Forecasting TAIWAN Stock Markets with Technical Indicators: A Comparison between Neural Network Model and Multiple Regression Model
碩士 === 國立臺灣大學 === 資訊管理研究所 === 84 === With the progress of information technology, it is more and more popular to use IT in the real life. This study is to forecast TAIWAN stock market. Two methods are used in this study; one is back-propagation neural net...
Main Authors: | , |
---|---|
Other Authors: | |
Format: | Others |
Language: | zh-TW |
Published: |
1996
|
Online Access: | http://ndltd.ncl.edu.tw/handle/18057332331002908481 |
id |
ndltd-TW-084NTU00396003 |
---|---|
record_format |
oai_dc |
spelling |
ndltd-TW-084NTU003960032016-07-13T04:10:50Z http://ndltd.ncl.edu.tw/handle/18057332331002908481 Forecasting TAIWAN Stock Markets with Technical Indicators: A Comparison between Neural Network Model and Multiple Regression Model 以技術指標預測台灣股市股價漲跌之實證研究--以類神經網路與複迴歸模式建構 Wang,Chun-Sheng 王春笙 碩士 國立臺灣大學 資訊管理研究所 84 With the progress of information technology, it is more and more popular to use IT in the real life. This study is to forecast TAIWAN stock market. Two methods are used in this study; one is back-propagation neural network, the other is statistical multiple regression. In addition, two decision support systems are also designed to trade stocks automatically. There are 18 companies sampled in this study. Ten out of 32 technical indicators are selected. These 10 indicators are fixed inputs of all neural network and statistical models. Each method has three kinds of models. One is to forecast the fluctuation of stock prices in 6 days, one is to forecast the fluctuation in 12 days, and the last is to forecast the fluctuation in 18 days. Using these models, this study computes the accuracy rate of forecasting and performance of trading simulation. Results reveal that one can forecast TAIWAN stock prices with certain accuracy. Back-propagation is better than multiple regression which is better than buy-and- hold strategy. The most profitable model in this study is to trade stock gradually by neural network model using the 18-days- later prices as target variables. Lee,Anthony J.T 李瑞庭 1996 學位論文 ; thesis 118 zh-TW |
collection |
NDLTD |
language |
zh-TW |
format |
Others
|
sources |
NDLTD |
description |
碩士 === 國立臺灣大學 === 資訊管理研究所 === 84 === With the progress of information technology, it is more and
more popular to use IT in the real life. This study is to
forecast TAIWAN stock market. Two methods are used in this
study; one is back-propagation neural network, the other is
statistical multiple regression. In addition, two decision
support systems are also designed to trade stocks
automatically. There are 18 companies sampled in this study.
Ten out of 32 technical indicators are selected. These 10
indicators are fixed inputs of all neural network and
statistical models. Each method has three kinds of models. One
is to forecast the fluctuation of stock prices in 6 days, one
is to forecast the fluctuation in 12 days, and the last is to
forecast the fluctuation in 18 days. Using these models, this
study computes the accuracy rate of forecasting and performance
of trading simulation. Results reveal that one can forecast
TAIWAN stock prices with certain accuracy. Back-propagation is
better than multiple regression which is better than buy-and-
hold strategy. The most profitable model in this study is to
trade stock gradually by neural network model using the 18-days-
later prices as target variables.
|
author2 |
Lee,Anthony J.T |
author_facet |
Lee,Anthony J.T Wang,Chun-Sheng 王春笙 |
author |
Wang,Chun-Sheng 王春笙 |
spellingShingle |
Wang,Chun-Sheng 王春笙 Forecasting TAIWAN Stock Markets with Technical Indicators: A Comparison between Neural Network Model and Multiple Regression Model |
author_sort |
Wang,Chun-Sheng |
title |
Forecasting TAIWAN Stock Markets with Technical Indicators: A Comparison between Neural Network Model and Multiple Regression Model |
title_short |
Forecasting TAIWAN Stock Markets with Technical Indicators: A Comparison between Neural Network Model and Multiple Regression Model |
title_full |
Forecasting TAIWAN Stock Markets with Technical Indicators: A Comparison between Neural Network Model and Multiple Regression Model |
title_fullStr |
Forecasting TAIWAN Stock Markets with Technical Indicators: A Comparison between Neural Network Model and Multiple Regression Model |
title_full_unstemmed |
Forecasting TAIWAN Stock Markets with Technical Indicators: A Comparison between Neural Network Model and Multiple Regression Model |
title_sort |
forecasting taiwan stock markets with technical indicators: a comparison between neural network model and multiple regression model |
publishDate |
1996 |
url |
http://ndltd.ncl.edu.tw/handle/18057332331002908481 |
work_keys_str_mv |
AT wangchunsheng forecastingtaiwanstockmarketswithtechnicalindicatorsacomparisonbetweenneuralnetworkmodelandmultipleregressionmodel AT wángchūnshēng forecastingtaiwanstockmarketswithtechnicalindicatorsacomparisonbetweenneuralnetworkmodelandmultipleregressionmodel AT wangchunsheng yǐjìshùzhǐbiāoyùcètáiwāngǔshìgǔjiàzhǎngdiēzhīshízhèngyánjiūyǐlèishénjīngwǎnglùyǔfùhuíguīmóshìjiàngòu AT wángchūnshēng yǐjìshùzhǐbiāoyùcètáiwāngǔshìgǔjiàzhǎngdiēzhīshízhèngyánjiūyǐlèishénjīngwǎnglùyǔfùhuíguīmóshìjiàngòu |
_version_ |
1718346093127794688 |