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| Paper Abstract and Keywords | ||
| Presentation | 2019-05-11 10:50 On Generation of Pseudo Exchange Rate Using Generative Adversarial Networks Koki Nakane, Hiroki Takada, Takayuki Hirata (Fukui Univ.)  NLP2019-13 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In this day and age, it is not necessary to have technical knowledge for the investment since the automatic algorithms to sell/buy investment destination have been developed with artificial intelligence (AI). However, these kinds of mechanical trading systems may not support variations realized in future because the systems were developed with use of time series data of the investment outlets in the past, or time sequences generated by stochastic processes to verify the systems. Therefore, we considered applying the generative adversarial network (GAN), which has attracted attention in the field of image generation, to time series of the exchange rate. Learning the properties of variations in the exchange rate whose factors are not elucidated in detail by GAN, the pseudo exchange rates were generated to use as the data for verification of the mechanical trading system. In this study, measuring similarity (stationarity, fractality, and degree of determinism) of variations in the exchange rates to the pseudo-exchange rates generated by GANs, we compared Winner processes with the GANs. From the viewpoint of stationarity, the similarity of sequences in the pseudo exchange rates were higher than those generated by the Winner processes, and high scores in the similarity were resulted from both sequences in terms of degree of determinism. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | GAN / Exchange rate / Double-Wayland algorithm / Stochastic process / Hurst index / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 119, no. 19, NLP2019-13, pp. 71-76, May 2019. | |
| Paper # | NLP2019-13 | |
| Date of Issue | 2019-05-03 (NLP) | |
| ISSN | Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 | |
| Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) | |
| Download PDF | NLP2019-13 |
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| Conference Information | |
| Committee | NLP |
| Conference Date | 2019-05-10 - 2019-05-11 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | J:COM HoltoHALL OITA |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | etc. |
| Paper Information | |
| Registration To | NLP |
| Conference Code | 2019-05-NLP |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | On Generation of Pseudo Exchange Rate Using Generative Adversarial Networks |
| Sub Title (in English) | |
| Keyword(1) | GAN |
| Keyword(2) | Exchange rate |
| Keyword(3) | Double-Wayland algorithm |
| Keyword(4) | Stochastic process |
| Keyword(5) | Hurst index |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Koki Nakane |
| 1st Author's Affiliation | University of Fukui (Fukui Univ.) |
| 2nd Author's Name | Hiroki Takada |
| 2nd Author's Affiliation | University of Fukui (Fukui Univ.) |
| 3rd Author's Name | Takayuki Hirata |
| 3rd Author's Affiliation | University of Fukui (Fukui Univ.) |
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| Speaker | Author-1 |
| Date Time | 2019-05-11 10:50:00 |
| Presentation Time | 25 minutes |
| Registration for | NLP |
| Paper # | NLP2019-13 |
| Volume (vol) | vol.119 |
| Number (no) | no.19 |
| Page | pp.71-76 |
| #Pages | 6 |
| Date of Issue | 2019-05-03 (NLP) |
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