Is Bitcoin Correlated With Stocks? What IMF Data Shows
IMF: Bitcoin and the S&P 500 had a 0.01 correlation in 2017–19 and 0.36 in 2020–21. What changed, what it means for diversification, limits.
Long reads built on primary sources: peer-reviewed research, official exchange documentation and regulators. Every number has a source; quotes are checked against the original.
IMF: Bitcoin and the S&P 500 had a 0.01 correlation in 2017–19 and 0.36 in 2020–21. What changed, what it means for diversification, limits.
A study of 29 exchanges found wash trading above 70% of reported volume on unregulated ones. The tests it used and what it means for traders.
Griffin and Shams (Journal of Finance): Tether flows followed price drops and preceded Bitcoin rises. What they measured, what they could not prove.
The Kelly formula from Edward Thorp's paper applied to a trade with a stop and a target, and why half Kelly is the practical choice.
A backtest on the current coin list ignores every dead coin. What Brown, Goetzmann, Ibbotson and Ross showed, with an example and a checklist.
Liu and Tsyvinski (Review of Financial Studies): bitcoin returns show time-series momentum and respond to attention. Numbers, sample and limits.
Open interest counts contracts still open, not trades. How it changes, how to read it with price, and what research on futures markets found.
Slippage has two parts: walking the order book and the price move your order causes. What the research says, with a worked order book example.
The Cont–Kukanov–Stoikov study of 50 stocks: net order flow at the best bid and ask explains short-term price changes. Formula, example, limits.
The blog publishes long reads about market structure, derivatives, testing trading ideas and order flow. Articles are built on primary sources: peer-reviewed papers in journals such as the Journal of Financial Economics and the Review of Financial Studies, official documentation of exchanges, and publications of regulators and recognized research institutions. We read the original, check every quotation against it and cite it at the end of the article.
We do not publish news, price predictions, sponsored reviews, rewritten forum posts or lists of "best indicators". If an article states a number, the number has a source listed at the end of the article, and you can open it yourself.
Research covers large tests: the Quasimodo pattern over a year of data, long histories on higher timeframes, regimes and coin selection. Backtesting and overfitting explains how good-looking results are produced by chance and how to protect yourself: out-of-sample checks, the number of variants tried, forward tests with criteria written in advance. Order flow looks at delta, CVD, footprint and the order book with tick data. Market structure defines swings, BOS, CHoCH, order blocks, fair value gaps and liquidity precisely. Arbitrage covers price gaps between exchanges and what it takes to capture them after fees and transfers.
Every article starts with key takeaways, so you can see the conclusion in a minute. Numbers in the text link to notes and to a list of sources at the end. We explain the method behind a finding, not just the headline number, and we say where the evidence is weak. Articles are updated when new data changes the conclusion, and the update date is shown next to the publication date.
A quotation appears only if we have read it in the original source, and it is attributed to its authors with the publication and year. Our own numbers come with the sample size and, where it matters, the error band. We prefer short, checkable claims over sweeping ones, and when a result depends on an assumption, such as the fee level, we show how it changes when the assumption changes.
The OrderBlock.net research team, the same people who build the scanner. Every article is based on primary sources, which are listed at the end.
No. They are research and education. Results on history do not guarantee future results.
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