Multiscaled Cross-Correlation Dynamics in Financial Time-Series

The cross correlation matrix between equities comprises multiple interactions between traders with varying strategies and time horizons. In this paper, we use the Maximum Overlap Discrete Wavelet Transform to calculate correlation matrices over different timescales and then explore the eigenvalue spectrum over sliding time windows. The dynamics of the eigenvalue spectrum at different times and scales provides insight into the interactions between the numerous constituents involved. Eigenvalue dynamics are examined for both medium and high-frequency equity returns, with the associated correlation structure shown to be dependent on both time and scale. Additionally, the Epps effect is established using this multivariate method and analyzed at longer scales than previously studied. A partition of the eigenvalue time-series demonstrates, at very short scales, the emergence of negative returns when the largest eigenvalue is greatest. Finally, a portfolio optimization shows the importance of timescale information in the context of risk management

Emergence of time-horizon invariant correlation structure in financial returns by subtraction of the market mode

We investigate the emergence of a structure in the correlation matrix of assets' returns as the time-horizon over which returns are computed increases from the minutes to the daily scale. We analyze data from different stock markets (New York, Paris, London, Milano) and with different methods. Result crucially depends on whether the data is restricted to the ``internal'' dynamics of the market, where the ``center of mass'' motion (the market mode) is removed or not. If the market mode is not removed, we find that the structure emerges, as the time-horizon increases, from splitting a single large cluster. In NYSE we find that when the market mode is removed, the structure of correlation at the daily scale is already well defined at the 5 minutes time-horizon, and this structure accounts for 80 % of the classification of stocks in economic sectors. Similar results, though less sharp, are found for the other markets. We also find that the structure of correlations in the overnight returns is markedly different from that of intraday activity.Comment: 12 pages, 17 figure

Very Isolated Early-Type Galaxies

We use the Karachentseva (1973) ``Catalogue of Very Isolated Galaxies'' to investigate a candidate list of >100 very isolated early-type galaxies. Broad-band imaging and low resolution spectroscopy are available for a large fraction of these candidates and result in a sample of 102 very isolated early-type galaxies, including 65 ellipticals and 37 S0 galaxies. Many of these systems are quite luminous and the resulting optical luminosity functions of the Es and early-types (E+S0s) show no statistical differences when compared to luminosity functions dominated by group and cluster galaxies. However, whereas S0s outnumber Es 4:1 in the CfA survey, isolated Es outnumber S0s by nearly 2:1. We conclude that very isolated elliptical galaxies show no evidence for a different formation and/or evolution process compared to Es formed in groups or clusters, but that most S0s are formed by a mechanism (e.g., gas stripping) that occurs only in groups and rich clusters. Our luminosity function results for ellipticals are consistent with very isolated ellipticals being formed by merger events, in which no companions remain. CHANDRA observations were proposed to test specifically the merger hypothesis for isolated ellipticals. However, this program has resulted in the observation of only one isolated early-type galaxy, the S0 KIG 284, which was not detected at a limit well below that expected for a remnant group of galaxies. Therefore, the hypothesis remains untested that very isolated elliptical galaxies are the remains of a compact group of galaxies which completely merged.Comment: 19 pages, 3 figures; AJ in pres

Tick size and price diffusion

A tick size is the smallest increment of a security price. It is clear that at the shortest time scale on which individual orders are placed the tick size has a major role which affects where limit orders can be placed, the bid-ask spread, etc. This is the realm of market microstructure and there is a vast literature on the role of tick size on market microstructure. However, tick size can also affect price properties at longer time scales, and relatively less is known about the effect of tick size on the statistical properties of prices. The present paper is divided in two parts. In the first we review the effect of tick size change on the market microstructure and the diffusion properties of prices. The second part presents original results obtained by investigating the tick size changes occurring at the New York Stock Exchange (NYSE). We show that tick size change has three effects on price diffusion. First, as already shown in the literature, tick size affects price return distribution at an aggregate time scale. Second, reducing the tick size typically leads to an increase of volatility clustering. We give a possible mechanistic explanation for this effect, but clearly more investigation is needed to understand the origin of this relation. Third, we explicitly show that the ability of the subordination hypothesis in explaining fat tails of returns and volatility clustering is strongly dependent on tick size. While for large tick sizes the subordination hypothesis has significant explanatory power, for small tick sizes we show that subordination is not the main driver of these two important stylized facts of financial market.Comment: To be published in the "Proceedings of Econophys-Kolkata V International Workshop on "Econophysics of Order-driven Markets" March 9-13, 2010, The New Economic Windows series of Springer-Verlag Italia

Economic Fluctuations and Diffusion

Stock price changes occur through transactions, just as diffusion in physical systems occurs through molecular collisions. We systematically explore this analogy and quantify the relation between trading activity - measured by the number of transactions $N_{\Delta t}$ - and the price change $G_{\Delta t}$, for a given stock, over a time interval $[t, t+\Delta t]$. To this end, we analyze a database documenting every transaction for 1000 US stocks over the two-year period 1994-1995. We find that price movements are equivalent to a complex variant of diffusion, where the diffusion coefficient fluctuates drastically in time. We relate the analog of the diffusion coefficient to two microscopic quantities: (i) the number of transactions $N_{\Delta t}$ in $\Delta t$, which is the analog of the number of collisions and (ii) the local variance $w^2_{\Delta t}$ of the price changes for all transactions in $\Delta t$, which is the analog of the local mean square displacement between collisions. We study the distributions of both $N_{\Delta t}$ and $w_{\Delta t}$, and find that they display power-law tails. Further, we find that $N_{\Delta t}$ displays long-range power-law correlations in time, whereas $w_{\Delta t}$ does not. Our results are consistent with the interpretation that the pronounced tails of the distribution of $G_{\Delta t} are due to$w_{\Delta t}$, and that the long-range correlations previously found for$| G_{\Delta t} |$are due to$N_{\Delta t}$.Comment: RevTex 2 column format. 6 pages, 36 references, 15 eps figure

The ROTSE-III Robotic Telescope System

The observation of a prompt optical flash from GRB990123 convincingly demonstrated the value of autonomous robotic telescope systems. Pursuing a program of rapid follow-up observations of gamma-ray bursts, the Robotic Optical Transient Search Experiment (ROTSE) has developed a next-generation instrument, ROTSE-III, that will continue the search for fast optical transients. The entire system was designed as an economical robotic facility to be installed at remote sites throughout the world. There are seven major system components: optics, optical tube assembly, CCD camera, telescope mount, enclosure, environmental sensing & protection and data acquisition. Each is described in turn in the hope that the techniques developed here will be useful in similar contexts elsewhere.Comment: 19 pages, including 4 figures. To be published in PASP in January, 2003. PASP Number IP02-11

Neutrophil C5a receptor and the outcome in a rat model of sepsis

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154259/1/fsb2fj030009fje.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154259/2/fsb2fj030009fje-sup-0001.pd

Statistical Properties of Share Volume Traded in Financial Markets

We quantitatively investigate the ideas behind the often-expressed adage `it takes volume to move stock prices', and study the statistical properties of the number of shares traded $Q_{\Delta t}$ for a given stock in a fixed time interval $\Delta t$. We analyze transaction data for the largest 1000 stocks for the two-year period 1994-95, using a database that records every transaction for all securities in three major US stock markets. We find that the distribution $P(Q_{\Delta t})$ displays a power-law decay, and that the time correlations in $Q_{\Delta t}$ display long-range persistence. Further, we investigate the relation between $Q_{\Delta t}$ and the number of transactions $N_{\Delta t}$ in a time interval $\Delta t$, and find that the long-range correlations in $Q_{\Delta t}$ are largely due to those of $N_{\Delta t}$. Our results are consistent with the interpretation that the large equal-time correlation previously found between $Q_{\Delta t}$ and the absolute value of price change $| G_{\Delta t} |$ (related to volatility) are largely due to $N_{\Delta t}$.Comment: 4 pages, two-column format, four figure

Use cases, best practice and reporting standards for metabolomics in regulatory toxicology

Metabolomics is a widely used technology in academic research, yet its application to regulatory science has been limited. The most commonly cited barrier to its translation is lack of performance and reporting standards. The MEtabolomics standaRds Initiative in Toxicology (MERIT) project brings together international experts from multiple sectors to address this need. Here, we identify the most relevant applications for metabolomics in regulatory toxicology and develop best practice guidelines, performance and reporting standards for acquiring and analysing untargeted metabolomics and targeted metabolite data. We recommend that these guidelines are evaluated and implemented for several regulatory use cases

Protonation-Induced Microphase Separation in Thin Films of a Polyelectrolyte-Hydrophilic Diblock Copolymer

Block copolymers composed of poly(oligo ethylene glycol methyl ether methacrylate) and poly(2-vinylpyridine) are disordered in the neat state but can be induced to order by protonation of the P2VP block, demonstrating a tunable and responsive method for triggering assembly in thin films. Comparison of protonation with the addition of salts shows that microphase separation is due to selective protonation of the P2VP block. Increasing acid incorporation and increasing 2-vinylpyridine content for P2VP minority copolymers both promote increasingly phase-separated morphologies, consistent with protonation increasing the effective strength of segregation between the two blocks. The self-assembled nanostructures formed after casting from acidic solutions may be tuned based on the amount and type of acid incorporation as well as the annealing treatment applied after casting, where both aqueous and polar organic solvents are shown to be effective. Therefore, POEGMA-b-P2VP is a novel ion-containing block copolymer whose morphologies can be facilely tuned during casting and processing by controlling its exposure to acid.United States. Dept. of Energy. Office of Basic Energy Sciences (Award DE-SC0001088)National Science Foundation (U.S.) (Award CMMI-1246740