Data
FOREX_eurdkk-day-Close

FOREX_eurdkk-day-Close

active ARFF Publicly available Visibility: public Uploaded 04-06-2019 by Jan van Rijn
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  • finance forex forex_close forex_day study_219
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Source: Dukascopy Historical Data Feed https://www.dukascopy.com/swiss/english/marketwatch/historical/ Edited by: Fabian Schut # Data Description This is the historical price data of the FOREX EUR/DKK from Dukascopy. One instance (row) is one candlestick of one day. The whole dataset has the data range from 1-1-2018 to 13-12-2018 and does not include the weekends, since the FOREX is not traded in the weekend. The timezone of the feature Timestamp is Europe/Amsterdam. The class attribute is the direction of the mean of the Close_Bid and the Close_Ask of the following day, relative to the Close_Bid and Close_Ask mean of the current minute. This means the class attribute is True when the mean Close price is going up the following day, and the class attribute is False when the mean Close price is going down (or stays the same) the following day. # Attributes `Timestamp`: The time of the current data point (Europe/Amsterdam) `Bid_Open`: The bid price at the start of this time interval `Bid_High`: The highest bid price during this time interval `Bid_Low`: The lowest bid price during this time interval `Bid_Close`: The bid price at the end of this time interval `Bid_Volume`: The number of times the Bid Price changed within this time interval `Ask_Open`: The ask price at the start of this time interval `Ask_High`: The highest ask price during this time interval `Ask_Low`: The lowest ask price during this time interval `Ask_Close`: The ask price at the end of this time interval `Ask_Volume`: The number of times the Ask Price changed within this time interval `Class`: Whether the average price will go up during the next interval

12 features

Class (target)nominal2 unique values
0 missing
Timestampdate1836 unique values
0 missing
Bid_Opennumeric1183 unique values
0 missing
Bid_Highnumeric1329 unique values
0 missing
Bid_Lownumeric1333 unique values
0 missing
Bid_Closenumeric1279 unique values
0 missing
Bid_Volumenumeric1823 unique values
0 missing
Ask_Opennumeric1207 unique values
0 missing
Ask_Highnumeric1311 unique values
0 missing
Ask_Lownumeric1341 unique values
0 missing
Ask_Closenumeric1280 unique values
0 missing
Ask_Volumenumeric1823 unique values
0 missing

19 properties

1836
Number of instances (rows) of the dataset.
12
Number of attributes (columns) of the dataset.
2
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
11
Number of numeric attributes.
1
Number of nominal attributes.
8.33
Percentage of binary attributes.
0
Percentage of instances having missing values.
0.47
Average class difference between consecutive instances.
0
Percentage of missing values.
91.67
Percentage of numeric attributes.
0.01
Number of attributes divided by the number of instances.
8.33
Percentage of nominal attributes.
52.07
Percentage of instances belonging to the most frequent class.
956
Number of instances belonging to the most frequent class.
47.93
Percentage of instances belonging to the least frequent class.
880
Number of instances belonging to the least frequent class.
1
Number of binary attributes.

10 tasks

0 runs - estimation_procedure: 20% Holdout (Ordered) - target_feature: Class
0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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