This GET method entails extracting data for analysis on your behalf. Note this carries a higher credits requirement. It is recommended to send in your own price data using POST endpoints if possible to increase the number of requests that can be made and at faster speeds.

Pearson’s correlation coefficient is used so often by many, albeit is frequently not the correct measure of dependency for a returns series. It measures linear relationships between variables but can be misleading when data is non-normally distributed or contains outliers, which is common in financial returns that exhibit skewness and fat tails.

Spearman’s Rho is a rank-based correlation measure that captures monotonic relationships between variables, making it more robust to outliers and non-linear dependencies often present in financial data. It transforms the raw values into ranks before calculating correlation, which helps identify patterns even when the relationship isn’t strictly linear.

Kendall’s tau is another rank-based correlation coefficient that measures the ordinal association between two variables based on concordant and discordant pairs. It’s particularly useful for smaller sample sizes and provides a more robust statistical inference than Pearson’s when the data doesn’t follow bivariate normal distribution, making it valuable for analyzing market dependencies during stressed periods.

GitHub Code Examples

GitHub Example

GitHub Example

Request Body (Curl)

curl -X GET "https://api.cryptowizards.net/v1beta/correlations?symbol_1=BTCUSDT\
&symbol_2=ETHUSDT&exchange=Binance&interval=Daily&period=365" \
-H "Content-Type: application/json" \
-H "X-api-key: REPLACE_WITH_YOUR_API_KEY"