I am trying to (re)build a basic prediction model of the S&P 500 INDEX (data orignates from Yahoo finance)
I have data that was programmed to acquire information every 5 hours which means multiple data points per day.The problem is sometimes the data logger fails or batteries die or whatever and there are
I need to add two irregular time series (covering business days). I have two xts series for two different products A + B.
李俊杰 2021-04-04 08:04 开发者_JS百科RT，入手后，不算牌照魏超 开发者_如何学Python
I have a xts object (stock price time series) that is comprised of intraday data for multiple years i.e. the data is a continuous stream that stitches together intraday data for each day in the period
I have 1 minute intraday price data which has missing data points. As such I want to fill them. I read through the suggestions in the following post and tried a similar procedure:
pretty newb question here, but I have not been able to track down a solution for some time: I have an XTS object of trading indicators (indicate) for stock data that looks like
My situation: I have a number of csv files all with the same suffix pre .csv, but the first two characters of the file name are different (ie AA01.csv, AB01.csv, AC01.csv etc)
I can\'t seem to use TTR indicator functions direclty with period.apply() from XTS. Please help me figure out what I\'m doing wrong.
I have an xts object, which I used to.period() on to \'up\' the period to produce a second xts object. Then I combined the two xts objects back to the faster period. How can I set cbind() so that the
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