful comparison starts with identity before moving to price behaviour. Check the Timestamp The next question is simple: When was each displayed value actually updated? A screen can refresh without every value changing at the same moment. One source may reflect a recent transaction while another may use delayed data, a different aggregation cycle or another upstream provider. When comparing two values, record:
• displayed timestamp
• time zone
• known delay
• market session
• last update time The goal is to make sure both displays refer to the same period. Align the Time Zones Two charts can describe the same market event while displaying different clock times. For example, one interface may use Eastern Time while another uses UTC. The timestamps are not necessarily inconsistent. They may simply use different time zones. Before interpreting a mismatch, normalize the time settings or convert both values to the same zone. This small step prevents a surprising number of false discrepancies. Match the Chart Interval A five-minute candle and a daily candle summarize different amounts of activity. Even two intraday charts can look different when one uses five-minute candles and the other uses fifteen-minute candles. Before comparing the structure of a move, align:
• candle duration
• date range
• start time
• end time Aggregation matters. A short interval can reveal volatility that disappears when the same data is compressed into a longer period. Neither view is automatically more accurate. They answer different analytical questions. Compare the Trading Sessions Session settings can materially change a chart. One source may show only regular trading hours. Another may include pre-market and after-hours activity. That difference can affect:
• opening values
• closing values
• intraday highs and lows
• visible gaps
• total volume If two charts disagree, check whether both include the same trading hours before looking for a more complex explanation. Review Historical Adjustments Historical charts introduce another variable: adjustment methodology. A stock split can change how earlier prices appear. Some charting systems also adjust for dividends or other corporate actions. If one chart uses adjusted data and another does not, their historical series can differ substantially even when both are based on legitimate source data. For long-term comparisons, always check:
• split adjustments
• dividend adjustments
• back-adjustment settings
• corporate-action handling Give Volume a Fair Comparison Volume can also become misleading when the observation periods differ. Suppose you check today's volume halfway through the session and compare it with yesterday's completed session. Those numbers represent different amounts of elapsed time. A more useful comparison may involve:
• the same portion of each session
• completed session vs completed session
• average volume at a comparable time of day The objective is not simply to compare numbers. It is to compare numbers that describe equivalent conditions. Understand What a Screener Result Actually Means A market screener helps reduce a large universe of instruments to a smaller set that matches selected criteria. But a screener result is not a conclusion. Its output depends on:
• filter definitions
• market coverage
• observation period
• available data
• calculation methodology If a screener flags an unusual volume condition, the next step should be to investigate the context rather than immediately infer a cause. Record the filter settings and scan time so the result can be reproduced later. Add Sector Context Once the data is aligned, widen the comparison. Ask whether related instruments moved in a similar direction over the same period. If several instruments in the same sector show comparable activity, the observation may reflect a broader pattern. If the movement is concentrated in one instrument, the research question changes. Sector context helps describe the pattern. It does not establish why the move occurred, and it does not predict what happens next. That distinction matters. Separate Observation From Explanation A useful research workflow separates what was observed from what is inferred. For example: The instrument gained 2.3% during the regular session while several sector peers also moved higher.

That is an observation.
Sector demand caused the instrument to rise.

That is an explanation.
The second statement may be reasonable, but it requires additional evidence beyond the chart itself.
Keeping those two layers separate makes analytical notes easier to review and challenge later.
Build a Repeatable Research Note
A good market-data comparison should be reproducible.
A short research note can record:
Instrument
Ticker, venue and currency.
Source
Where the data came from.
Timestamp
Including the time zone.
Interval
For example, five-minute or daily.
Session
Regular hours, extended hours or both.
Settings
Including historical adjustments.
Observation
What was actually visible in the data.
Open questions
What remains unresolved.
This structure makes it easier to revisit the same comparison later without reconstructing the context from memory.
A Simple Comparison Checklist
Before deciding that two market-data feeds disagree, check:

1. Are they showing the same instrument?
2. Are the timestamps aligned?
3. Are the time zones the same?
4. Are the candle intervals equivalent?
5. Are both charts using the same trading session?
6. Are historical adjustments configured consistently?
7. Are volume figures calculated over comparable periods?
8. Are the sources using the same aggregation method? Only after those questions are answered does it make sense to investigate a deeper data-quality issue. The Core Principle A useful market-data workflow is not about forcing every source to display identical numbers. It is about understanding why the numbers differ and documenting the conditions behind the comparison. Better analysis often starts with something simple: align the inputs before interpreting the output. This research note is part of the Ositrustees technical research series on market data, source comparison and structured analytical workflows. Research. Compare. Verify.