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You searched for +publisher:"NSYSU" +contributor:("Gow-Liang Huang"). Showing records 1 – 2 of 2 total matches.

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NSYSU

1. Lin, Chin-Yuan. Risk-return in the banking industry using quantile regression: Evidence from cross-straits banking industry.

Degree: PhD, Finance, 2013, NSYSU

The enigma of risk-return relationships has long posed problems in the field of banking research. This study employed data related to cross-strait banking to investigate the risk-return relationship between 2005 and 2011.Traditional OLS optimization techniques capture only central behaviors, and misidentify the relationship between bank risk and profitability, including the amount, significance, and even sign; therefore, this study departs from conventional research in the modeling of parameters related to risk-return regression and proposes a novel, conditional quantile regression method (hereafter QR), to survey the dynamics of the relationship between risk and return among banks in Taiwan, Hong Kong, and China. This study employed ROE as a proxy variable for bank returns, using loan/total assets (LO) as a proxy variable for bank risk. Risk-return relationships for banks were analyzed using OLS regression and QR. The study period covered the period of the subprime lending crisis; therefore, data was categorized into two groups: a pre-subprime crisis group and a post-subprime crisis group. Data was also classified into three groups according to LO level: low LO group, middle LO group and high LO group. This enabled the effects of the subprime crisis and the impact of risk exposure to be clearly differentiated. Analysis of OLS regression demonstrated that risk and return among banks in Taiwan were negatively related over the entire study period, the pre-subprime crisis group, the low and the middle LO group. This means that increasing the risk assumed by banks would result in reduced profits for these banks. In addition, our empirical findings demonstrate that the risk-return relationship varied across the quantiles of bank profitability in the three LO ranges, both before and after the subprime crisis. Furthermore, variations in profitability were often the result of the business strategies employed. This indicates that grouping banks with different business strategies to facilitate analysis disregards the impact of business strategy on returns and may be one of the reasons for previous inconsistencies in empirical results. While OLS regression results showed a positive risk-return relationship associated with banks in China and Hong Kong, QR results indicate a positive risk-return relationship in all quantile groups, with the exception of banks of Hong Kong in the upper-quantile of the middle LO group and in the lower-quantile of the high LO group. These results support the theory of a positive risk-return relationship; however, it deviates from the negative risk-return relationship observed in Taiwanese banks. In a comparison of loan quality between banks in Taiwan and those in Hong Kong, based on BDTI-LO relationships we discovered that the negative risk-return relationship in Taiwan could be attributed to poor loan quality. Thus, despite efforts of the banking industry in Taiwan to increase the loan ratio for higher ROE, the widespread issue of poor loan quality remains. If loan quality cannot be improved, the… Advisors/Committee Members: Gow-Liang Huang (chair), Chia-Chien Chang (chair), Hsiou-Jen Kuo (committee member), So-De Shyu (committee member), Roger C. Y. Chen (chair).

Subjects/Keywords: Risk-return relationship; Loan quality; Risk of banks; Return of banks; Quantile regression

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APA (6th Edition):

Lin, C. (2013). Risk-return in the banking industry using quantile regression: Evidence from cross-straits banking industry. (Doctoral Dissertation). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0613113-113330

Chicago Manual of Style (16th Edition):

Lin, Chin-Yuan. “Risk-return in the banking industry using quantile regression: Evidence from cross-straits banking industry.” 2013. Doctoral Dissertation, NSYSU. Accessed January 18, 2020. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0613113-113330.

MLA Handbook (7th Edition):

Lin, Chin-Yuan. “Risk-return in the banking industry using quantile regression: Evidence from cross-straits banking industry.” 2013. Web. 18 Jan 2020.

Vancouver:

Lin C. Risk-return in the banking industry using quantile regression: Evidence from cross-straits banking industry. [Internet] [Doctoral dissertation]. NSYSU; 2013. [cited 2020 Jan 18]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0613113-113330.

Council of Science Editors:

Lin C. Risk-return in the banking industry using quantile regression: Evidence from cross-straits banking industry. [Doctoral Dissertation]. NSYSU; 2013. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0613113-113330


NSYSU

2. Huang, Tzu-lun. Web Search Behavior of Individual Investors and Trading Activities in Capital Markets.

Degree: PhD, Finance, 2013, NSYSU

Investors nowadays can utilize search engines to collect information from the Internet before trading. Using Google Search Volume Index as a proxy, this study aims to elucidate the link between the web search behavior of investors and trading activities in the capital market. Our findings indicate that firms in portfolios with more Google search volume possess higher stock returns and Jensen's alpha. Abnormal increases in Google search volume can predict higher future stock returns. Rises in Google search volume are positively associated with trading volumes by individual investors, margin purchase, and day trading. Overall, these findings imply that market administrators can predict trading activities of individual investors by observing changes in Google search volume. Moreover, the mediation analysis indicates that the Internet and financial media probably capture investor attention from different groups. They both significantly affect stock returns, but their impacts appear to be weak and insignificant during financial crises. Advisors/Committee Members: Miao-Ling Chen (committee member), Jen-Sin Lee (chair), Hsiou-jen Kuo (committee member), Chang-Chiang Chin (chair), Gow-Liang Huang (chair).

Subjects/Keywords: Media Coverage; Asset Pricing; Investor Attention; Google Search Volume Index; Web Search Behavior

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Huang, T. (2013). Web Search Behavior of Individual Investors and Trading Activities in Capital Markets. (Doctoral Dissertation). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1118113-154531

Chicago Manual of Style (16th Edition):

Huang, Tzu-lun. “Web Search Behavior of Individual Investors and Trading Activities in Capital Markets.” 2013. Doctoral Dissertation, NSYSU. Accessed January 18, 2020. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1118113-154531.

MLA Handbook (7th Edition):

Huang, Tzu-lun. “Web Search Behavior of Individual Investors and Trading Activities in Capital Markets.” 2013. Web. 18 Jan 2020.

Vancouver:

Huang T. Web Search Behavior of Individual Investors and Trading Activities in Capital Markets. [Internet] [Doctoral dissertation]. NSYSU; 2013. [cited 2020 Jan 18]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1118113-154531.

Council of Science Editors:

Huang T. Web Search Behavior of Individual Investors and Trading Activities in Capital Markets. [Doctoral Dissertation]. NSYSU; 2013. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1118113-154531

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