Mieko Tanaka-Yamawaki

Learn More
We examine the effectiveness of frequently used technical indicators for intra-day forecast by applying them on the tick data of various stock prices. We show that the optimal combination of a few indicators chosen for each stock by using evolutional computation provides us a good forecast on the level of the future price at several ticks ahead. r 2007(More)
Abs t rac t . Contrary to the common sense in economics and financial engineering, price fluctuations at very fine level of motion exhibit various evidences against the efficient market hypothesis. We attempt to investigate this issue by studying extensive amount of foreign currency exchange data for over five years at the finest level of resolution. We(More)
We propose and apply a new algorithm of principal component analysis which is suitable for a large sized, highly random time series data, such as a set of stock prices in a stock market. This algorithm utilizes the fact that the major part of the time series is random, and compare the eigenvalue spectrum of cross correlation matrix of a large set of random(More)
Random matrix theory (RMT) derives, at the limit of both the dimension N and the length of sequences L going to infinity, that the eigenvalue distribution of the cross correlation matrix with high random nature can be expressed by one function of Q = L/N . Using this fact, we propose a new method of testing randomness of a given sequence. Namely, a sequence(More)