Chii-Ruey Hwang

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We seek a global minimum of U:[0, 1]"-. R. The solution to (d/dt)x,=-VU(xt) will find local minima. The solution to dxt =-V U(xt) dt + dw,, where w is standard (n-dimensional) Brownian motion and the boundaries are reflecting, will concentrate near the global minima of U, at least when "temperature" T is small: the equilibrium distribution for xt is Gibbs(More)
Starting from a robust, nonparametric definition of large returns ("excursions"), we study the statistics of their occurrences, focusing on the recurrence process. The empirical waiting-time distribution between excursions is remarkably invariant to year, stock, and scale (return interval). This invariance is related to self-similarity of the marginal(More)
Statistical analysis based on two characteristics of a small-world network, and on Lempel-Ziv's measure of Kolmogorov-Chaitin's algorithmic complexity are first proposed to scan through an individual behavioral sequence for possible existence of non-stationarity. Due to fixed window width, these tests have drawbacks in mapping out regions of(More)
High-frequency return, trading volume and transaction number are digitally coded via a nonparametric computing algorithm, called hierarchical factor segmentation (HFS), and then are coupled together to reveal a single stock dynamics without global state-space structural assumptions. The base-8 digital coding sequence, which is capable of revealing(More)
Many kernel-based learning algorithms have the computational load scaled with the sample size n due to the column size of a full kernel Gram matrix K. This article considers the Nyström low-rank approximation. It uses a reduced kernel í µí±² ̂ , which is n×m, consisting of m columns (say columns i1, i2,···, im) randomly drawn from K. This approximation(More)
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