University of Massachusetts Amherst

About: University of Massachusetts Amherst is a education organization based out in Amherst Center, Massachusetts, United States. It is known for research contribution in the topics: Population & Galaxy. The organization has 37274 authors who have published 83965 publications receiving 3834996 citations. The organization is also known as: UMass Amherst & Massachusetts State College.

Stock Return Characteristics, Skew Laws, and the Differential Pricing of Individual Equity Options

Abstract: and relate it to variations in return skewness. Second, we show how risk aversion introduces skewness in the risk-neutral density. Third, we derive laws that decompose individual return skewness into a systematic component and an idiosyncratic component. Empirical analysis of OEX options and 30 stocks demonstrates that individual riskneutral distributions differ from that of the market index by being far less negatively skewed. This article explains the presence and evolution of risk-neutral skewness over time and in the cross section of individual stocks.

Galaxy Groups in the SDSS DR4. I. The Catalog and Basic Properties

Abstract: We use a modified version of the halo-based group finder developed by Yang et al. to select galaxy groups from the Sloan Digital Sky Survey (SDSS DR4). In the first step, a combination of two methods is used to identify the centers of potential groups and to estimate their characteristic luminosity. Using an iterative approach, the adaptive group finder then uses the average mass-to-light ratios of groups, obtained from the previous iteration, to assign a tentative mass to each group. This mass is then used to estimate the size and velocity dispersion of the underlying halo that hosts the group, which in turn is used to determine group membership in redshift space. Finally, each individual group is assigned two different halo masses: one based on its characteristic luminosity and the other based on its characteristic stellar mass. Applying the group finder to the SDSS DR4, we obtain 301,237 groups in a broad dynamic range, including systems of isolated galaxies. We use detailed mock galaxy catalogs constructed for the SDSS DR4 to test the performance of our group finder in terms of completeness of true members, contamination by interlopers, and accuracy of the assigned masses. This paper is the first in a series and focuses on the selection procedure, tests of the reliability of the group finder, and the basic properties of the group catalog (e.g., the mass-to-light ratios, the halo mass-to-stellar mass ratios). The group catalogs including the membership of the groups are available on request.

Convergence of Stochastic Iterative Dynamic Programming Algorithms

Abstract: Recent developments in the area of reinforcement learning have yielded a number of new algorithms for the prediction and control of Markovian environments. These algorithms, including the TD(λ) algorithm of Sutton (1988) and the Q-learning algorithm of Watkins (1989), can be motivated heuristically as approximations to dynamic programming (DP). In this paper we provide a rigorous proof of convergence of these DP-based learning algorithms by relating them to the powerful techniques of stochastic approximation theory via a new convergence theorem. The theorem establishes a general class of convergent algorithms to which both TD(λ) and Q-learning belong.

Relationship of cell growth to the regulation of tissue-specific gene expression during osteoblast differentiation.

Abstract: The relationship of cell proliferation to the temporal expression of genes characterizing a developmental sequence associated with bone cell differentiation can be examined in primary diploid cultures of fetal calvarial-derived osteoblasts by the combination of molecular, biochemical, histochemical, and ultrastructural approaches. Modifications in gene expression define a developmental sequence that has 1) three principal periods: proliferation, extracellular matrix maturation, and mineralization; and 2) two restriction points to which the cells can progress but cannot pass without further signals. The first restriction point is when proliferation is down-regulated and gene expression associated with extracellular matrix maturation is induced, and the second when mineralization occurs. Initially, actively proliferating cells, expressing cell cycle and cell growth regulated genes, produce a fibronectin/type I collagen extracellular matrix. A reciprocal and functionally coupled relationship between the decl...