API Documentation
For flexible, fast, low cost queries
Data done for you
This is a method whereby you provide the api with any price data you wish for rapid turnaround and much lower credits used.
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.
All price series must match in length
curl -X POST "https://api.cryptowizards.net/v1beta/correlations" \
-H "Content-Type: application/json" \
-H "X-api-key: REPLACE_WITH_YOUR_API_KEY" \
-d '{
"series_1_closes": [1.1, 1.2, 1.3, 1.4],
"series_2_closes": [4.1, 4.2, 4.3, 4.4]
}'{
"kendall": 0.4590806019377448,
"spearman": 0.6260235003092146,
"pearson": 0.5322145284631511
}