Open morfeo630 opened 1 year ago
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Hi Valter,
Thank you for your questions.
Kindly see our response below:
THE EOD DATABASE CONTAINS OHLCV DATA AS WELL AS ADJUSTMENTS/EXCHANGE CORRECTIONS -- these are the product's inclusions. You can learn about the exact column definitions by following this link: https://data.nasdaq.com/databases/EOD/documentation?anchor=column-definition [1]. The EOD database adjusts split/cash dividend/spinoff. Please note that EOD data is available by 5:00 PM ET, and adjustments/exchange corrections are updated by 9:30 PM ET.
Please consult the methodology section of the product, which details how adjusted values are calculated. You may view it here: https://data.nasdaq.com/databases/EOD/documentation?anchor=knowledge-base [2].
The adjusted price data is backward-adjusted. This means today's adjusted price will always equal the price traded in the market. Adjustments apply only to historical data; the further back you go into the past, the greater the cumulative adjustments are likely to be, as corporate actions accumulate. THE ADJUSTMENT TAKES IN CONSIDERATION THE 1.65 DIVIDEND THAT TOOK PLACE ON NOV. 9.
Regarding which of the two is best used for calculation, here is an article on Investopedia that details the difference between the unadjusted and adjusted prices (also details the benefits and criticism of using adjusted stock prices): https://www.investopedia.com/terms/a/adjusted_closing_price.asp#:~:text=Key%20Takeaways-,The%20adjusted%20closing%20price%20amends%20a%20stock's%20closing%20price%20to,price%20before%20the%20market%20closes [3].
The above link is an example only. There are many other third-party sites that discuss which of the two should be used depending on the use case.
We hope this information helps. Please let us know should you have further questions.
Best regards, Kim
[1] https://data.nasdaq.com/databases/EOD/documentation?anchor=column-definitions [2] https://data.nasdaq.com/databases/EOD/documentation?anchor=knowledge-base [3] https://www.investopedia.com/terms/a/adjusted_closing_price.asp#:~:text=Key%20Takeaways-,The%20adjusted%20closing%20price%20amends%20a%20stock's%20closing%20price%20to,price%20before%20the%20market%20closes
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> On Fri, Dec 30, 2022 at 8:08 AM EST, Nasdaq/data-Link-Python ***@***.***> wrote:
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Hello to all, I have some questions regarding the adjusted data.
- I understand that the data can vary from broker to broker for a little bit but why nasdaq have in the same row the "regular" data (open, high, low, close) and the adjusted data (adj_open, adj_high, adj_low, adj_close)?
- Why the adj_* data exists in first place and how is calculated?
- Why for the date before and included 2022-11-08 the adj_* data is so different from the "regular" data?
- What data is best to use for further calculation and data manipulation?
Folowing is the data:
ticker date open high low close volume dividend split adj_open adj_high adj_low adj_close adj_volume 0 IBM 2022-11-14 142.63 146.08 142.18 144.20 5293453.0 0.00 1.0 142.630000 146.080000 142.180000 144.200000 5293453.0 1 IBM 2022-11-11 141.50 144.13 140.96 143.17 5869298.0 0.00 1.0 141.500000 144.130000 140.960000 143.170000 5869298.0 2 IBM 2022-11-10 140.26 141.37 138.29 141.23 5386540.0 0.00 1.0 140.260000 141.370000 138.290000 141.230000 5386540.0 3 IBM 2022-11-09 137.95 138.90 136.94 137.39 4718328.0 1.65 1.0 137.950000 138.900000 136.940000 137.390000 4718328.0 4 IBM 2022-11-08 139.00 140.93 138.72 140.04 5039458.0 0.00 1.0 137.350475 139.257571 137.073797 138.378133 5039458.0 5 IBM 2022-11-07 136.64 138.70 136.51 138.34 4042576.0 0.00 1.0 135.018481 137.054035 134.890024 136.698307 4042576.0 6 IBM 2022-11-04 135.65 137.73 134.94 136.96 4176645.0 0.00 1.0 134.040229 136.095546 133.338655 135.334684 4176645.0 7 IBM 2022-11-03 136.42 136.48 133.97 134.47 4441075.0 0.00 1.0 134.801092 134.860380 132.380166 132.874233 4441075.0 8 IBM 2022-11-02 137.75 140.17 136.80 136.83 5360222.0 0.00 1.0 136.115309 138.506590 135.176582 135.206226 5360222.0 9 IBM 2022-11-01 138.25 138.65 136.70 138.20 3574815.0 0.00 1.0 136.609375 137.004628 135.077769 136.559968 3574815.0
The upper data was received using:
data = nasdaqdatalink.get_table('QUOTEMEDIA/PRICES', ticker='IBM', date={'gte': '2022-11-01', 'lte': '2022-11-14'}, paginate=True) print(data)
Thank you in advance for your time and answers and helping me understanding and getting a dipper knowledge of the market data. Best regards, Valter
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Hello to all, I have some questions regarding the adjusted data.
Folowing is the data:
The upper data was received using:
Thank you in advance for your time and answers and helping me understanding and getting a dipper knowledge of the market data. Best regards, Valter