Application of Convolutional Neural Network and Long Short-Term Memory to Forex Analysis

碩士 === 國立東華大學 === 資訊工程學系 === 106 === FX market has tens of thousands of transactions every day. This paper hopes to find regularities in the FX market via machine learning. This paper uses deep learning Convolutional Neural Network ( CNN ) and Long Short-Term Memory ( LSTM ) models for FX analysis....

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Main Authors:	Kuo-Chan Huang, 黃國展
Other Authors:	Shi-Jim Yen
Format:	Others
Language:	zh-TW
Published:	2018
Online Access:	http://ndltd.ncl.edu.tw/handle/wx566h

id	ndltd-TW-106NDHU5392018
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spelling	ndltd-TW-106NDHU53920182019-05-16T01:07:40Z http://ndltd.ncl.edu.tw/handle/wx566h Application of Convolutional Neural Network and Long Short-Term Memory to Forex Analysis 卷積神經網路及長短期記憶模型應用於外匯分析 Kuo-Chan Huang 黃國展碩士國立東華大學資訊工程學系 106 FX market has tens of thousands of transactions every day. This paper hopes to find regularities in the FX market via machine learning. This paper uses deep learning Convolutional Neural Network ( CNN ) and Long Short-Term Memory ( LSTM ) models for FX analysis. This paper establishes the CNN and the LSTM model to forecast, and the two cooperate with each other and set the trading conditions. The experimental use of the sample period USD/JPY from January 10, 2005 to March 30, 2018, and from January 2, 2018 to March 30, 2018, the results which can earn profit in the FX. Shi-Jim Yen 顏士淨 2018 學位論文 ; thesis 33 zh-TW
collection	NDLTD
language	zh-TW
format	Others
sources	NDLTD
description	碩士 === 國立東華大學 === 資訊工程學系 === 106 === FX market has tens of thousands of transactions every day. This paper hopes to find regularities in the FX market via machine learning. This paper uses deep learning Convolutional Neural Network ( CNN ) and Long Short-Term Memory ( LSTM ) models for FX analysis. This paper establishes the CNN and the LSTM model to forecast, and the two cooperate with each other and set the trading conditions. The experimental use of the sample period USD/JPY from January 10, 2005 to March 30, 2018, and from January 2, 2018 to March 30, 2018, the results which can earn profit in the FX.
author2	Shi-Jim Yen
author_facet	Shi-Jim Yen Kuo-Chan Huang 黃國展
author	Kuo-Chan Huang 黃國展
spellingShingle	Kuo-Chan Huang 黃國展 Application of Convolutional Neural Network and Long Short-Term Memory to Forex Analysis
author_sort	Kuo-Chan Huang
title	Application of Convolutional Neural Network and Long Short-Term Memory to Forex Analysis
title_short	Application of Convolutional Neural Network and Long Short-Term Memory to Forex Analysis
title_full	Application of Convolutional Neural Network and Long Short-Term Memory to Forex Analysis
title_fullStr	Application of Convolutional Neural Network and Long Short-Term Memory to Forex Analysis
title_full_unstemmed	Application of Convolutional Neural Network and Long Short-Term Memory to Forex Analysis
title_sort	application of convolutional neural network and long short-term memory to forex analysis
publishDate	2018
url	http://ndltd.ncl.edu.tw/handle/wx566h
work_keys_str_mv	AT kuochanhuang applicationofconvolutionalneuralnetworkandlongshorttermmemorytoforexanalysis AT huángguózhǎn applicationofconvolutionalneuralnetworkandlongshorttermmemorytoforexanalysis AT kuochanhuang juǎnjīshénjīngwǎnglùjízhǎngduǎnqījìyìmóxíngyīngyòngyúwàihuìfēnxī AT huángguózhǎn juǎnjīshénjīngwǎnglùjízhǎngduǎnqījìyìmóxíngyīngyòngyúwàihuìfēnxī
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Application of Convolutional Neural Network and Long Short-Term Memory to Forex Analysis

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