Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12540/487
Title: Multiple regression model: the contribution of high-tech industries to the STAR Market
Authors: Wang, Zhen 
Issue Date: 2020
Source: Wang, Zhen. (2020). Multiple regression model: the contribution of high-tech industries to the STAR Market [Unpublished bachelor's thesis]. Wenzhou-Kean University.
Abstract: Quantitative research on the new-born stock market is necessary for further investing activities. The speech of Xi Jinping at the first China International Import Expo (CIIE) announced the hatch of the Sci-Tech Innovation Board (STAR Market), a brand-new secondary stock market in the Shanghai Stock Exchange (SSE). The STAR Market began trading on July 19th, 2019 and created a significant success in China. The STAR Market merely serves for high-tech related firms and is impacted by the nature of technology-related issues, high volatility. Through the Paasche weight price method, it is found that the volatility in the STAR Market is much more violent than that in the whole SSE. It reveals that STAR Market indeed benefits from tech-related industries, but the separate amount of their influences is uncertain and has not been quantized. This research aims to vary, quantize these impacts and find out the most significant industry. It is expected that the performance of the STAR Market highly relies on the performances of different high-tech industries. Through multiple regression modeling, the output supports the assumption and successfully quantize those contributions. It is also found that "IT, Software related industry", which has the largest number of firms, does not has a dominating impact on the changes of STAR performance; "Telecom, PC related industry" is proved to have the most significant influence to the STAR Market.
URI: https://hdl.handle.net/20.500.12540/487
Appears in Collections:Theses and Dissertations

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