Data
FOREX_usdjpy-day-Close

FOREX_usdjpy-day-Close

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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 USD/JPY 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
Timestampdate1835 unique values
0 missing
Bid_Opennumeric1778 unique values
0 missing
Bid_Highnumeric1774 unique values
0 missing
Bid_Lownumeric1776 unique values
0 missing
Bid_Closenumeric1772 unique values
0 missing
Bid_Volumenumeric1824 unique values
0 missing
Ask_Opennumeric1776 unique values
0 missing
Ask_Highnumeric1765 unique values
0 missing
Ask_Lownumeric1780 unique values
0 missing
Ask_Closenumeric1769 unique values
0 missing
Ask_Volumenumeric1824 unique values
0 missing

19 properties

1835
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.
0.01
Number of attributes divided by the number of instances.
91.67
Percentage of numeric attributes.
50.84
Percentage of instances belonging to the most frequent class.
8.33
Percentage of nominal attributes.
933
Number of instances belonging to the most frequent class.
49.16
Percentage of instances belonging to the least frequent class.
902
Number of instances belonging to the least frequent class.
1
Number of binary attributes.
8.33
Percentage of binary attributes.
0
Percentage of instances having missing values.
0.48
Average class difference between consecutive instances.
0
Percentage of missing values.

10 tasks

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