| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0311416 |
| utime |
20240103190348.9 |
| mtime |
20081008235959.9 |
| title
(primary) (eng) |
Wavelet Neural Networks Prediction of Central European Stock Markets |
| specification |
|
| serial |
| ARLID |
cav_un_epca*0311267 |
| ISBN |
978-80-8078-217-7 |
| title
|
Quantitative Methods in Economics: Multiple Criteria Decision making XIV |
| page_num |
291-297 |
| publisher |
| place |
Bratislava |
| name |
University of Economics in Bratislava |
| year |
2008 |
|
| editor |
|
|
| title
(cze) |
Vlnové neurálních sítě předvídající centrální evropský trh s cennými papíry |
| keyword |
neural networks |
| keyword |
hard threshold denoising |
| keyword |
wavelets |
| author
(primary) |
| ARLID |
cav_un_auth*0101217 |
| name1 |
Vácha |
| name2 |
Lukáš |
| institution |
UTIA-B |
| full_dept |
Department of Econometrics |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0242028 |
| name1 |
Baruník |
| name2 |
Jozef |
| institution |
UTIA-B |
| full_dept |
Department of Econometrics |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| cas_special |
| project |
| project_id |
GP402/08/P207 |
| agency |
GA ČR |
| ARLID |
cav_un_auth*0241655 |
|
| project |
| project_id |
GA402/06/1417 |
| agency |
GA ČR |
| country |
CZ |
| ARLID |
cav_un_auth*0213949 |
|
| research |
CEZ:AV0Z10750506 |
| abstract
(eng) |
In this paper we apply neural network with denoising layer method for forecasting of Central European Stock Exchanges, namely Prague, Budapest and Warsaw. Hard threshold denoising with Daubechies 6 wavelet filter and three level decomposition is used to denoise the stock index returns, and two-layer feed-forward neural network with Levenberg-Marquardt learning algorithm is used for modeling. The results show that wavelet network structure is able to approximate the underlying process of considered stock markets better that multilayered neural network architecture without using wavelets. Further on we discuss the impact of structural changes of the market on forecasting accuracy, and we find that for certain periods the one-step-ahead prediction accuracy of the direction of the stock index can reach 60% to 70%. |
| abstract
(cze) |
Vlnové neurálních sítě předvídající centrální evropský trh s cennými papíry |
| action |
| ARLID |
cav_un_auth*0241903 |
| name |
Quantitative Methods in Economics: Multiplie Criteria Decision Making XIV |
| place |
Tatranská Lomnica |
| dates |
05.07.2008-07.07.2008 |
| country |
SK |
|
| reportyear |
2009 |
| RIV |
AH |
| permalink |
http://hdl.handle.net/11104/0163034 |
| arlyear |
2008 |
| mrcbU63 |
cav_un_epca*0311267 Quantitative Methods in Economics: Multiple Criteria Decision making XIV 978-80-8078-217-7 291 297 Kvantitativní metody v ekonomii: Vícekriteriální rozhodování XIV Bratislava University of Economics in Bratislava 2008 |
| mrcbU67 |
Reiff Sladký 340 |
|