High frequency dynamics of order flow

In this paper, we focus on the high frequency dynamics of limit order flow and market order flow. We compared the fitting performance of different models for the inter-arrival time of the order flow, including exponential distribution, gamma distribution and power law. We then studied the dependence of the placement of these two order flows, which can be captured by the self-excitation effect and mutual-excitation effect of Hawkes process. We also introduced a new model which combines the Hawkes features with the gamma distribution.\ud \ud Key words: High frequency dynamics; order flow; market microstructure; maximum likelihood estimation; Hawkes process; Hawkes-Gamma distribution

Novel characterization method of impedance cardiography signals using time-frequency distributions

The purpose of this document is to describe a methodology to select the most adequate time-frequency distribution (TFD) kernel for the characterization of impedance cardiography signals (ICG). The predominant ICG beat was extracted from a patient and was synthetized using time-frequency variant Fourier approximations. These synthetized signals were used to optimize several TFD kernels according to a performance maximization. The optimized kernels were tested for noise resistance on a clinical database. The resulting optimized TFD kernels are presented with their performance calculated using newly proposed methods. The procedure explained in this work showcases a new method to select an appropriate kernel for ICG signals and compares the performance of different time-frequency kernels found in the literature for the case of ICG signals. We conclude that, for ICG signals, the performance (P) of the spectrogram with either Hanning or Hamming windows (P¿=¿0.780) and the extended modified beta distribution (P¿=¿0.765) provided similar results, higher than the rest of analyzed kernels.Peer ReviewedPostprint (published version

Optical Phase-Space-Time-Frequency Tomography

We present a new approach for constructing optical phase-space-time-frequency tomography (OPSTFT) of an optical wave field. This tomography can be measured by using a novel four-window optical imaging system based on two local oscillator fields balanced heterodyne detection. The OPSTFT is a Wigner distribution function of two independent Fourier Transform pairs, i.e., phase-space and time-frequency. From its theoretical and experimental aspects, it can provide information of position, momentum, time and frequency of a spatial light field with precision beyond the uncertainty principle. We simulate the OPSTFT for a light field obscured by a wire and a single-line absorption filter. We believe that the four-window system can provide spatial and temporal properties of a wave field for quantum image processing and biophotonics.Comment: 11 pages, 6 figure