TY - GEN
T1 - Stock prices fluctuation analysis of food companies after the Great East-Japan Earthquake
T2 - 12th International Conference on Digital Information Management, ICDIM 2017
AU - Yamaguchi, Kenji
AU - Shirota, Yukari
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/6/28
Y1 - 2017/6/28
N2 - Just after the Great East-Japan Earthquake in Fukushima on March 11th, 2011, in many Japanese companies, stock prices were declining. However, on the other hand, some companies' stock prices rose owing to the emergency demands of the earthquake. When we have been conducting the stock price fluctuations, we found the special pattern of a growth by the emergency demand of food companies. The companies are Otsuka Holdings, Toyo Suisan, and Nisshin Food Holdings. The companies produce emergency food such as pot noodles and CalorieMate. We infer that the rapid growth of the demand for the emergency food let the stock price risen. We analyze the stock prices using the Random Matrix Theory. The main part of the method is Singular Value Decomposition. We extract eigenvectors which are principle components of the time series data. In our analysis method, first we start at the landmark company and then using the company we in turn find other companies which have similar movement to the start company. In this paper, we shall describe the extracting approach of the special growth companies.
AB - Just after the Great East-Japan Earthquake in Fukushima on March 11th, 2011, in many Japanese companies, stock prices were declining. However, on the other hand, some companies' stock prices rose owing to the emergency demands of the earthquake. When we have been conducting the stock price fluctuations, we found the special pattern of a growth by the emergency demand of food companies. The companies are Otsuka Holdings, Toyo Suisan, and Nisshin Food Holdings. The companies produce emergency food such as pot noodles and CalorieMate. We infer that the rapid growth of the demand for the emergency food let the stock price risen. We analyze the stock prices using the Random Matrix Theory. The main part of the method is Singular Value Decomposition. We extract eigenvectors which are principle components of the time series data. In our analysis method, first we start at the landmark company and then using the company we in turn find other companies which have similar movement to the start company. In this paper, we shall describe the extracting approach of the special growth companies.
KW - emergency demand
KW - emergency food
KW - Great East-Japan Earthquake
KW - Random Matrix Theory
KW - Singular Value Decomposition
KW - stock data analysis
UR - http://www.scopus.com/inward/record.url?scp=85049374861&partnerID=8YFLogxK
U2 - 10.1109/ICDIM.2017.8244659
DO - 10.1109/ICDIM.2017.8244659
M3 - Conference contribution
AN - SCOPUS:85049374861
T3 - 2017 12th International Conference on Digital Information Management, ICDIM 2017
SP - 65
EP - 69
BT - 2017 12th International Conference on Digital Information Management, ICDIM 2017
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 12 September 2017 through 14 September 2017
ER -