Correlation Heatmaps

Ten dollars is the cost of the data feed. The analysis provided in the note orb trading crypto against hillary publishes on this covers correlation heatmaps for identifying whether an opening range breakout represents an isolated move or a systemic shift across the crypto sector.

Isolating Asset Specificity

A single asset moving outside its opening range does not indicate a trend change without context. A heatmap shows the mathematical relationship between various tokens during the first hour of liquid trading. If a specific coin breaks its fifteen minute range while the rest of the market stays flat, the move is idiosyncratic. This suggests local liquidity or a specific news event rather than a market rotation. Conversely, if every asset in the basket shows high positive correlation during the same timeframe, the breakout is driven by broader market momentum. Tracking these shifts prevents taking a trade based on a fluke move that lacks broad participation.

Mapping Market Breadth

Correlation matrices reveal the strength of the connection between assets during the intraday session. A heatmap uses color to represent the coefficient of correlation. When the heat intensifies across the entire grid, it signals a high-beta environment where individual price action is secondary to the general direction of the market. During the thirty minute range, a sudden spike in correlation often precedes a volatility expansion. If an asset breaks out but the heatmap shows declining correlation with its peers, the move lacks the support of a broader trend. This distinction changes the execution of the trade. A lone mover is a scalp, while a correlated move is a trend play.

Timeframe Synchronicity

The scale of the correlation matters. A move that appears significant on a 5 minute chart might dissolve when viewed against the sixty minute range. Heatmaps should be recalculated at different intervals to see if the correlation holds as the session progresses. High correlation during the premarket often shifts once the regular trading hours begin. If the correlation breaks down after the market open, the initial move was likely a liquidity hunt rather than a structural shift. Monitoring the relationship between assets across the first fifteen minutes of the session helps identify if the initial volatility is being sustained by the wider market.

Detecting Divergence

Divergence occurs when one asset breaks its session high while the heatmap shows a decoupling from the index. This lack of coordination is a signal of idiosyncratic risk. In a healthy trend, the breakout asset should move in lockstep with its high-correlation peers. A heatmap helps confirm that the movement is not an outlier. If the heatmap remains dark while one asset turns bright, the move is isolated. If the entire heatmap turns bright simultaneously, the entire sector is reacting to a macro variable. This mechanical check separates systemic shifts from noise.