- 學位論文
股市波動性與熊市：以美國產業為例
Stock Market Volatility and Bear Stock Market: American Industries
摘要
本論文主要探討美國產業之股市波動性能否預測未來股市發生熊市。以五大產業類股作為研究對象，利用 Pagan & Sossounov (2003) 的無母數方法來建構熊市序列，並透過 realized volatility 來衡量股市的波動性，且基於牛、熊市序列為雙元變數，因此採用Probit 模型對未來熊市的發生機率進行預測。除應用單一變數探討股市波動性與熊市之間的關係外，本研究亦加入了不同時間區段的子樣本分析、其他預測模型、納入其他控制變數以及比較市場波動性的強韌性檢測。研究結果顯示，波動性對未來發生熊市之可能性具有預測力 (predictive power) ，美國產業類股波動性預測其未來可能發生熊市有正相關，並且預測短期未來之發生機率最為顯著。
並列摘要
This paper mainly explores whether the stock market volatility of the US industries can predict their future bear market. Taking the five major industrial stocks as the research object, the bear market sequence is constructed by non-parametric approach of Pagan & Sossounov (2003), and the stock market volatility is measured by realized volatility. Based on the bull and bear market sequences as binary variables, we used the Probit model to predict the bear market in the future. In addition to using a single variable to explore the relationship between stock market volatility and bear markets, this paper also incorporates subsamples of different time periods analysis, other predictive models, and stock market volatility to test the robustness. The research results show that stock market volatility has predictive power on the possibility of a bear market in the future. The volatility of US industrial stocks is positively correlated with the possibility of a bear market in the future, and the probability of occurrence in the short-term future is the most significant.