The Crisis Of Crowding

Chincarini, Ludwig B.

doi:10.1002/9781119203414

Cited by 30 publications

(10 citation statements)

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“…Nevertheless, there are indications that flares have peak energies in the soft range of the X-ray spectrum, E pk < 1 keV (Paper II). Concerning the underlying afterglow light curve, after the steep decay the spectral index does not change considerably and β ∼ 1 (Chincarini et al 2005). A different behaviour is observed during the steep decay, that is the phase during which we detect most of the flares: the spectrum can be very soft, up to β ∼ 3 (a beautiful example is GRB090111; Margutti et al 2009).…”

Section: Spectral Energy Distributionmentioning

confidence: 72%

Unveiling the origin of X-ray flares in gamma-ray bursts

Chincarini¹,

Mao²,

Margutti³

et al. 2010

Monthly Notices of the Royal Astronomical Society

178

280

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We present an updated catalogue of 113 X-ray flares detected by Swift in the ~33 per cent of the X-ray afterglows of gamma-ray burst (GRB). 43 flares have a measured redshift. For the first time the analysis is performed in four different X-ray energy bands, allowing us to constrain the evolution of the flare temporal properties with energy. We find that flares are narrower at higher energies: their width follows a power-law relation w ~ E^(-0.5) reminiscent of the prompt emission. Flares are asymmetric structures, with a decay time which is twice the rise time on average. Both time-scales linearly evolve with time, giving rise to a constant rise-to-decay ratio: this implies that both time-scales are stretched by the same factor. As a consequence, the flare width linearly evolves with time to larger values: this is a key point that clearly distinguishes the flare from the GRB prompt emission. The flare 0.3-10 keV peak luminosity decreases with time, following a power-law behaviour with large scatter: Lpk ~ t^(-2.7+/-0.5). When multiple flares are present, a global softening trend is established: each flare is on average softer than the previous one. The 0.3-10 keV isotropic energy distribution is a lognormal peaked at 10^51 erg, with a possible excess at low energies. The flare average spectral energy distribution is found to be a power law with spectral energy index β ~ 1.1. These results confirmed that the flares are tightly linked to the prompt emission. However, after considering various models we conclude that no model is currently able to account for the entire set of observations

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Section: Spectral Energy Distributionmentioning

confidence: 72%

Unveiling the origin of X-ray flares in gamma-ray bursts

Chincarini¹,

Mao²,

Margutti³

et al. 2010

Monthly Notices of the Royal Astronomical Society

178

280

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“…• NGC 1245: The first photometric studies of NGC 1245 (l = 146.6 o , b = −8.9 o ) were carried out in the 1960's (Hoag et al 1961, Chincarini 1964. It is a very rich cluster, 1.1±0.2 Gyr old (Salaris et al 2004) and with a populous red giant clump.…”

Section: Discussionmentioning

confidence: 99%

“…This places NGC 1245 3.0±0.3 kpc from the Sun, with R gc = 11.1±0.3 kpc, and z = −460±50 pc. Stellar identifications come from Chincarini (1964); alternate ID's come from Wee & Lee (1996). J2000 coordinates have been taken from the USNO-B1.0 catalog 12 .…”

Section: Discussionmentioning

confidence: 99%

A Chemical Abundance Study of 10 Open Clusters Based on Wiyn-Hydra Spectroscopy

Jacobson

Pilachowski

Friel

2011

The Astronomical Journal

118

111

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We present a detailed chemical abundance study of evolved stars in 10 open clusters based on Hydra multi-object echelle spectra obtained with the WIYN 3.5m telescope. From an analysis of both equivalent widths and spectrum synthesis, abundances have been determined for the elements Fe, Na, O, Mg, Si, Ca, Ti, Ni, Zr, and for two of the 10 clusters, Al and Cr. To our knowledge, this is the first detailed abundance analysis for clusters NGC 1245, NGC 2194, NGC 2355 and NGC 2425. These 10 clusters were selected for analysis because they span a Galactocentric distance range R gc ∼9-13 kpc, the approximate location of the transition between the inner and outer disk. Combined with cluster samples from our previous work and those of other studies in the literature, we explore abundance trends as a function of cluster R gc , age, and [Fe/H]. As found previously by us and other studies, the [Fe/H] distribution appears to decrease with increasing R gc to a distance of ∼12 kpc, and then flattens to a roughly constant value in the outer disk. Cluster average element [X/Fe] ratios appear to be independent of R gc , although the picture for [O/Fe] is more more complicated by a clear trend of [O/Fe] with [Fe/H] and sample incompleteness. Other than oxygen, no other element [X/Fe] exhibits a clear trend with [Fe/H]; likewise, there does not appear to be any strong correlation between abundance and cluster age. We divided clusters into different age bins to explore temporal variations in the radial element distributions. The radial metallicity gradient appears to have flattened slightly as a function of time, as found by other studies. There is also some indication that the transition from the inner disk metallicity gradient to the ∼constant [Fe/H] distribution of the outer disk occurs at different Galactocentric radii for different age bins. However, interpretation of the time evolution of radial abundance distributions is complicated by the unequal R gc and [Fe/H] ranges spanned by clusters in different age bins.

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“…It should be noted that significance of the market timing variable may be due to the timing of other factors in their quantitative models and is being picked up by the market timing proxy. That is, it may be that some of these hedge funds are not timing the market factor, but other factors such as value versus growth, which are being captured by the market factor (see Chincarini and Nakao, 2011;Chincarini, 2012b;Bali et al, 2011).…”

Section: Market Timingmentioning

confidence: 99%

“…Some studies have examined hedge fund returns in more detail to determine whether hedge funds offer market neutral or hedged investing (Asness et al, 2001;Patton, 2009;and Titman and Tiu, 2011). New research has focused on the copycat behaviour of hedge funds (Chincarini, 2012b) and has found that immediately after the 13-F releases of hedge fund holdings, there is copycat behaviour by other funds who buy these holdings, even though the long-term return benefit does not seem to exist (Brown and Schwarz, 2013). There are notable differences in the management structure of hedge funds, including their terms of liquidity.…”

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confidence: 99%

The Impact of Quantitative Methods on Hedge Fund Performance

Chincarini

2013

Euro Fin Management

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In the last 20 years, the amount of assets managed by quantitative and qualitative hedge funds have grown dramatically. We examine the difference between quantitative and qualitative hedge funds in a variety of ways, including management differences and performance differences. We find that both quantitative and qualitative hedge funds have positive risk‐adjusted returns. We also find that overall, quantitative hedge funds as a group have higher αs than qualitative hedge funds. The outperformance might be as high as 72 bps per year when considering all risk factors. We also suggest that this additional performance may be due to better timing ability.

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The Crisis Of Crowding

Cited by 30 publications

References 0 publications

Unveiling the origin of X-ray flares in gamma-ray bursts

Unveiling the origin of X-ray flares in gamma-ray bursts

A Chemical Abundance Study of 10 Open Clusters Based on Wiyn-Hydra Spectroscopy

The Impact of Quantitative Methods on Hedge Fund Performance

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