Abstract
This paper applies fuzzy cluster analysis to investigate co movement of Asian and U.S. stock prices from the viewpoints of both region and industry. Specifically, we analyze daily stock price data of Chinese, Indian, Japanese, South Korean, and U.S. firms from 2005 through 2011. The past literature has never used daily data because of non-synchronous trading times and holidays, but we resolve this problem by analyzing American depositary receipts traded in the New York Stock Exchange instead of underlying shares traded all over the world. Partition trees computed each year provide overwhelming evidence that the country effect always surpasses the industry effect (i.e., shares from the same country tend to move together but shares within the same industry do not). This finding is particularly informative for portfolio managers, choosing a country and then many kinds of industry therein is a riskier strategy than choosing an industry and then many countries. Besides this practical implication, the dominant country effect highlights a slow process of globalization. Nationality of shares should not matter in a globalized world, but there still exist barriers segmenting countries. All these results and implications are robust to different clustering methods, the frequency of data, and foreign exchange rates.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 3rd International Conference on Innovations in Bio-Inspired Computing and Applications, IBICA 2012 |
| Pages | 34-38 |
| Number of pages | 5 |
| DOIs | |
| Publication status | Published - 2012 |
| Externally published | Yes |
| Event | 3rd International Conference on Innovations in Bio-Inspired Computing and Applications, IBICA 2012 - Kaohsiung City Duration: 2012 Sep 26 → 2012 Sep 28 |
Other
| Other | 3rd International Conference on Innovations in Bio-Inspired Computing and Applications, IBICA 2012 |
|---|---|
| City | Kaohsiung City |
| Period | 12/9/26 → 12/9/28 |
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Keywords
- Fuzzy Cluster Analysis
- Partition Tree
- Similarity Value
- Stock Price
- Ward's Method
- Zadeh's Method
ASJC Scopus subject areas
- Bioengineering
- Software
Cite this
Fuzzy cluster analysis and its application on international stock prices. / Motegi, Kaiji; Shinkai, Kimiaki; Uesu, Hiroaki; Kanagawa, Shuya; Chung, Hsunhsun; Nagashima, Kenichi.
Proceedings - 3rd International Conference on Innovations in Bio-Inspired Computing and Applications, IBICA 2012. 2012. p. 34-38 6337633.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Fuzzy cluster analysis and its application on international stock prices
AU - Motegi, Kaiji
AU - Shinkai, Kimiaki
AU - Uesu, Hiroaki
AU - Kanagawa, Shuya
AU - Chung, Hsunhsun
AU - Nagashima, Kenichi
PY - 2012
Y1 - 2012
N2 - This paper applies fuzzy cluster analysis to investigate co movement of Asian and U.S. stock prices from the viewpoints of both region and industry. Specifically, we analyze daily stock price data of Chinese, Indian, Japanese, South Korean, and U.S. firms from 2005 through 2011. The past literature has never used daily data because of non-synchronous trading times and holidays, but we resolve this problem by analyzing American depositary receipts traded in the New York Stock Exchange instead of underlying shares traded all over the world. Partition trees computed each year provide overwhelming evidence that the country effect always surpasses the industry effect (i.e., shares from the same country tend to move together but shares within the same industry do not). This finding is particularly informative for portfolio managers, choosing a country and then many kinds of industry therein is a riskier strategy than choosing an industry and then many countries. Besides this practical implication, the dominant country effect highlights a slow process of globalization. Nationality of shares should not matter in a globalized world, but there still exist barriers segmenting countries. All these results and implications are robust to different clustering methods, the frequency of data, and foreign exchange rates.
AB - This paper applies fuzzy cluster analysis to investigate co movement of Asian and U.S. stock prices from the viewpoints of both region and industry. Specifically, we analyze daily stock price data of Chinese, Indian, Japanese, South Korean, and U.S. firms from 2005 through 2011. The past literature has never used daily data because of non-synchronous trading times and holidays, but we resolve this problem by analyzing American depositary receipts traded in the New York Stock Exchange instead of underlying shares traded all over the world. Partition trees computed each year provide overwhelming evidence that the country effect always surpasses the industry effect (i.e., shares from the same country tend to move together but shares within the same industry do not). This finding is particularly informative for portfolio managers, choosing a country and then many kinds of industry therein is a riskier strategy than choosing an industry and then many countries. Besides this practical implication, the dominant country effect highlights a slow process of globalization. Nationality of shares should not matter in a globalized world, but there still exist barriers segmenting countries. All these results and implications are robust to different clustering methods, the frequency of data, and foreign exchange rates.
KW - Fuzzy Cluster Analysis
KW - Partition Tree
KW - Similarity Value
KW - Stock Price
KW - Ward's Method
KW - Zadeh's Method
UR - http://www.scopus.com/inward/record.url?scp=84870697655&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84870697655&partnerID=8YFLogxK
U2 - 10.1109/IBICA.2012.50
DO - 10.1109/IBICA.2012.50
M3 - Conference contribution
SP - 34
EP - 38
BT - Proceedings - 3rd International Conference on Innovations in Bio-Inspired Computing and Applications, IBICA 2012
ER -