TY - JOUR
T1 - Cluster analysis for stable processes
AU - Watanabe, Tsutomu
AU - Shiraishi, Hiroshi
AU - Taniguchi, Masanobu
PY - 2010/1/1
Y1 - 2010/1/1
N2 - It is known that various financial time series, e.g., daily log returns on a share price, foreign exchange rates, excess bond returns, etc., exhibit heavy-tailed behavior. Recently, discriminant analysis has been applied to financial time series, such as, the problem of credit rating for companies. In this article, we investigate the problem of classifying an -stable linear process into one of two categories with indices 1 and 2, respectively. We propose some discriminant criteria. It is shown that our discriminant statistics are consistent. The misclassification probabilities are also evaluated under contiguous hypotheses. Some numerical studies for an (AR(1)) process are given.
AB - It is known that various financial time series, e.g., daily log returns on a share price, foreign exchange rates, excess bond returns, etc., exhibit heavy-tailed behavior. Recently, discriminant analysis has been applied to financial time series, such as, the problem of credit rating for companies. In this article, we investigate the problem of classifying an -stable linear process into one of two categories with indices 1 and 2, respectively. We propose some discriminant criteria. It is shown that our discriminant statistics are consistent. The misclassification probabilities are also evaluated under contiguous hypotheses. Some numerical studies for an (AR(1)) process are given.
KW - Discriminant analysis
KW - Functional limit theorem
KW - Integrated periodogram
KW - Linear process
KW - Stable process
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U2 - 10.1080/03610920802155460
DO - 10.1080/03610920802155460
M3 - Article
AN - SCOPUS:77951982042
VL - 39
SP - 1630
EP - 1642
JO - Communications in Statistics - Theory and Methods
JF - Communications in Statistics - Theory and Methods
SN - 0361-0926
IS - 8-9
ER -