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I have time series data for top 10 cryptocurrencies including these features:

open, close, high, low, volume.

1). I want to know which method is better for correlation testing between them - Pearson's Correlation or Spearman Correlation? Why?

2). Correlation should be tested for which price - low, high, open, close, average?

3). Since it is time series data, for testing correlation how much time period data is required(minimum)?

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  • $\begingroup$ Hi this looks more like an Project. For the Time-series you can use influxdb influxdata.com for the analyse python pandas $\endgroup$
    – Denis Kohl
    Commented Dec 23, 2021 at 19:53
  • $\begingroup$ Possibly related (because you appear to be asking about corr( price_it, price_jt ) for two different financial assets i and j): stats.stackexchange.com/questions/555540/… $\endgroup$
    – Adrian
    Commented Dec 23, 2021 at 20:09
  • $\begingroup$ Also related: stats.stackexchange.com/questions/133155/… $\endgroup$
    – Adrian
    Commented Dec 23, 2021 at 20:11
  • $\begingroup$ @Adrian I already read those solutions but here I am asking in context with cryptocurrencies means they don't follow the assumptions of pearson correlation (normaility). Also please could you answer other two questions as well. $\endgroup$
    – The_Different
    Commented Dec 24, 2021 at 4:06

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