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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/72920
標題: | 機器學習在商業週期的分類與預測之應用 Applications of Machine Learning in Classifying and Forecasting Business Cycles |
作者: | Scott Schwartz 天空 |
指導教授: | 楊曙榮(Sunny Yang) |
關鍵字: | 機器學習,商業週期,景氣衰退,預測,分類, Machine Learning,Forecasting,Recession,Business Cycle,Prediction,Classification, |
出版年 : | 2019 |
學位: | 碩士 |
摘要: | The term “recession”is not only a sensitive topic to the workers, investors, and businesses that suffer immense loss during this time, but also economists whom continually struggle to predict them. Through the rise of Big Data, Machine Learning potentially gives statisticians and economists alike a new tool for predicting recessions. In order to explore this field, this paper asks two fundamental questions:
• Does machine learning help classify and forecast recessions within the business cycle? • Which models are most effective in predicting and classifying recessions? Applying the most common machine learning classification algorithms, we perform out-of-sample performance evaluations using a self-selected sample of macroeconomic indicators. Our findings imply that Random Forest, KNN, and Support Vector Machine models best classify and predict recessions. The analysis results suggest that machine learning has incredible potential in improving prediction accuracy. However, we believe these models can be further developed through additional research and application within the Deep Learning field of machine learning. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/72920 |
DOI: | 10.6342/NTU201901681 |
全文授權: | 有償授權 |
顯示於系所單位: | 管理學院企業管理專班(Global MBA) |
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