Z-Score Trading is a quantitative investment strategy that utilizes the Z-score statistical measure to identify assets whose current price or a specific indicator has deviated significantly from its historical mean, signaling potential overbought or oversold conditions. This strategy operates on the statistical assumption of mean reversion.
Mechanism
The mechanism involves calculating the Z-score for a selected financial time series, such as an asset’s price, trading volume, or a technical indicator, relative to its moving average and standard deviation over a defined historical period. A high absolute Z-score suggests an extreme deviation, which then triggers a trade entry based on the expectation of reversion to the mean.
Methodology
In crypto investing and smart trading, Z-score trading can be applied to various digital assets to detect statistical arbitrage opportunities or identify relative value in volatile markets. Algorithmic systems continuously monitor Z-scores across a basket of cryptocurrencies or pairs, executing automated buy or sell orders when predefined Z-score thresholds are crossed, particularly for institutional options trading or delta-neutral strategies where statistical edges are sought.
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