Foreign exchange rate forecasting with artificial neural networks:
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
New York, NY
Springer
2007
|
| Schriftenreihe: | International series in operations research & management science
107 |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis Klappentext |
| Beschreibung: | Literaturverz. S. [291] - 310 |
| Beschreibung: | XXIII, 313 S. Ill., graph. Darst. 235 mm x 155 mm |
| ISBN: | 9780387717197 0387717196 |
Internformat
MARC
| LEADER | 00000nam a2200000 cb4500 | ||
|---|---|---|---|
| 001 | BV023081145 | ||
| 003 | DE-604 | ||
| 005 | 20081204 | ||
| 007 | t | ||
| 008 | 080115s2007 gw ad|| |||| 00||| eng d | ||
| 015 | |a 07,N15,0990 |2 dnb | ||
| 016 | 7 | |a 983522952 |2 DE-101 | |
| 020 | |a 9780387717197 |c Gb. : ca. EUR 99.46 (freier Pr.), ca. sfr 152.50 (freier Pr.) |9 978-0-387-71719-7 | ||
| 020 | |a 0387717196 |c Gb. : ca. EUR 99.46 (freier Pr.), ca. sfr 152.50 (freier Pr.) |9 0-387-71719-6 | ||
| 024 | 3 | |a 9780387717197 | |
| 028 | 5 | 2 | |a 11923282 |
| 035 | |a (OCoLC)154711864 | ||
| 035 | |a (DE-599)DNB983522952 | ||
| 040 | |a DE-604 |b ger |e rakddb | ||
| 041 | 0 | |a eng | |
| 044 | |a gw |c XA-DE-BE | ||
| 049 | |a DE-355 |a DE-521 |a DE-M347 | ||
| 050 | 0 | |a HG3821 | |
| 082 | 0 | |a 332.456 | |
| 084 | |a QM 331 |0 (DE-625)141778: |2 rvk | ||
| 084 | |a 650 |2 sdnb | ||
| 100 | 1 | |a Yu, Lean |e Verfasser |0 (DE-588)133837610 |4 aut | |
| 245 | 1 | 0 | |a Foreign exchange rate forecasting with artificial neural networks |c Lean Yu, Shouyang Wang and Kin Keung Lai |
| 246 | 1 | 3 | |a Foreign-exchange-rate forecasting with artificial neural networks |
| 264 | 1 | |a New York, NY |b Springer |c 2007 | |
| 300 | |a XXIII, 313 S. |b Ill., graph. Darst. |c 235 mm x 155 mm | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 1 | |a International series in operations research & management science |v 107 | |
| 500 | |a Literaturverz. S. [291] - 310 | ||
| 650 | 7 | |a Kunstmatige intelligentie |2 gtt | |
| 650 | 7 | |a Neurale netwerken |2 gtt | |
| 650 | 7 | |a Prognoses |2 gtt | |
| 650 | 7 | |a Wisselkoersen |2 gtt | |
| 650 | 4 | |a Foreign exchange rates |x Forecasting | |
| 650 | 4 | |a Neural networks (Computer science) | |
| 650 | 0 | 7 | |a Wechselkursänderung |0 (DE-588)4129405-1 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Prognoseverfahren |0 (DE-588)4358095-6 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Neuronales Netz |0 (DE-588)4226127-2 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Operations Research |0 (DE-588)4043586-6 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a Wechselkursänderung |0 (DE-588)4129405-1 |D s |
| 689 | 0 | 1 | |a Operations Research |0 (DE-588)4043586-6 |D s |
| 689 | 0 | 2 | |a Neuronales Netz |0 (DE-588)4226127-2 |D s |
| 689 | 0 | 3 | |a Prognoseverfahren |0 (DE-588)4358095-6 |D s |
| 689 | 0 | |5 DE-604 | |
| 700 | 1 | |a Wang, Shouyang |d 1958- |e Verfasser |0 (DE-588)123314542 |4 aut | |
| 700 | 1 | |a Lai, Kin Keung |d 1950- |e Verfasser |0 (DE-588)131350609 |4 aut | |
| 830 | 0 | |a International series in operations research & management science |v 107 |w (DE-604)BV011630976 |9 107 | |
| 856 | 4 | 2 | |m Digitalisierung UB Regensburg |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016284164&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
| 856 | 4 | 2 | |m Digitalisierung UB Regensburg |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016284164&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |3 Klappentext |
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-016284164 | |
Datensatz im Suchindex
| _version_ | 1807957699326902272 |
|---|---|
| adam_text |
Table
of
Contents
Preface
.xi
Biographies
of Three Authors of the Book
.xv
List of Figures
.xvii
List of Tables
.xxi
Part I: Forecasting Foreign Exchange Rates with Artificial
Neural Networks: An Analytical Survey
.1
1
Are Foreign Exchange Rates Predictable?
—
A Literature
Review from Artificial Neural Networks Perspective
.3
1.1
Introduction
.3
1.2
Literature Collection
.5
1.3
Analytical Results and Factor Investigation
.7
1.3.1
Basic Classifications and Factors Summarization
.7
1.3.2
Factor Analysis
.8
1.4
Implications and Research Topics
.21
1.5
Conclusions
.23
Part II: Basic Learning Principles of Artificial Neural
Networks and Data Preparation
.25
2
Basic Learning Principles of Artificial Neural Networks
.27
2.1
Introduction
.27
2.2
Basic Structure of the BPNN Model
.28
2.3
Learning Process of the BPNN Algorithm
.30
2.4
Weight Update Formulae of the BPNN Algorithm
.31
2.5
Conclusions
.37
3
Data Preparation in Neural Network Data Analysis
.39
3.1
Introduction
.39
3.2
Neural Network for Data Analysis
.42
vi
Table of Contents
3.3
An Integrated Data Preparation Scheme
.44
3.3.1
Integrated Data Preparation Scheme for Neural Network
Data Analysis
.44
3.3.2
Data Pre-Analysis Phase
.46
3.3.3
Data Preprocessing Phase
.51
3.3.4
Data Post-Analysis Phase
.56
3.4
Costs-Benefits Analysis of the Integrated Scheme
.59
3.5
Conclusions
.61
Part III: Individual Neural Network Models with Optimal
Learning Rates and Adaptive Momentum
Factors for Foreign Exchange Rates Prediction
.63
4
Forecasting Foreign Exchange Rates Using
an Adaptive Back-Propagation Algorithm with Optimal
Learning Rates and Momentum Factors
.65
4.1
Introduction
.65
4.2
BP Algorithm with Optimal Learning Rates
and Momentum Factors
.68
4.2.1
Optimal Learning Rates Determination
.68
4.2.2
Determination of Optimal Momentum Factors
.76
4.3
Experiment Study
.78
4.3.1
Data Description and Experiment Design
.78
4.3.2
Experimental Results
.80
4.4
Concluding Remarks
.84
5
An Online BP Learning Algorithm with Adaptive Forgetting
Factors for Foreign Exchange Rates Forecasting
.87
5.1
Introduction
.87
5.2
An Online BP Learning Algorithm with Adaptive Forgetting Factors
.88
5.3
Experimental Analysis
.94
5.3.1
Data Description and Experiment Design
.94
5.3.2
Experimental Results
.96
5.4
Conclusions
.99
6
An Improved BP Algorithm with Adaptive Smoothing
Momentum Terms for Foreign Exchange Rates Prediction
.101
6.1
Introduction
.101
Table
of
Contents
vii
6.2
Formulation
of the Improved
BP
Algorithm
.103
6.2.1
Determination of Adaptive Smoothing Momentum
.103
6.2.2
Formulation of the Improved BPNN Algorithm
.106
6.3
Empirical Study
.108
6.3.1
Data Description and Experiment Design
.109
6.3.2
Forecasting Results and Comparisons
.109
6.3.3
Comparisons of Different Learning Rates
.112
6.3.4
Comparisons with Different Momentum Factors
.113
6.3.5
Comparisons with Different Error Propagation Methods
.114
6.3.6
Comparisons with Different Numbers of Hidden Neurons
.115
6.3.7
Comparisons with Different Hidden Activation Functions
.116
6.4
Comparisons of Three Single Neural Network Models
.117
6.5
Conclusions
.117
Part IV: Hybridizing ANN with Other Forecasting
Techniques for Foreign Exchange Rates
Forecasting
.119
7
Hybridizing BPNN and Exponential Smoothing for Foreign
Exchange Rate Prediction
.121
7.1
Introduction
.121
7.2
Basic Backgrounds
.123
7.2.1
Exponential Smoothing Forecasting Model
.123
7.2.2
Neural Network Forecasting Model
.125
7.3
A Hybrid Model Integrating BPNN and Exponential Smoothing
.127
7.4
Experiments
.129
7.5
Conclusions
.130
8
A Nonlinear Combined Model Hybridizing ANN and GLAR
for Exchange Rates Forecasting
---------------------------------------------133
8.1
Introduction
.133
8.2
Model Building Processes
.136
8.2.1
Generalized Linear Auto-Regression (GLAR) Model
.136
8.2.2
Artificial Neural Network (ANN) Model
.138
8.2.3
A Hybrid Model Integrating GLAR with ANN
.139
8.2.4
Combined Forecasting Models
.141
viii Table of
Contents
8.2.5
A Nonlinear Combined
(NC)
Forecasting
Model
.142
8.2.6
Forecasting Evaluation Criteria
.145
8.3
Empirical Analysis
.148
8.3.1
Data Description
.148
8.3.2
Empirical Results
.148
8.4
Conclusions
.153
9
A Hybrid GA-Based SVM Model for Foreign Exchange
Market Tendency Exploration
.155
9.1
Introduction
.155
9.2
Formulation of the Hybrid GA-SVM Model
.158
9.2.1
Basic Theory of SVM
.158
9.2.2
Feature Selection with GA for SVM Modeling
.160
9.2.3
A Hybrid GASVM Model
.164
9.3
Empirical Study
.165
9.3.1
Research Data
.165
9.3.2
Descriptions of Other Comparable Forecasting Models
.167
9.3.3
Experiment Results
.168
9.4
Comparisons of Three Hybrid Neural Network Models
.172
9.5
Conclusions
.173
Part V: Neural Network Ensemble for Foreign Exchange
Rates Forecasting
.175
10
Forecasting Foreign Exchange Rates with a Multistage Neural
Network Ensemble Model
.177
10.1
Introduction
.177
10.2
Motivations for Neural Network Ensemble Model
.179
10.3
Formulation of Neural Network Ensemble Model
.181
10.3.1
Framework of Multistage Neural Ensemble Model
.181
10.3.2
Preprocessing Original Data
.182
10.3.3
Generating Individual Neural Predictors
.185
10.3.4
Selecting Appropriate Ensemble Members
.187
10.3.5
Ensembling the Selecting Members
.192
10.4
Empirical Analysis
.196
10.4.1
Experimental Data and Evaluation Criterion
.196
10.4.2
Experiment Design
.196
Table
of
Contents
ix
10.4.3
Experiment Results and Comparisons
.198
10.5
Conclusions
.201
11
Neural Networks Meta-Learning for Foreign Exchange Rate
Ensemble Forecasting
.203
11.1
Introduction
.203
11.2
Introduction of Neural Network Learning Paradigm
.204
11.3
Neural Network Meta-Learning Process for Ensemble
.206
11.3.1
Basic Background of Meta-Learning
.206
11.3.2
Data Sampling
.207
11.3.3
Individual Neural Network Base Model Creation
.209
11.3.4
Neural Network Base Model Pruning
.210
11.3.5
Neural-Network-Based Meta-Model Generation
.212
11.4
Empirical Study
.213
11.4.1
Research Data and Experiment Design
.213
11.4.2
Experiment Results
.215
11.5
Conclusions
.216
12
Predicting Foreign Exchange Market Movement Direction
Using a Confidence-Based Neural Network Ensemble Model
.217
12.1
Introduction
.217
12.2
Formulation of Neural Network Ensemble Model
.219
12.2.1
Partitioning Original Data Set
.220
12.2.2
Creating Individual Neural Network Classifiers
.221
12.2.3
BP Network Learning and Confidence Value Generation
.222
12.2.4
Confidence Value Transformation
.223
12.2.5
Integrating Multiple Classifiers into an Ensemble Output
.223
12.3
Empirical Study
.226
12.4
Comparisons of Three Ensemble Neural Networks
.230
12.5
Conclusions
.230
13
Foreign Exchange Rates Forecasting with Multiple Candidate
Models: Selecting or Combining? A Further Discussion
.233
13.1
Introduction
.233
13.2
Two Dilemmas and Their Solutions
.237
13.3
Empirical Analysis
.242
13.4
Conclusions and Future Directions
.244
χ
Table of Contents
Part VI: Developing an Intelligent Foreign Exchange
Rates Forecasting and Trading Decision
Support System
.247
14
Developing an Intelligent Forex Rolling Forecasting
and Trading Decision Support System I: Conceptual
Framework, Modeling Techniques and System
Implementations
.249
14.1
Introduction
.249
14.2
System Framework and Main Functions
.250
14.3
Modeling Approach and Quantitative Measurements
.252
14.3.1
BPNN-Based Forex Rolling Forecasting Sub-System
.253
14.3.2
Web-Based Forex Trading Decision Support System
.263
14.4
Development and Implementation of FRFTDSS
.269
14.4.1
Development of the FRFTDSS
.269
14.4.2
Implementation of the FRFTDSS
.270
14.5
Conclusions
.274
15
Developing an Intelligent Forex Rolling Forecasting
and Trading Decision Support System II: An Empirical
and Comprehensive Assessment
.275
15.1
Introduction
.275
15.2
Empirical Assessment on Performance of FRFTDSS
.276
15.2.1
Parametric Evaluation Methods
.276
15.2.2
Nonparametric Evaluation Methods
.278
15.3
Performance Comparisons with Classical Models
.280
15.3.1
Selection for Comparable Classical Models
.280
15.3.2
Performance Comparison Results with Classical Models
.280
15.4
Performance Comparisons with Other Systems
.281
15.4.1
Searching for Existing Forex Forecasting Systems
.281
15.4.2
Performance Comparisons with Other Existing Systems
.283
15.4.3
A Comprehensive Comparison Analysis
.285
15.5
Discussions and Conclusions
.288
References
.291
Subject Index
_311
International Series in Operations Research
&
Management Science ISOR
107
LeanYu
ShouyangWang
Kin Keung Lai
Foreign-Exchange-Rate Forecasting with Artificial Neural Networks
The book focuses on forecasting foreign exchange rates \ria artificial neural networks.
It creates and applies the highly useful computational techniques of Artificial Neural
Networks (ANNs) to foreign-exchange-rate forecasting. The result is an up-to-date review
of the most recent research developments in forecasting foreign exchange rates coupled
with a highly useful methodological approach to predicting rate changes in foreign
currency exchanges. Foreign-Exchange-Rate Forecasting with Artificial Neural Networks
is targeted at both the academic and practitioner audiences. Managers, analysts and
technical practitioners in financial institutions across the world will have considerable
interest in the book, and scholars and graduate students studying financial markets and
business forecast will also have considerable interest in the book. |
| adam_txt |
Table
of
Contents
Preface
.xi
Biographies
of Three Authors of the Book
.xv
List of Figures
.xvii
List of Tables
.xxi
Part I: Forecasting Foreign Exchange Rates with Artificial
Neural Networks: An Analytical Survey
.1
1
Are Foreign Exchange Rates Predictable?
—
A Literature
Review from Artificial Neural Networks Perspective
.3
1.1
Introduction
.3
1.2
Literature Collection
.5
1.3
Analytical Results and Factor Investigation
.7
1.3.1
Basic Classifications and Factors Summarization
.7
1.3.2
Factor Analysis
.8
1.4
Implications and Research Topics
.21
1.5
Conclusions
.23
Part II: Basic Learning Principles of Artificial Neural
Networks and Data Preparation
.25
2
Basic Learning Principles of Artificial Neural Networks
.27
2.1
Introduction
.27
2.2
Basic Structure of the BPNN Model
.28
2.3
Learning Process of the BPNN Algorithm
.30
2.4
Weight Update Formulae of the BPNN Algorithm
.31
2.5
Conclusions
.37
3
Data Preparation in Neural Network Data Analysis
.39
3.1
Introduction
.39
3.2
Neural Network for Data Analysis
.42
vi
Table of Contents
3.3
An Integrated Data Preparation Scheme
.44
3.3.1
Integrated Data Preparation Scheme for Neural Network
Data Analysis
.44
3.3.2
Data Pre-Analysis Phase
.46
3.3.3
Data Preprocessing Phase
.51
3.3.4
Data Post-Analysis Phase
.56
3.4
Costs-Benefits Analysis of the Integrated Scheme
.59
3.5
Conclusions
.61
Part III: Individual Neural Network Models with Optimal
Learning Rates and Adaptive Momentum
Factors for Foreign Exchange Rates Prediction
.63
4
Forecasting Foreign Exchange Rates Using
an Adaptive Back-Propagation Algorithm with Optimal
Learning Rates and Momentum Factors
.65
4.1
Introduction
.65
4.2
BP Algorithm with Optimal Learning Rates
and Momentum Factors
.68
4.2.1
Optimal Learning Rates Determination
.68
4.2.2
Determination of Optimal Momentum Factors
.76
4.3
Experiment Study
.78
4.3.1
Data Description and Experiment Design
.78
4.3.2
Experimental Results
.80
4.4
Concluding Remarks
.84
5
An Online BP Learning Algorithm with Adaptive Forgetting
Factors for Foreign Exchange Rates Forecasting
.87
5.1
Introduction
.87
5.2
An Online BP Learning Algorithm with Adaptive Forgetting Factors
.88
5.3
Experimental Analysis
.94
5.3.1
Data Description and Experiment Design
.94
5.3.2
Experimental Results
.96
5.4
Conclusions
.99
6
An Improved BP Algorithm with Adaptive Smoothing
Momentum Terms for Foreign Exchange Rates Prediction
.101
6.1
Introduction
.101
Table
of
Contents
vii
6.2
Formulation
of the Improved
BP
Algorithm
.103
6.2.1
Determination of Adaptive Smoothing Momentum
.103
6.2.2
Formulation of the Improved BPNN Algorithm
.106
6.3
Empirical Study
.108
6.3.1
Data Description and Experiment Design
.109
6.3.2
Forecasting Results and Comparisons
.109
6.3.3
Comparisons of Different Learning Rates
.112
6.3.4
Comparisons with Different Momentum Factors
.113
6.3.5
Comparisons with Different Error Propagation Methods
.114
6.3.6
Comparisons with Different Numbers of Hidden Neurons
.115
6.3.7
Comparisons with Different Hidden Activation Functions
.116
6.4
Comparisons of Three Single Neural Network Models
.117
6.5
Conclusions
.117
Part IV: Hybridizing ANN with Other Forecasting
Techniques for Foreign Exchange Rates
Forecasting
.119
7
Hybridizing BPNN and Exponential Smoothing for Foreign
Exchange Rate Prediction
.121
7.1
Introduction
.121
7.2
Basic Backgrounds
.123
7.2.1
Exponential Smoothing Forecasting Model
.123
7.2.2
Neural Network Forecasting Model
.125
7.3
A Hybrid Model Integrating BPNN and Exponential Smoothing
.127
7.4
Experiments
.129
7.5
Conclusions
.130
8
A Nonlinear Combined Model Hybridizing ANN and GLAR
for Exchange Rates Forecasting
---------------------------------------------133
8.1
Introduction
.133
8.2
Model Building Processes
.136
8.2.1
Generalized Linear Auto-Regression (GLAR) Model
.136
8.2.2
Artificial Neural Network (ANN) Model
.138
8.2.3
A Hybrid Model Integrating GLAR with ANN
.139
8.2.4
Combined Forecasting Models
.141
viii Table of
Contents
8.2.5
A Nonlinear Combined
(NC)
Forecasting
Model
.142
8.2.6
Forecasting Evaluation Criteria
.145
8.3
Empirical Analysis
.148
8.3.1
Data Description
.148
8.3.2
Empirical Results
.148
8.4
Conclusions
.153
9
A Hybrid GA-Based SVM Model for Foreign Exchange
Market Tendency Exploration
.155
9.1
Introduction
.155
9.2
Formulation of the Hybrid GA-SVM Model
.158
9.2.1
Basic Theory of SVM
.158
9.2.2
Feature Selection with GA for SVM Modeling
.160
9.2.3
A Hybrid GASVM Model
.164
9.3
Empirical Study
.165
9.3.1
Research Data
.165
9.3.2
Descriptions of Other Comparable Forecasting Models
.167
9.3.3
Experiment Results
.168
9.4
Comparisons of Three Hybrid Neural Network Models
.172
9.5
Conclusions
.173
Part V: Neural Network Ensemble for Foreign Exchange
Rates Forecasting
.175
10
Forecasting Foreign Exchange Rates with a Multistage Neural
Network Ensemble Model
.177
10.1
Introduction
.177
10.2
Motivations for Neural Network Ensemble Model
.179
10.3
Formulation of Neural Network Ensemble Model
.181
10.3.1
Framework of Multistage Neural Ensemble Model
.181
10.3.2
Preprocessing Original Data
.182
10.3.3
Generating Individual Neural Predictors
.185
10.3.4
Selecting Appropriate Ensemble Members
.187
10.3.5
Ensembling the Selecting Members
.192
10.4
Empirical Analysis
.196
10.4.1
Experimental Data and Evaluation Criterion
.196
10.4.2
Experiment Design
.196
Table
of
Contents
ix
10.4.3
Experiment Results and Comparisons
.198
10.5
Conclusions
.201
11
Neural Networks Meta-Learning for Foreign Exchange Rate
Ensemble Forecasting
.203
11.1
Introduction
.203
11.2
Introduction of Neural Network Learning Paradigm
.204
11.3
Neural Network Meta-Learning Process for Ensemble
.206
11.3.1
Basic Background of Meta-Learning
.206
11.3.2
Data Sampling
.207
11.3.3
Individual Neural Network Base Model Creation
.209
11.3.4
Neural Network Base Model Pruning
.210
11.3.5
Neural-Network-Based Meta-Model Generation
.212
11.4
Empirical Study
.213
11.4.1
Research Data and Experiment Design
.213
11.4.2
Experiment Results
.215
11.5
Conclusions
.216
12
Predicting Foreign Exchange Market Movement Direction
Using a Confidence-Based Neural Network Ensemble Model
.217
12.1
Introduction
.217
12.2
Formulation of Neural Network Ensemble Model
.219
12.2.1
Partitioning Original Data Set
.220
12.2.2
Creating Individual Neural Network Classifiers
.221
12.2.3
BP Network Learning and Confidence Value Generation
.222
12.2.4
Confidence Value Transformation
.223
12.2.5
Integrating Multiple Classifiers into an Ensemble Output
.223
12.3
Empirical Study
.226
12.4
Comparisons of Three Ensemble Neural Networks
.230
12.5
Conclusions
.230
13
Foreign Exchange Rates Forecasting with Multiple Candidate
Models: Selecting or Combining? A Further Discussion
.233
13.1
Introduction
.233
13.2
Two Dilemmas and Their Solutions
.237
13.3
Empirical Analysis
.242
13.4
Conclusions and Future Directions
.244
χ
Table of Contents
Part VI: Developing an Intelligent Foreign Exchange
Rates Forecasting and Trading Decision
Support System
.247
14
Developing an Intelligent Forex Rolling Forecasting
and Trading Decision Support System I: Conceptual
Framework, Modeling Techniques and System
Implementations
.249
14.1
Introduction
.249
14.2
System Framework and Main Functions
.250
14.3
Modeling Approach and Quantitative Measurements
.252
14.3.1
BPNN-Based Forex Rolling Forecasting Sub-System
.253
14.3.2
Web-Based Forex Trading Decision Support System
.263
14.4
Development and Implementation of FRFTDSS
.269
14.4.1
Development of the FRFTDSS
.269
14.4.2
Implementation of the FRFTDSS
.270
14.5
Conclusions
.274
15
Developing an Intelligent Forex Rolling Forecasting
and Trading Decision Support System II: An Empirical
and Comprehensive Assessment
.275
15.1
Introduction
.275
15.2
Empirical Assessment on Performance of FRFTDSS
.276
15.2.1
Parametric Evaluation Methods
.276
15.2.2
Nonparametric Evaluation Methods
.278
15.3
Performance Comparisons with Classical Models
.280
15.3.1
Selection for Comparable Classical Models
.280
15.3.2
Performance Comparison Results with Classical Models
.280
15.4
Performance Comparisons with Other Systems
.281
15.4.1
Searching for Existing Forex Forecasting Systems
.281
15.4.2
Performance Comparisons with Other Existing Systems
.283
15.4.3
A Comprehensive Comparison Analysis
.285
15.5
Discussions and Conclusions
.288
References
.291
Subject Index
_311
International Series in Operations Research
&
Management Science ISOR
107
LeanYu
ShouyangWang
Kin Keung Lai
Foreign-Exchange-Rate Forecasting with Artificial Neural Networks
The book focuses on forecasting foreign exchange rates \ria artificial neural networks.
It creates and applies the highly useful computational techniques of Artificial Neural
Networks (ANNs) to foreign-exchange-rate forecasting. The result is an up-to-date review
of the most recent research developments in forecasting foreign exchange rates coupled
with a highly useful methodological approach to predicting rate changes in foreign
currency exchanges. Foreign-Exchange-Rate Forecasting with Artificial Neural Networks
is targeted at both the academic and practitioner audiences. Managers, analysts and
technical practitioners in financial institutions across the world will have considerable
interest in the book, and scholars and graduate students studying financial markets and
business forecast will also have considerable interest in the book. |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author | Yu, Lean Wang, Shouyang 1958- Lai, Kin Keung 1950- |
| author_GND | (DE-588)133837610 (DE-588)123314542 (DE-588)131350609 |
| author_facet | Yu, Lean Wang, Shouyang 1958- Lai, Kin Keung 1950- |
| author_role | aut aut aut |
| author_sort | Yu, Lean |
| author_variant | l y ly s w sw k k l kk kkl |
| building | Verbundindex |
| bvnumber | BV023081145 |
| callnumber-first | H - Social Science |
| callnumber-label | HG3821 |
| callnumber-raw | HG3821 |
| callnumber-search | HG3821 |
| callnumber-sort | HG 43821 |
| callnumber-subject | HG - Finance |
| classification_rvk | QM 331 |
| ctrlnum | (OCoLC)154711864 (DE-599)DNB983522952 |
| dewey-full | 332.456 |
| dewey-hundreds | 300 - Social sciences |
| dewey-ones | 332 - Financial economics |
| dewey-raw | 332.456 |
| dewey-search | 332.456 |
| dewey-sort | 3332.456 |
| dewey-tens | 330 - Economics |
| discipline | Wirtschaftswissenschaften |
| discipline_str_mv | Wirtschaftswissenschaften |
| format | Book |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>00000nam a2200000 cb4500</leader><controlfield tag="001">BV023081145</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20081204</controlfield><controlfield tag="007">t</controlfield><controlfield tag="008">080115s2007 gw ad|| |||| 00||| eng d</controlfield><datafield tag="015" ind1=" " ind2=" "><subfield code="a">07,N15,0990</subfield><subfield code="2">dnb</subfield></datafield><datafield tag="016" ind1="7" ind2=" "><subfield code="a">983522952</subfield><subfield code="2">DE-101</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9780387717197</subfield><subfield code="c">Gb. : ca. EUR 99.46 (freier Pr.), ca. sfr 152.50 (freier Pr.)</subfield><subfield code="9">978-0-387-71719-7</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">0387717196</subfield><subfield code="c">Gb. : ca. EUR 99.46 (freier Pr.), ca. sfr 152.50 (freier Pr.)</subfield><subfield code="9">0-387-71719-6</subfield></datafield><datafield tag="024" ind1="3" ind2=" "><subfield code="a">9780387717197</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">11923282</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)154711864</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DNB983522952</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rakddb</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="044" ind1=" " ind2=" "><subfield code="a">gw</subfield><subfield code="c">XA-DE-BE</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-355</subfield><subfield code="a">DE-521</subfield><subfield code="a">DE-M347</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">HG3821</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">332.456</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">QM 331</subfield><subfield code="0">(DE-625)141778:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">650</subfield><subfield code="2">sdnb</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Yu, Lean</subfield><subfield code="e">Verfasser</subfield><subfield code="0">(DE-588)133837610</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Foreign exchange rate forecasting with artificial neural networks</subfield><subfield code="c">Lean Yu, Shouyang Wang and Kin Keung Lai</subfield></datafield><datafield tag="246" ind1="1" ind2="3"><subfield code="a">Foreign-exchange-rate forecasting with artificial neural networks</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">New York, NY</subfield><subfield code="b">Springer</subfield><subfield code="c">2007</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">XXIII, 313 S.</subfield><subfield code="b">Ill., graph. Darst.</subfield><subfield code="c">235 mm x 155 mm</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="1" ind2=" "><subfield code="a">International series in operations research & management science</subfield><subfield code="v">107</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Literaturverz. S. [291] - 310</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Kunstmatige intelligentie</subfield><subfield code="2">gtt</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Neurale netwerken</subfield><subfield code="2">gtt</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Prognoses</subfield><subfield code="2">gtt</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Wisselkoersen</subfield><subfield code="2">gtt</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Foreign exchange rates</subfield><subfield code="x">Forecasting</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Neural networks (Computer science)</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Wechselkursänderung</subfield><subfield code="0">(DE-588)4129405-1</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Prognoseverfahren</subfield><subfield code="0">(DE-588)4358095-6</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Neuronales Netz</subfield><subfield code="0">(DE-588)4226127-2</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Operations Research</subfield><subfield code="0">(DE-588)4043586-6</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Wechselkursänderung</subfield><subfield code="0">(DE-588)4129405-1</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="1"><subfield code="a">Operations Research</subfield><subfield code="0">(DE-588)4043586-6</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="2"><subfield code="a">Neuronales Netz</subfield><subfield code="0">(DE-588)4226127-2</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="3"><subfield code="a">Prognoseverfahren</subfield><subfield code="0">(DE-588)4358095-6</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="5">DE-604</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wang, Shouyang</subfield><subfield code="d">1958-</subfield><subfield code="e">Verfasser</subfield><subfield code="0">(DE-588)123314542</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lai, Kin Keung</subfield><subfield code="d">1950-</subfield><subfield code="e">Verfasser</subfield><subfield code="0">(DE-588)131350609</subfield><subfield code="4">aut</subfield></datafield><datafield tag="830" ind1=" " ind2="0"><subfield code="a">International series in operations research & management science</subfield><subfield code="v">107</subfield><subfield code="w">(DE-604)BV011630976</subfield><subfield code="9">107</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="m">Digitalisierung UB Regensburg</subfield><subfield code="q">application/pdf</subfield><subfield code="u">http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016284164&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA</subfield><subfield code="3">Inhaltsverzeichnis</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="m">Digitalisierung UB Regensburg</subfield><subfield code="q">application/pdf</subfield><subfield code="u">http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016284164&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA</subfield><subfield code="3">Klappentext</subfield></datafield><datafield tag="943" ind1="1" ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-016284164</subfield></datafield></record></collection> |
| id | DE-604.BV023081145 |
| illustrated | Illustrated |
| index_date | 2024-07-02T19:37:10Z |
| indexdate | 2024-08-21T01:13:42Z |
| institution | BVB |
| isbn | 9780387717197 0387717196 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-016284164 |
| oclc_num | 154711864 |
| open_access_boolean | |
| owner | DE-355 DE-BY-UBR DE-521 DE-M347 |
| owner_facet | DE-355 DE-BY-UBR DE-521 DE-M347 |
| physical | XXIII, 313 S. Ill., graph. Darst. 235 mm x 155 mm |
| publishDate | 2007 |
| publishDateSearch | 2007 |
| publishDateSort | 2007 |
| publisher | Springer |
| record_format | marc |
| series | International series in operations research & management science |
| series2 | International series in operations research & management science |
| spelling | Yu, Lean Verfasser (DE-588)133837610 aut Foreign exchange rate forecasting with artificial neural networks Lean Yu, Shouyang Wang and Kin Keung Lai Foreign-exchange-rate forecasting with artificial neural networks New York, NY Springer 2007 XXIII, 313 S. Ill., graph. Darst. 235 mm x 155 mm txt rdacontent n rdamedia nc rdacarrier International series in operations research & management science 107 Literaturverz. S. [291] - 310 Kunstmatige intelligentie gtt Neurale netwerken gtt Prognoses gtt Wisselkoersen gtt Foreign exchange rates Forecasting Neural networks (Computer science) Wechselkursänderung (DE-588)4129405-1 gnd rswk-swf Prognoseverfahren (DE-588)4358095-6 gnd rswk-swf Neuronales Netz (DE-588)4226127-2 gnd rswk-swf Operations Research (DE-588)4043586-6 gnd rswk-swf Wechselkursänderung (DE-588)4129405-1 s Operations Research (DE-588)4043586-6 s Neuronales Netz (DE-588)4226127-2 s Prognoseverfahren (DE-588)4358095-6 s DE-604 Wang, Shouyang 1958- Verfasser (DE-588)123314542 aut Lai, Kin Keung 1950- Verfasser (DE-588)131350609 aut International series in operations research & management science 107 (DE-604)BV011630976 107 Digitalisierung UB Regensburg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016284164&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Regensburg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016284164&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Klappentext |
| spellingShingle | Yu, Lean Wang, Shouyang 1958- Lai, Kin Keung 1950- Foreign exchange rate forecasting with artificial neural networks International series in operations research & management science Kunstmatige intelligentie gtt Neurale netwerken gtt Prognoses gtt Wisselkoersen gtt Foreign exchange rates Forecasting Neural networks (Computer science) Wechselkursänderung (DE-588)4129405-1 gnd Prognoseverfahren (DE-588)4358095-6 gnd Neuronales Netz (DE-588)4226127-2 gnd Operations Research (DE-588)4043586-6 gnd |
| subject_GND | (DE-588)4129405-1 (DE-588)4358095-6 (DE-588)4226127-2 (DE-588)4043586-6 |
| title | Foreign exchange rate forecasting with artificial neural networks |
| title_alt | Foreign-exchange-rate forecasting with artificial neural networks |
| title_auth | Foreign exchange rate forecasting with artificial neural networks |
| title_exact_search | Foreign exchange rate forecasting with artificial neural networks |
| title_exact_search_txtP | Foreign exchange rate forecasting with artificial neural networks |
| title_full | Foreign exchange rate forecasting with artificial neural networks Lean Yu, Shouyang Wang and Kin Keung Lai |
| title_fullStr | Foreign exchange rate forecasting with artificial neural networks Lean Yu, Shouyang Wang and Kin Keung Lai |
| title_full_unstemmed | Foreign exchange rate forecasting with artificial neural networks Lean Yu, Shouyang Wang and Kin Keung Lai |
| title_short | Foreign exchange rate forecasting with artificial neural networks |
| title_sort | foreign exchange rate forecasting with artificial neural networks |
| topic | Kunstmatige intelligentie gtt Neurale netwerken gtt Prognoses gtt Wisselkoersen gtt Foreign exchange rates Forecasting Neural networks (Computer science) Wechselkursänderung (DE-588)4129405-1 gnd Prognoseverfahren (DE-588)4358095-6 gnd Neuronales Netz (DE-588)4226127-2 gnd Operations Research (DE-588)4043586-6 gnd |
| topic_facet | Kunstmatige intelligentie Neurale netwerken Prognoses Wisselkoersen Foreign exchange rates Forecasting Neural networks (Computer science) Wechselkursänderung Prognoseverfahren Neuronales Netz Operations Research |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016284164&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016284164&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV011630976 |
| work_keys_str_mv | AT yulean foreignexchangerateforecastingwithartificialneuralnetworks AT wangshouyang foreignexchangerateforecastingwithartificialneuralnetworks AT laikinkeung foreignexchangerateforecastingwithartificialneuralnetworks |