A Multiple Indicators Model for Volatility Using Intra-Daily Data

Many ways exist to measure and model financial asset volatility. In principle, as the frequency of the data increases, the quality of forecasts should improve. Yet, there is no consensus about a true' or best' measure of volatility. In this paper we propose to jointly consider absolute daily returns, daily high-low range and daily realized volatility to develop a forecasting model based on their conditional dynamics. As all are non-negative series, we develop a multiplicative error model that is consistent and asymptotically normal under a wide range of specifications for the error density function. The estimation results show significant interactions between the indicators. We also show that one-month-ahead forecasts match well (both in and out of sample) the market-based volatility measure provided by an average of implied volatilities of index options as measured by VIX.

Vector Multiplicative Error Models: Representation and Inference

The Multiplicative Error Model introduced by Engle (2002) for positive valued processes is specified as the product of a (conditionally autoregressive) scale factor and an innovation process with positive support. In this paper we propose a multi-variate extension of such a model, by taking into consideration the possibility that the vector innovation process be contemporaneously correlated. The estimation procedure is hindered by the lack of probability density functions for multivariate positive valued random variables. We suggest the use of copulafunctions and of estimating equations to jointly estimate the parameters of the scale factors and of the correlations of the innovation processes. Empirical applications on volatility indicators are used to illustrate the gains over the equation by equation procedure.

The discovery of the first human retrovirus: HTLV-1 and HTLV-2

I describe here the history leading up to and including my laboratory's discovery of the first human retrovirus, HTLV-I, and its close relative, HTLV-II. My efforts were inspired by early work showing a retroviral etiology for leukemias in various animals, including non-human primates. My two main approaches were to develop criteria for and methods for detection of viral reverse transcriptase and to identify growth factors that could support the growth of hematopoietic cells. These efforts finally yielded success following the discovery of IL-2 and its use to culture adult T cell lymphoma/leukemia cells

Constitutional Law - Fourth and Fifth Amendment - Civil Forfeiture - Due Process Clause

The Supreme Court of the United States held that absent exigent circumstances, the Due Process Clause does require the Government to provide notice and a hearing before seizing real property that is subject to civil forfeiture. United States v. Good, 114 S. Ct. 492 (1993)

AMUSE-Virgo I. Super-massive black holes in low-mass spheroids

We present the first results from the AGN Multiwavelength Survey of Early-type galaxies in the Virgo cluster (AMUSE-Virgo). This large program targets 100 early-type galaxies with the Advanced CCD Imaging Spectrometer on board the Chandra X-ray Observatory and the Multi-band Imaging Photometer on board the Spitzer Space Telescope, with the aim of providing an unbiased census of low-level super-massive black hole (SMBH) activity in the local universe. Here we report on the Chandra observations of the first 16 targets, and combine them with results from archival data of another, typically more massive, 16 targets. Point-like X-ray emission from a position coincident with the optical nucleus is detected in 50% of the galaxies (down to our completeness limit of ~4E+38 erg/sec). Two of the X-ray nuclei are hosted by galaxies (VCC1178=N4464 and VCC1297=N4486B) with absolute B magnitudes fainter than -18, where nuclear star clusters are known to become increasingly common. After carefully accounting for possible contamination from low mass X-ray binaries, we argue that the detected nuclear X-ray sources are most likely powered by low-level accretion on to a SMBH, with a <11% chance contamination in VCC1178, where a star cluster is barely resolvable in archival Hubble Space Telescope images. Based on black hole mass estimates from the global properties of the host galaxies, all the detected nuclei are highly sub-Eddington, with luminosities in the range -8.4<log(L_0.3-10keV/L_Edd)<-5.9. The incidence of nuclear X-ray activity increases with the stellar mass M_star of the host galaxy: only between 3-44% of the galaxies with M_star<1E+10 M_Sun harbor an X-ray active SMBH. The fraction rises to between 49-87% in galaxies with stellar mass above 1E+10 M_Sun (at the 95% confidence level).Comment: Revised version, accepted by Ap

Characterization and Thermal Behavior of the Iron Dietary Supplement Ferrous Glycine Sulfate Pentahydrate

Ferrous glycine sulfate pentahydrate [Fe(glycine)(SO4)·5H2O with glycine = C2H5NO2], contained in the supplement for treating iron deficiency anaemia, commercially known as ferro sanol duodenal®, was characterized by laboratory X‐ray powder diffraction (XRPD), scanning electron microscope (SEM), and infrared spectroscopy (IR). The thermal behavior was investigated by thermal analysis (TGA and DTA) and temperature‐dependent in situ XRPD measurements. Furthermore, the phase transitions to a less hydrated form [Fe(glycine)(SO4)·3H2O] and successively to the anhydrous form were demonstrated to occur in the crystalline solid state. Compared to the crystal structure of the pentahydrate, the trihydrate exhibits a different coordination environment of the iron sites where glycine ligands bridge iron forming a 1D polymeric chain structure. From detailed structural comparison, the mechanism of the phase transitions can be concluded

Semiparametric vector MEM

In financial time series analysis we encounter several instances of non–negative valued processes (volumes, trades, durations, realized volatility, daily range, and so on) which exhibit clustering and can be modeled as the product of a vector of conditionally autoregressive scale factors and a multivariate iid innovation process (vector Multiplicative Error Model). Two novel points are introduced in this paper relative to previous suggestions: a more general specification which sets this vector MEM apart from an equation by equation specification; and the adoption of a GMM-based approach which bypasses the complicated issue of specifying a general multivariate non–negative valued innovation process. A vMEM for volumes, number of trades and realized volatility reveals empirical support for a dynamically interdependent pattern of relationships among the variables on a number of NYSE stocks