title: Fit arima model with weekly data (quantmod)
body: <p>I am working in R with weekly financial data downloaded directly from <code>quantmod</code>.</p>
  <p>My question is, if I want to apply ARIMA models, is it necessary to transform the data to a time series (ts) or can I work directly with the closing prices (xts zoo) obtained from quantmod? I ask this question because I have directly used the auto.arima (<code>forecast</code> package) function with the closing prices obtained and it has proposed me a model, but I do not know if the procedure is quite correct.</p>
  <p>If I finally need to transform such data to time series (ts), what is the process?</p>
  <p>Is this correct?</p>
  <pre><code>getSymbols(&quot;^N225&quot;,from=&quot;1999-01-01&quot;, to = &quot;2022-03-23&quot;, periodicity =&quot;weekly&quot;)
  N225C&lt;-N225[,4]
  </code></pre>
  <p>I get data like this:</p>
  <pre><code>             N225.Close
  1999-01-01   13536.56
  1999-01-08   13738.86
  1999-01-15   14245.42
  1999-01-22   14342.32
  1999-01-29   14086.85
  
  structure(c(13536.55957, 13738.860352, 14245.419922, 14342.320313, 
  14086.849609, 13952.400391, 14146.790039, 14470.450195, 14183.450195, 
  15502.139648, 15717.919922, 15986.040039, 16327.55957, 16846.689453, 
  16727.080078), class = c(&quot;xts&quot;, &quot;zoo&quot;), src = &quot;yahoo&quot;, updated = structure(1648408487.85182, class = c(&quot;POSIXct&quot;, 
  &quot;POSIXt&quot;)), index = structure(c(915148800, 915753600, 916358400, 
  916963200, 917568000, 918172800, 918777600, 919382400, 919987200, 
  920592000, 921196800, 921801600, 922406400, 923011200, 923616000
  ), tzone = &quot;UTC&quot;, tclass = &quot;Date&quot;), .Dim = c(15L, 1L), .Dimnames = list(
      NULL, &quot;N225.Close&quot;))
          
  </code></pre>
  <p>Is this process correct?:</p>
  <pre><code>start = c(1999, 1)
  tsnikkei&lt;-ts(N225C, start = start, frequency = 52)
  arimanikkei&lt;-auto.arima(tsnikkei, trace = TRUE, lambda = 0)
  </code></pre>
  <p>Or can I directly use the closing prices?</p>
  <pre><code> arimanikkei&lt;-autoarima(N225C, trace = TRUE, lambda = 0)
  </code></pre>
  <p>Thanks in advance and sorry for my english</p>