Market Data and Its Traps

Where price data comes from, what it quietly hides, and how to clean it before it misleads a backtest.

What you will be able to do

Distinguish bar, tick and quote data, and choose the granularity a question needs.
Detect missing bars, bad prints, duplicated timestamps and timezone errors.
Explain how splits, dividends and futures rolls distort raw prices.
Recognise survivorship bias in a list of instruments.

1
Where market data comes from
Exchanges, vendors and brokers; bars, ticks and quotes; what each one costs and what it leaves out.
Coming next
2
Timestamps, sessions and timezones
Bar-labelling conventions, exchange hours, daylight saving, and why "the close" can mean different things.
Coming next
3
Cleaning data: gaps, outliers and duplicates
A repeatable checklist for finding and handling bad rows before they reach a backtest.
Coming next
4
Corporate actions and continuous futures
Splits, dividends, adjusted prices and futures rolls — how each one changes the series you test.
Coming next
5
Survivorship and selection bias
Why a list of today's instruments is a biased sample of the past, and what to use instead.
Coming next