Data
dow-jones-index

dow-jones-index

active ARFF Publicly available Visibility: public Uploaded 11-06-2021 by Meilina Reksoprodjo
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Author: Dr. Michael Brown Source: [UCI](https://archive.ics.uci.edu/ml/datasets/dow+jones+index) - 2017 Please cite: [Paper](https://link.springer.com/content/pdf/10.1007%2F978-3-642-39712-7_3.pdf) Dow Jones Index Data Set In our research each record (row) is data for a week. Each record also has the percentage of return that stock has in the following week (percent_change_next_weeks_price). Ideally, you want to determine which stock will produce the greatest rate of return in the following week. This can help you train and test your algorithm. Some of these attributes might not be use used in your research. They were originally added to our database to perform calculations. (Brown, Pelosi & Dirska, 2013) used percent_change_price, percent_change_volume_over_last_wk, days_to_next_dividend, and percent_return_next_dividend. We left the other attributes in the dataset in case you wanted to use any of them. Of course what you want to maximize is percent_change_next_weeks_price. Training data vs Test data: In (Brown, Pelosi & Dirska, 2013) we used quarter 1 (Jan-Mar) data for training and quarter 2 (Apr-Jun) data for testing. Interesting data points: If you use quarter 2 data for testing, you will notice something interesting in the week ending 5/27/2011 every Dow Jones Index stock lost money. ### Attribute information - quarter: the yearly quarter (1 = Jan-Mar; 2 = Apr=Jun) - stock: the stock symbol (see above) - date: the last business day of the work (this is typically a Friday) - open: the price of the stock at the beginning of the week - high: the highest price of the stock during the week - low: the lowest price of the stock during the week - close: the price of the stock at the end of the week - volume: the number of shares of stock that traded hands in the week - percent_change_price: the percentage change in price throughout the week - percent_chagne_volume_over_last_wek: the percentage change in the number of shares of stock that traded hands for this week compared to the previous week - previous_weeks_volume: the number of shares of stock that traded hands in the previous week - next_weeks_open: the opening price of the stock in the following week - next_weeks_close: the closing price of the stock in the following week - percent_change_next_weeks_price: the percentage change in price of the stock in the - following week days_to_next_dividend: the number of days until the next dividend - percent_return_next_dividend: the percentage of return on the next dividend

16 features

quarternumeric2 unique values
0 missing
stockstring30 unique values
0 missing
datestring25 unique values
0 missing
openstring722 unique values
0 missing
highstring713 unique values
0 missing
lowstring711 unique values
0 missing
closestring711 unique values
0 missing
volumenumeric750 unique values
0 missing
percent_change_pricenumeric745 unique values
0 missing
percent_change_volume_over_last_wknumeric720 unique values
30 missing
previous_weeks_volumenumeric720 unique values
30 missing
next_weeks_openstring720 unique values
0 missing
next_weeks_closestring715 unique values
0 missing
percent_change_next_weeks_pricenumeric745 unique values
0 missing
days_to_next_dividendnumeric105 unique values
0 missing
percent_return_next_dividendnumeric729 unique values
0 missing

19 properties

750
Number of instances (rows) of the dataset.
16
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
60
Number of missing values in the dataset.
30
Number of instances with at least one value missing.
8
Number of numeric attributes.
0
Number of nominal attributes.
0
Percentage of binary attributes.
4
Percentage of instances having missing values.
Average class difference between consecutive instances.
0.5
Percentage of missing values.
0.02
Number of attributes divided by the number of instances.
50
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.

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