New York University

About: New York University is a education organization based out in New York, New York, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 72380 authors who have published 165545 publications receiving 8334030 citations. The organization is also known as: NYU & University of the City of New York.

Specification Analysis of Affine Term Structure Models

Abstract: This paper explores the structural differences and relative goodness-of-fits of affine term structure models ~ATSMs!. Within the family of ATSMs there is a tradeoff between f lexibility in modeling the conditional correlations and volatilities of the risk factors. This trade-off is formalized by our classification of N-factor affine family into N 1 1 non-nested subfamilies of models. Specializing to three-factor ATSMs, our analysis suggests, based on theoretical considerations and empirical evidence, that some subfamilies of ATSMs are better suited than others to explaining historical interest rate behavior. IN SPECIFYING A DYNAMIC TERM STRUCTURE MODEL—one that describes the comovement over time of short- and long-term bond yields—researchers are inevitably confronted with trade-offs between the richness of econometric representations of the state variables and the computational burdens of pricing and estimation. It is perhaps not surprising then that virtually all of the empirical implementations of multifactor term structure models that use time series data on long- and short-term bond yields simultaneously have focused on special cases of “affine” term structure models ~ATSMs! .A n ATSM accommodates time-varying means and volatilities of the state variables through affine specifications of the risk-neutral drift and volatility coefficients. At the same time, ATSMs yield essentially closed-form expressions for zero-coupon-bond prices ~Duffie and Kan ~1996!!, which greatly facilitates pricing and econometric implementation. The focus on ATSMs extends back at least to the pathbreaking studies by Vasicek ~1977! and Cox, Ingersoll, and Ross ~1985!, who presumed that the instantaneous short rate r~t! was an affine function of an N-dimensional state vector Y~t!, r~t! 5 d 0 1 d y ’ Y~t!, and that Y~t! followed Gaussian and square-root diffusions, respectively. More recently, researchers have explored formulations of ATSMs that extend the one-factor Markov represen

Variance Risk Premiums

Abstract: We propose a direct and robust method for quantifying the variance risk premium on financial assets. We show that the risk-neutral expected value of return variance, also known as the variance swap rate, is well approximated by the value of a particular portfolio of options. We propose to use the difference between the realized variance and this synthetic variance swap rate to quantify the variance risk premium. Using a large options data set, we synthesize variance swap rates and investigate the historical behavior of variance risk premiums on five stock indexes and 35 individual stocks. (JEL G10, G12, G13) It has been well documented that return variance is stochastic. When investing in a security, an investor faces at least two sources of uncertainty, namely the uncertainty about the return as captured by the return variance, and the uncertainty about the return variance itself. It is important to know how investors deal with the uncertainty in return variance to effectively manage risk and allocate assets, to accurately price and hedge derivative securities, and to understand the behavior of financial asset prices in general. We develop a direct and robust method for quantifying the return variance risk premium on an asset using the market prices of options written on this asset. Our method uses the notion of a variance swap, which is an over-thecounter contract that pays the difference between a standard estimate of the realized variance and the fixed variance swap rate. Since variance swaps cost zero to enter, the variance swap rate represents the risk-neutral expected value of the realized variance. We show that the variance swap rate can be synthesized accurately by a particular linear combination of option prices. We propose to

Autoinduction and signal transduction in the regulation of staphylococcal virulence

Abstract: The accessory genes of Staphylococcus aureus, including those involved in pathogenesis, are controlled by a complex regulatory network that includes at least four two-component systems, one of which, agr, is a quorum sensor, an alternative sigma factor and a large set of transcription factors, including at least two of the superantigen genes, tst and seb. These regulatory genes are hypothesized to act in a time- and population density-dependent manner to integrate signals received from the external environment with the internal metabolic machinery of the cell, in order to achieve the production of particular subsets of accessory/virulence factors at the time and in quantities that are appropriate to the needs of the organism at any given location. From the standpoint of pathogenesis, the regulatory agenda is presumably tuned to particular sites in the host organism. To address this hypothesis, it will be necessary to understand in considerable detail the regulatory interactions among the organism's numerous controlling systems. This review is an attempt to integrate a large body of data into the beginnings of a model that will hopefully help to guide research towards a full-scale test.

Examining the Relationship Between Reviews and Sales: The Role of Reviewer Identity Disclosure in Electronic Markets

Abstract: Consumer-generated product reviews have proliferated online, driven by the notion that consumers' decision to purchase or not purchase a product is based on the positive or negative information about that product they obtain from fellow consumers. Using research on information processing as a foundation, we suggest that in the context of an online community, reviewer disclosure of identity-descriptive information is used by consumers to supplement or replace product information when making purchase decisions and evaluating the helpfulness of online reviews. Using a unique data set based on both chronologically compiled ratings as well as reviewer characteristics for a given set of products and geographical location-based purchasing behavior from Amazon, we provide evidence that community norms are an antecedent to reviewer disclosure of identity-descriptive information. Online community members rate reviews containing identity-descriptive information more positively, and the prevalence of reviewer disclosure of identity information is associated with increases in subsequent online product sales. In addition, we show that shared geographical location increases the relationship between disclosure and product sales, thus highlighting the important role of geography in electronic commerce. Taken together, our results suggest that identity-relevant information about reviewers shapes community members' judgment of products and reviews. Implications for research on the relationship between online word-of-mouth WOM and sales, peer recognition and reputation systems, and conformity to online community norms are discussed.

The microbiota in adaptive immune homeostasis and disease

Abstract: In the mucosa, the immune system's T cells and B cells have position-specific phenotypes and functions that are influenced by the microbiota. These cells play pivotal parts in the maintenance of immune homeostasis by suppressing responses to harmless antigens and by enforcing the integrity of the barrier functions of the gut mucosa. Imbalances in the gut microbiota, known as dysbiosis, can trigger several immune disorders through the activity of T cells that are both near to and distant from the site of their induction. Elucidation of the mechanisms that distinguish between homeostatic and pathogenic microbiota–host interactions could identify therapeutic targets for preventing or modulating inflammatory diseases and for boosting the efficacy of cancer immunotherapy.