Taiwan Stock Market Intraday Trading Strategy Using Random Forest Time Series Model
碩士 === 輔仁大學 === 統計資訊學系應用統計碩士班 === 104 === This study applies Random Forest model to predict the price of Taiwan listed shares and its return rate. This study use the informations of institutional investors and index of main countries as daily data, and use technical indicators、futures index、exchan...
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ndltd-TW-104FJU005060082017-07-30T04:40:56Z http://ndltd.ncl.edu.tw/handle/41448732017556051010 Taiwan Stock Market Intraday Trading Strategy Using Random Forest Time Series Model 以隨機森林時間序列模型為基礎之台灣上市股市即時交易策略之研究 LI,PEI-YING 李佩螢 碩士 輔仁大學 統計資訊學系應用統計碩士班 104 This study applies Random Forest model to predict the price of Taiwan listed shares and its return rate. This study use the informations of institutional investors and index of main countries as daily data, and use technical indicators、futures index、exchange rate、informations of Taiwan listed shares and index of Asia countries as intraday data. We integrate all variables through Random Forest method then generate a model and trading strategy. Final, let the study’s strategy and buy & hold strategy be compared. This study choose TSMC(2330)、LARGAN(3008)、ECLAT(1476) from Taiwan Top50 index to do backtesting. The empirical interval is from May 25, 2016 to June 3, 2016 with 8 trading days, 728 data. The empirical result shows that the model can fully learn with 1 or 2 days training data, and the input variable which highly influences the result is relationship between price and volume. Also, no matter what type of the stock price in empirical period is, the random forest model can predict the rising and falling section effectively. HUANG,HSIAO-YUN 黃孝雲 2016 學位論文 ; thesis 57 zh-TW |
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碩士 === 輔仁大學 === 統計資訊學系應用統計碩士班 === 104 === This study applies Random Forest model to predict the price of Taiwan listed shares and its return rate. This study use the informations of institutional investors and index of main countries as daily data, and use technical indicators、futures index、exchange rate、informations of Taiwan listed shares and index of Asia countries as intraday data. We integrate all variables through Random Forest method then generate a model and trading strategy. Final, let the study’s strategy and buy & hold strategy be compared.
This study choose TSMC(2330)、LARGAN(3008)、ECLAT(1476) from Taiwan Top50 index to do backtesting. The empirical interval is from May 25, 2016 to June 3, 2016 with 8 trading days, 728 data. The empirical result shows that the model can fully learn with 1 or 2 days training data, and the input variable which highly influences the result is relationship between price and volume. Also, no matter what type of the stock price in empirical period is, the random forest model can predict the rising and falling section effectively.
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HUANG,HSIAO-YUN |
author_facet |
HUANG,HSIAO-YUN LI,PEI-YING 李佩螢 |
author |
LI,PEI-YING 李佩螢 |
spellingShingle |
LI,PEI-YING 李佩螢 Taiwan Stock Market Intraday Trading Strategy Using Random Forest Time Series Model |
author_sort |
LI,PEI-YING |
title |
Taiwan Stock Market Intraday Trading Strategy Using Random Forest Time Series Model |
title_short |
Taiwan Stock Market Intraday Trading Strategy Using Random Forest Time Series Model |
title_full |
Taiwan Stock Market Intraday Trading Strategy Using Random Forest Time Series Model |
title_fullStr |
Taiwan Stock Market Intraday Trading Strategy Using Random Forest Time Series Model |
title_full_unstemmed |
Taiwan Stock Market Intraday Trading Strategy Using Random Forest Time Series Model |
title_sort |
taiwan stock market intraday trading strategy using random forest time series model |
publishDate |
2016 |
url |
http://ndltd.ncl.edu.tw/handle/41448732017556051010 |
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