網路評論應用於Black-Litterman模型之投資組合績效評估

在互聯網時代，人們習慣於在網路上留下自己對於事物的看法，並與別人討論分享，而這些評論和分享中隱藏的一些重要資訊往往被人忽視，如人們對個股的留言中所隱含的關於股票走勢預測的資訊。本研究希望對這些個股留言資訊加以整理和分析，並以此作為投資者的觀點，從而放進Black-Litterman模型來建構投資組合。本研究發現在選定的股票組合中，用網路評論為觀點依據的Black-Litterman模型的優化配置的歷史績效較市場配置佳，雖在統計上無達到顯著水準，但也顯示了網路評論隱含著對股價有價值的訊息。

關鍵字

Black-Litterman 模型；網路評論

並列摘要

Recent advances in information technology have provided the ability for everyone to leave comments on the internet as well as to easily share their opinions with each other. In addition, those comments are hidden with information regarding trend of stocks. Nevertheless, they are usually ignored by people. This research tried to utilize these online reviews as investor views of the Black-Litterman Model to build a portfolio. The results showed that the return of selected portfolio from online reviews to the Black-Litterman model was higher than before using online review adjustment. Even though the results were not statistically significant, this indicates that online reviews include a considerable amount of value for stock prices.

並列關鍵字

Black-Litterman Model ； Online reviews

參考文獻

[1]Fama, E. F. (1970), Efficient Capital Markets: A Review of Theory and Empirical Work, Journal of Finance, 25, 383-417.

Google Scholar

[2]Han Zhuolin, Qiao Yuanbo, Shao Xiaoyan(2018), The Asset Allocation of “Shanghai-Shenzhen-HK Stock-Connect Fund Based on Black - Litterman Model. Review of Investment Studies, Issuue4, 2018 Pages 125-139

Google Scholar

[3]Harry Markowitz (1952), Portfolio Selection. The Journal of Finance, Vol. 7, No. 1, pp. 77-91

Google Scholar

[4]Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova(2018). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Google Scholar

[5]Johan Bollen, Huina Mao, Xiaojun Zeng(2011). Twitter mood predicts the stock market. Journal of Computational Science Volume 2, Issue 1, March 2011, Pages 1-8

Google Scholar

國際替代計量

網路評論應用於Black-Litterman模型之投資組合績效評估

未授權

主題瀏覽