Fumio Ishizaki
Modal Stage
Fumio Ishizaki received B. Eng., M. Eng., and Dr. Eng. from Kyoto University, Kyoto, Japan, in 1990, 1992 and 1996, respectively. From April 1993 to September 1995, he was an Assistant Professor in the Department of Electronic Engineering at Kinki University, Higashiosaka, Japan. From October 1995 to March 2000, he was an Assistant Professor in the Department of Information Science and Intelligent Systems at the University of Tokushima, Tokushima, Japan. From May 1998 to October 1998, he was a Visiting Researcher in the Department of Information and Computer Science, University of California, Irvine, CA, USA. From April 2000 to February 2005, he was an Associate Professor in the Department of Information and Telecommunication Engineering at Nanzan University, Seto, Japan. From August 2001 to July 2002, he was an Invited Member of Engineering Staff at the Electronics and Telecommunication Research Institute (ETRI), Daejeon, Korea. From January 2005 to December 2006, he was a Visiting Associate Professor in the Department of Mathematics and Telecommunication Mathematics Research Center at Korea University, Seoul, Korea. From January 2007 to March 2008, he was an Associate Professor in the Department of Information and Telecommunication Engineering at Nanzan University, Seto, Japan. From April 2008 to March 2009, he was a Professor in the Department of Information and Telecommunication Engineering at Nanzan University, Seto, Japan. From April 2009 to March 2013, he was a Professor in the Department of Systems Design and Engineering at Nanzan University, Seto, Japan. Since January 2017, he has been working at Modal Stage.
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Articles by Fumio Ishizaki
Formulations to select assets for constructing sparse index tracking portfolios
The authors put forward methods to chose assets for sparse index tracking portfolios and demonstrate the tracking performance with numerical examples.
Correlation diversified passive portfolio strategy based on permutation of assets
This paper proposes a new idea to determine the adjustment weight vector in order to construct a passive portfolio with lower risk than the risk of the benchmark index.