Methodology
Why market-data timestamps and freshness matter
Distinguish event, exchange, provider, receipt, and display times so a current-looking number is not mistaken for executable or contemporaneous data.
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Insights
Sourced explanations and practical research methods for individual investors and active traders.
Strategy Risk
What makes a backtest trustworthy
A trustworthy backtest preserves the information available at each date, exposes assumptions and costs, and survives tests it was not optimized to win.
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Understanding refinery stocks and crack spreads
Use crack spreads as transparent market indicators, then account for crude quality, product yields, operating costs, utilization, and location.
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Understanding European natural gas markets
A source-led map of the interacting supply, demand, infrastructure, and expectation variables behind European wholesale gas prices.
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Position sizing with ATR and defined risk
Understand what average true range measures, how it can scale a hypothetical risk unit, and why it cannot guarantee exits or define suitability.
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Portfolio concentration and scenario testing
Look through ticker counts to economic exposures, then use transparent shocks to find where correlated losses and liquidity needs may cluster.
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How ChartCompass uses AI, sources, and privacy boundaries
A practical checklist for verifying generated market explanations, separating sources from synthesis, and reviewing data handling before sharing sensitive context.
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Explaining market moves without confusing correlation and cause
A practical evidence ladder for describing what moved, what changed nearby, and how much confidence a causal explanation deserves.
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Earnings, guidance, and analyst revisions
Separate reported results, management's forward ranges, market expectations, and subsequent analyst revisions before explaining a reaction.
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Comparing stocks with different business models
Start with how each company earns cash, then normalize accounting definitions, capital needs, cycles, and risks before comparing valuation multiples.
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Combining technicals, fundamentals, and news
Use price behavior, company economics, and dated events as separate lenses that answer different questions instead of forcing them into one score.
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Building a decision-useful market watchlist
Turn a list of tickers into a dated research queue with a question, evidence, invalidation condition, next catalyst, and explicit status.
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