Multi-Fractal Spectral Analysis of the 1987 Stock Market Crash

The multifractal model of asset returns captures the volatility persistence of many financial time series. Its multifractal spectrum computed from wavelet modulus maxima lines provides the spectrum of irregularities in the distribution of market returns over time and thereby of the kind of uncertainty or randomness in a particular market. Changes in this multifractal spectrum display distinctive patterns around substantial market crashes or drawdowns. In other words, the kinds of singularities and the kinds of irregularity change in a distinct fashion in the periods immediately preceding and following major market drawdowns. This paper focuses on these identifiable multifractal spectral patterns surrounding the stock market crash of 1987. Although we are not able to find a uniquely identifiable irregularity pattern within the same market preceding different crashes at different times, we do find the same uniquely identifiable pattern in various stock markets experiencing the same crash at the same time. Moreover, our results suggest that all such crashes are preceded by a gradual increase in the weighted average of the values of the Lipschitz regularity exponents, under low dispersion of the multifractal spectrum. At a crash, this weighted average irregularity value drops to a much lower value, while the dispersion of the spectrum of Lipschitz exponents jumps up to a much higher level after the crash. Our most striking result, therefore, is that the multifractal spectra of stock market returns are not stationary. Also, while the stock market returns show a global Hurst exponent of slight persistence 0.5Financial Markets, Persistence, Multi-Fractal Spectral Analysis, Wavelets

Interoperability in the GENESIS 3.0 Software Federation : the NEURON Simulator as an Example

© 2013 Cornelis et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Poster presented at CNS 2013Non peer reviewe

Production of single-domain magnetite throughout life by sockeye salmon, Oncorhynchus nerka

Although single-domain particles of biogenic magnetite have been found in different species of pelagic fishes, nothing is known about when it is synthesized, or about whether the time during life when it is produced is correlated with the development of responses to magnetic field stimuli. We have investigated production of biogenic magnetite suitable for use in magnetoreception in different life stages of the sockeye salmon, Oncorhynchus nerka (Walbaum). Sockeye salmon were chosen because responses in orientation arenas to magnetic field stimuli have been demonstrated in both fry and smolt stages of this species. We found significant quantities of single-domain magnetite in connective tissue from the ethmoid region of the skull of adult (4-year-old) sockeye salmon. The ontogenetic study revealed an orderly increase in the amount of magnetic material in the same region of the skull but not in other tissues of sockeye salmon fry, yearlings and smolts. The physical properties of this material closely matched those of magnetite particles extracted from the ethmoid tissue of the adult fish. We suggest that single-domain magnetite particles suitable for use in magnetoreception are produced throughout life in the ethmoid region of the skull in sockeye salmon. Based on theoretical calculations, we conclude that there are enough particles present in the skulls of the fry to mediate their responses to magnetic field direction. By the smolt stage, the amount of magnetite present in the front of the skull is sufficient to provide the fish with a magnetoreceptor capable of detecting small changes in the intensity of the geomagnetic field. Other tissues of the salmon, such as the eye and skin, often contained ferromagnetic material, although the magnetizations of these tissues were usually more variable than in the ethmoid tissue. These deposits of unidentified magnetic material, some of which may be magnetite, appear almost exclusively in adults and so would not be useful in magnetoreception by young fish. We suggest that tissue from within the ethmoid region of the skull in pelagic fishes is the only site yet identified where magnetite suitable for use in magnetoreception is concentrated

Pricing options and computing implied volatilities using neural networks

This paper proposes a data-driven approach, by means of an Artificial Neural Network (ANN), to value financial options and to calculate implied volatilities with the aim of accelerating the corresponding numerical methods. With ANNs being universal function approximators, this method trains an optimized ANN on a data set generated by a sophisticated financial model, and runs the trained ANN as an agent of the original solver in a fast and efficient way. We test this approach on three different types of solvers, including the analytic solution for the Black-Scholes equation, the COS method for the Heston stochastic volatility model and Brent's iterative root-finding method for the calculation of implied volatilities. The numerical results show that the ANN solver can reduce the computing time significantly

Long-Term Dependence Characteristics of European Stock Indices

In this paper we show the degrees of persistence of the time series if eight European stock market indices are measured, after their lack of ergodicity and stationarity has been established. The proper identification of the nature of the persistence of financial time series forms a crucial step in deciding whether econometric modeling of such series might provide meaningful results. Testing for ergodicity and stationarity must be the first step in deciding whether the assumptions of numerous time series models are met. Our results indicate that ergodicity and stationarity are very difficult to establish in daily observations of these market indexes and thus various time-series models cannot be successfully identified. However, the measured degrees of persistence point to the existence of certain dependencies, most likely of a nonlinear nature, which, perhaps can be used in the identification of proper empirical econometric models of such dynamic time paths of the European stock market indexes. The paper computes and analyzes the long- term dependence of the equity index data as measured by global Hurst exponents, which are computed from wavelet multi-resolution analysis. For example, the FTSE turns out to be an ultra-efficient market with abnormally fast mean-reversion, faster than theoretically postulated by a Geometric Brownian Motion. Various methodologies appear to produce non-unique empirical measurement results and it is very difficult to obtain definite conclusions regarding the presence or absence of long term dependence phenomena like persistence or anti-persistence based on the global or homogeneous Hurst exponent. More powerful methods, such as the computation of the multifractal spectra of financial time series may be required. However, the visualization of the wavelet resonance coefficients and their power spectrograms in the form of localized scalograms and average scalegrams, forcefully assist with the detection and measurement of several nonlinear types of market price diffusion.Long-Term Dependence, European Stock Indices

Systematics of Unionicola Laurentiana, N.Sp., and U. Nearctica, N. Sp., Sponge-Associated Hydracarina (Parasitengona: Unionicolidae) from North America

Author Institution: Department of Biology, Saint Lawrence University; Zoologisch Laboratorium, Universiteit van Amsterdam, The NetherlandsThe sponge-associated Hydracarina of North America historically have been considered conspecific with the European species Unionicola crassipes (Miiller 1776). Ratio diagrams based on numerous morphological characteristics distinguish the North American crassipes-like mites from U. crassipes and two North American species are described. Unionicola laurentiana, n.sp., occurs in the Laurentian Great Lakes and St. Lawrence River basins. U. nearctica, n.sp., occurs in that region and its range extends across Canada from Ontario to British Columbia