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What should you check before sharing trading data with AI?
Check AI trading data privacy before sharing records. Review permissions, model training, retention and deletion to keep control of your trading information.
Oct 30, 2026
How to fact-check AI-generated market summaries
Check AI hallucinations financial research against original releases, timestamps and calculations. Separate verified market facts from unsupported claims.
Oct 30, 2026
How bias in training data can affect AI trading analysis
AI trading model bias can distort analysis. Learn how missing records, uneven coverage and information timing affect the evidence behind trading scores.
Oct 30, 2026
How missing trade data can distort a performance review
Missing trading data analysis starts with reconciliation. Check trades, charges and open positions before drawing conclusions from a performance review.
Oct 29, 2026
Why automation bias matters when reviewing trading data
Automation bias trading reviews need independent checks. Learn how to question scores, verify trade records and keep automated summaries in context.
Oct 29, 2026
Why AI performance scores need context and explanation
AI trading performance scores need context, not blind trust. Learn how to review inputs, trading behaviour and outcomes without treating scores as signals.
Oct 29, 2026
Why does free margin change while a trade is open?
Understand why free margin changes during an open trade. Separate equity movements from margin requirements and check costs, currency conversion and risk.
Oct 28, 2026
How to read margin level alongside your open positions
Learn how to read margin level alongside open positions. Understand equity, used margin and shared exposure without treating a percentage as a safety score.
Oct 28, 2026
Why your trading balance and equity show different amounts
Balance vs equity trading explained: balance tracks booked activity; equity includes open results. Learn how to reconcile positions, charges and credit.
Oct 28, 2026