I'm doing a bitcoin statistical analysis using Python. The bitcoin prices consist of close,open, low, high prices per an hour. For statistical analysis, which price do I need to take to consider. Is it close price? Or the mean prices.

Many of the analysis had used the closing price as shown below. What is the base for that? What if we consider the mean of them?


Sorry if this is not the write place to post this question

1 Answer 1


I worked in IT in the traditional finance industry for a while many moons ago.

There is no 'right' answer to what you want. What's important is not that you use one or other, but that you are consistent and reasonable in your choice. Being consistent example: if you use the open price, always use the open price. Being reasonable example: if you are analysing for highs, then use the highs that come in.

Bitcoin is a 24 hour market unlike traditional trading where they will often use the close. There, the close has a particular meaning: people have often borrowed to trade a position and they want to leave that position before the close, particularly at the end of each session or before weekends. If they do not, they risk the market moving against them at the next open, and risk additional costs for holding borrowed money during a period where there's no trading. Thus, you may prefer to use the close because that's what many traditional traders do, even though it has less meaning to Bitcoin, and even less meaning for hourly closes.

If your analysis is directed at trading, you might want to try https://quant.stackexchange.com/


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