662 research outputs found
The impact of order size on stock liquidity: a representative study
Liquidity, the ease of trading an asset, strongly varies between different sizes of stock positions. We analyze this aspect using the Xetra Liquidity Measure (XLM), which calculates daily, weighted spread for impatient traders transacting against the limit order book. For this measure, we have data for 160 German stocks over 5.5 years, which allows us a representative analysis of the order-size impact on liquidity cost and its main statistical characteristics. We find that in the sample period average liquidity costs rose to over 100bp in large DAX and to 460bp in large SDAX positions. Over the last 5.5 years, liquidity has equally improved across all order sizes. Liquid position sizes, however, suffered less badly during the recent sub-prime crises, which represents another type of the flight-to-liquidity. As the basis for further theoretical analysis, we find that trends in liquidity levels and inefficiencies in liquidity prices of large positions generate non-normality in the liquidity distribution. We also show that - as a rule of thumb - liquidity of an order size relative to market value and transaction volume is constant across stocks and time. While order size is not the most important liquidity determinant, doubling order size increases liquidity cost by 5-10% on average when accounting for other differences in stocks. --asset liquidity,liquidity cost,price impact,weighted spread,Xetra liquidity measure (XLM)
Market liquidity risk: an overview
Market liquidity is the ease of trading an asset. Its risk is the potential loss, because a security can only be traded at high or prohibitive costs. While the omnipresence and importance of market liquidity is widely acknowledged, it has long remained a more or less elusive concept. Treatment of liquidity risk is still under development. This paper provides an overview on important aspects of market liquidity and its risk. We also survey existing models to integrate market liquidity risk into risk frameworks. We place special emphasis on practical usability and discuss relevant strengths, weaknesses and their implications. --asset liquidity,liquidity cost,price impact,Xetra liquidity measure (XLM),risk measurement,Value-at-Risk, market liquidity risk,overview
Why and how to integrate liquidity risk into a VaR-framework
We integrate liquidity risk measured by the weighted spread into a Value-at-Risk (VaR) framework. The weighted spread measure extracts liquidity costs by order size from the limit order book. We show that it is precise from a risk perspective in a wide range of clearly defined situations. Using a unique, representative data set provided by Deutsche Boerse AG, we find liquidity risk to increase traditionally-measured price risk by over 25%, even at standard 10-day horizons and for liquid DAX stocks. We also show that the common approach of simply adding liquidity risk to price risk substantially overestimates total risk because correlation between liquidity and price is neglected. Our results are robust with respect to changes in risk measure, to sample periods and to effects of portfolio diversification. --asset liquidity,price impact,weighted spread,Xetra Liquidity Measure (XLM),Value-at-Risk,market liquidity risk
Complex thermorheology of living cells
Temperature has a reliable and nearly instantaneous influence onmechanical responses of cells.As recently
published, MCF-10Anormal epithelial breast cells follow the time–temperature superposition (TTS)
principle. Here,wemeasured thermorheological behaviour of eightcommoncell types within
physiologically relevant temperatures and appliedTTS to creep compliance curves.Our results showed that
superposition is not universal and was seen in four of the eight investigated cell types. For the other cell
types, transitions of thermorheological responses were observed at 36 °C.Activation energies (EA)were
calculated for all cell types and ranged between 50 and 150 kJmol−1.The scaling factors of the superposition
of creep curves were used to group the cell lines into three categories. They were dependent on relaxation
processes aswell as structural composition of the cells in response tomechanical load and temperature
increase.This study supports the view that temperature is a vital parameter for comparing cell rheological
data and should be precisely controlledwhen designing experiments
project report Promise2007
Das Projekt Promise2007 befasste sich mit der Erstellung und Auswertung einer Statistik zur Mitgliedersituation im Berufsverband Medizinischer Informatiker e.V.. Mit dem Ziel mehr über die Mitglieder und ihre derzeitige Situation zu erfahren wurde das Projekt an der Fachhochschule Hannover initiiert. Statistisch erfasst wurden Fragen zum Beschäftigungsverhältnis, zu Aus- und Weiterbildung, der beruflichen Situation und persönliche Angaben. Die Ergebnisse wurden ausgewertet und daraus wichtige Erkenntnisse für den BVMI e.V. abgeleitet, welche auf die weitere Verbandsarbeit Einfluss nehmen
Complex thermorheology of living cells
Temperature has a reliable and nearly instantaneous influence on mechanical responses of cells. As recently published, MCF-10A normal epithelial breast cells follow the time-temperature superposition (TTS) principle. Here, we measured thermorheological behaviour of eight common cell types within physiologically relevant temperatures and applied TTS to creep compliance curves. Our results showed that superposition is not universal and was seen in four of the eight investigated cell types. For the other cell types, transitions of thermorheological responses were observed at 36 °C. Activation energies (EA) were calculated for all cell types and ranged between 50 and 150 kJ mol-1. The scaling factors of the superposition of creep curves were used to group the cell lines into three categories. They were dependent on relaxation processes as well as structural composition of the cells in response to mechanical load and temperature increase. This study supports the view that temperature is a vital parameter for comparing cell rheological data and should be precisely controlled when designing experiments
The allele distribution in next-generation sequencing data sets is accurately described as the result of a stochastic branching process
With the availability of next-generation sequencing (NGS) technology, it is expected that sequence variants may be called on a genomic scale. Here, we demonstrate that a deeper understanding of the distribution of the variant call frequencies at heterozygous loci in NGS data sets is a prerequisite for sensitive variant detection. We model the crucial steps in an NGS protocol as a stochastic branching process and derive a mathematical framework for the expected distribution of alleles at heterozygous loci before measurement that is sequencing. We confirm our theoretical results by analyzing technical replicates of human exome data and demonstrate that the variance of allele frequencies at heterozygous loci is higher than expected by a simple binomial distribution. Due to this high variance, mutation callers relying on binomial distributed priors are less sensitive for heterozygous variants that deviate strongly from the expected mean frequency. Our results also indicate that error rates can be reduced to a greater degree by technical replicates than by increasing sequencing depth
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Defining the Identity and Dynamics of Adult Gastric Isthmus Stem Cells.
The gastric corpus epithelium is the thickest part of the gastrointestinal tract and is rapidly turned over. Several markers have been proposed for gastric corpus stem cells in both isthmus and base regions. However, the identity of isthmus stem cells (IsthSCs) and the interaction between distinct stem cell populations is still under debate. Here, based on unbiased genetic labeling and biophysical modeling, we show that corpus glands are compartmentalized into two independent zones, with slow-cycling stem cells maintaining the base and actively cycling stem cells maintaining the pit-isthmus-neck region through a process of "punctuated" neutral drift dynamics. Independent lineage tracing based on Stmn1 and Ki67 expression confirmed that rapidly cycling IsthSCs maintain the pit-isthmus-neck region. Finally, single-cell RNA sequencing (RNA-seq) analysis is used to define the molecular identity and lineage relationship of a single, cycling, IsthSC population. These observations define the identity and functional behavior of IsthSCs.Wellcome Trust
Royal Societ
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