Language:
English
繁體中文
Help
圖資館首頁
Login
Back
Switch To:
Labeled
|
MARC Mode
|
ISBD
Financial data resampling for machin...
~
Borges, Tome Almeida.
Financial data resampling for machine learning based tradingapplication to cryptocurrency markets /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Financial data resampling for machine learning based tradingby Tome Almeida Borges, Rui Neves.
Reminder of title:
application to cryptocurrency markets /
Author:
Borges, Tome Almeida.
other author:
Neves, Rui.
Published:
Cham :Springer International Publishing :2021.
Description:
xv, 93 p. :ill., digital ;24 cm.
Contained By:
Springer Nature eBook
Subject:
CryptocurrenciesStatistical methods.
Online resource:
https://doi.org/10.1007/978-3-030-68379-5
ISBN:
9783030683795$q(electronic bk.)
Financial data resampling for machine learning based tradingapplication to cryptocurrency markets /
Borges, Tome Almeida.
Financial data resampling for machine learning based trading
application to cryptocurrency markets /[electronic resource] :by Tome Almeida Borges, Rui Neves. - Cham :Springer International Publishing :2021. - xv, 93 p. :ill., digital ;24 cm. - SpringerBriefs in applied sciences and technology, Computational intelligence. - SpringerBriefs in applied sciences and technology.Computational intelligence..
This book presents a system that combines the expertise of four algorithms, namely Gradient Tree Boosting, Logistic Regression, Random Forest and Support Vector Classifier to trade with several cryptocurrencies. A new method for resampling financial data is presented as alternative to the classical time sampled data commonly used in financial market trading. The new resampling method uses a closing value threshold to resample the data creating a signal better suited for financial trading, thus achieving higher returns without increased risk. The performance of the algorithm with the new resampling method and the classical time sampled data are compared and the advantages of using the system developed in this work are highlighted.
ISBN: 9783030683795$q(electronic bk.)
Standard No.: 10.1007/978-3-030-68379-5doiSubjects--Topical Terms:
895268
Cryptocurrencies
--Statistical methods.
LC Class. No.: HG1710.3
Dewey Class. No.: 332.63
Financial data resampling for machine learning based tradingapplication to cryptocurrency markets /
LDR
:01853nmm a2200325 a 4500
001
600639
003
DE-He213
005
20210616152705.0
006
m d
007
cr nn 008maaau
008
211104s2021 sz s 0 eng d
020
$a
9783030683795$q(electronic bk.)
020
$a
9783030683788$q(paper)
024
7
$a
10.1007/978-3-030-68379-5
$2
doi
035
$a
978-3-030-68379-5
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
HG1710.3
072
7
$a
PBKS
$2
bicssc
072
7
$a
MAT006000
$2
bisacsh
072
7
$a
PBKS
$2
thema
082
0 4
$a
332.63
$2
23
090
$a
HG1710.3
$b
.B732 2021
100
1
$a
Borges, Tome Almeida.
$3
895267
245
1 0
$a
Financial data resampling for machine learning based trading
$h
[electronic resource] :
$b
application to cryptocurrency markets /
$c
by Tome Almeida Borges, Rui Neves.
260
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2021.
300
$a
xv, 93 p. :
$b
ill., digital ;
$c
24 cm.
490
1
$a
SpringerBriefs in applied sciences and technology, Computational intelligence
520
$a
This book presents a system that combines the expertise of four algorithms, namely Gradient Tree Boosting, Logistic Regression, Random Forest and Support Vector Classifier to trade with several cryptocurrencies. A new method for resampling financial data is presented as alternative to the classical time sampled data commonly used in financial market trading. The new resampling method uses a closing value threshold to resample the data creating a signal better suited for financial trading, thus achieving higher returns without increased risk. The performance of the algorithm with the new resampling method and the classical time sampled data are compared and the advantages of using the system developed in this work are highlighted.
650
0
$a
Cryptocurrencies
$x
Statistical methods.
$3
895268
650
0
$a
Investments
$x
Statistical methods.
$3
863709
650
0
$a
Resampling (Statistics)
$3
185434
650
1 4
$a
Computational Mathematics and Numerical Analysis.
$3
274020
700
1
$a
Neves, Rui.
$3
806504
710
2
$a
SpringerLink (Online service)
$3
273601
773
0
$t
Springer Nature eBook
830
0
$a
SpringerBriefs in applied sciences and technology.
$p
Computational intelligence.
$3
674590
856
4 0
$u
https://doi.org/10.1007/978-3-030-68379-5
950
$a
Mathematics and Statistics (SpringerNature-11649)
based on 0 review(s)
ALL
電子館藏
Items
1 records • Pages 1 •
1
Inventory Number
Location Name
Item Class
Material type
Call number
Usage Class
Loan Status
No. of reservations
Opac note
Attachments
000000199173
電子館藏
1圖書
電子書
EB HG1710.3 .B732 2021 2021
一般使用(Normal)
On shelf
0
1 records • Pages 1 •
1
Multimedia
Multimedia file
https://doi.org/10.1007/978-3-030-68379-5
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login