Data
FOREX_usdcad-minute-High

FOREX_usdcad-minute-High

active ARFF Publicly available Visibility: public Uploaded 04-06-2019 by Jan van Rijn
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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/CAD from Dukascopy. One instance (row) is one candlestick of one minute. 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 High_Bid and the High_Ask of the following minute, relative to the High_Bid and High_Ask mean of the current minute. This means the class attribute is True when the mean High price is going up the following minute, and the class attribute is False when the mean High price is going down (or stays the same) the following minute. Note that this is a hypothetical task, meant for scientific purposes only. Realistic trade strategies can only be applied to predictions on 'Close'-attributes (also available). # 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
Timestampdate375840 unique values
0 missing
Bid_Opennumeric13713 unique values
0 missing
Bid_Highnumeric13712 unique values
0 missing
Bid_Lownumeric13664 unique values
0 missing
Bid_Closenumeric13700 unique values
0 missing
Bid_Volumenumeric29094 unique values
0 missing
Ask_Opennumeric13705 unique values
0 missing
Ask_Highnumeric13698 unique values
0 missing
Ask_Lownumeric13686 unique values
0 missing
Ask_Closenumeric13694 unique values
0 missing
Ask_Volumenumeric29356 unique values
0 missing

62 properties

375840
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.
68.68
Third quartile of standard deviation of attributes of the numeric type.
9113188740.3
Maximum standard deviation of attributes of the numeric type.
45.77
Percentage of instances belonging to the least frequent class.
-0.12
First quartile of kurtosis among attributes of the numeric type.
0
Standard deviation of the number of distinct values among attributes of the nominal type.
Average entropy of the attributes.
172035
Number of instances belonging to the least frequent class.
1.3
First quartile of means among attributes of the numeric type.
9750.33
Mean kurtosis among attributes of the numeric type.
1
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
139132673150.36
Mean of means among attributes of the numeric type.
-0.28
First quartile of skewness among attributes of the numeric type.
0.55
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.03
First quartile of standard deviation of attributes of the numeric type.
0.99
Entropy of the target attribute values.
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
Second quartile (Median) of entropy among attributes.
0
Number of attributes divided by the number of instances.
2
Average number of distinct values among the attributes of the nominal type.
-0.12
Second quartile (Median) of kurtosis among attributes of the numeric type.
1.3
Second quartile (Median) of means among attributes of the numeric type.
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
26.57
Mean skewness among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
54.23
Percentage of instances belonging to the most frequent class.
828471720.56
Mean standard deviation of attributes of the numeric type.
-0.27
Second quartile (Median) of skewness among attributes of the numeric type.
203805
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
0.03
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-1.2
Minimum kurtosis among attributes of the numeric type.
8.33
Percentage of binary attributes.
Third quartile of entropy among attributes.
102739.04
Maximum kurtosis among attributes of the numeric type.
1.3
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
-0.12
Third quartile of kurtosis among attributes of the numeric type.
1530459404482.7
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
80.1
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
91.67
Percentage of numeric attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
2
The maximum number of distinct values among attributes of the nominal type.
-0.28
Minimum skewness among attributes of the numeric type.
8.33
Percentage of nominal attributes.
0
Third quartile of skewness among attributes of the numeric type.
264.68
Maximum skewness among attributes of the numeric type.
0.03
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.

1 tasks

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