An Empirical Comparison of Single-Factor Consistent Models


Book Description

Yield-curve models are broadly used by the industry for valuating fixed-income securities. These models reply term-structure of interest rates observed in the market accurately. In this work we make an empirical comparison among the main one-factor models used as management portfolio tools: the Hull-White model, the squared Gaussian model and a restricted version of Black-Karasinski model.







An Empirical Comparison of Latent Trait Theory and Hierarchical Factor Analysis in Applications to the Measurements of Job Satisfaction


Book Description

Data were collected on the Job Descriptive Index from a large heterogeneous sample of respondents. These data are used to compare empirically a latent trait model to a hierarchical factor analytic model. Latent trait item parameters estimated by LOGIST agree quite well with the item loadings on a general satisfaction factor based on the methodology suggested by Humphreys. These results are consistent with a hierarchical job satisfaction construct that has one general factor and multiple group factors. The implications of the results and future research are discussed. (Author).




Mathematical Models in Finance


Book Description

Mathematical Models in Finance compiles papers presented at the Royal Society of London discussion meeting. Topics range from the foundations of classical theory to sophisticated, up-to-date mathematical modeling and analysis. In the wake of the increased level of mathematical awareness in the financial research community, attention has focused on fundamental issues of market modelling that are not adequately allowed for in the standard analyses. Examples include market anomalies and nonlinear coupling effects, and demand new synthesis of mathematical and numerical techniques. This line of inquiry is further stimulated by ever tightening profits due to increased competition. Several papers in this volume offer pointers to future developments in this area.










Handbook of Structural Equation Modeling


Book Description

"This accessible volume presents both the mechanics of structural equation modeling (SEM) and specific SEM strategies and applications. The editor, along with an international group of contributors, and editorial advisory board are leading methodologists who have organized the book to move from simpler material to more statistically complex modeling approaches. Sections cover the foundations of SEM; statistical underpinnings, from assumptions to model modifications; steps in implementation, from data preparation through writing the SEM report; and basic and advanced applications, including new and emerging topics in SEM. Each chapter provides conceptually oriented descriptions, fully explicated analyses, and engaging examples that reveal modeling possibilities for use with readers' data. Many of the chapters also include access to data and syntax files at the companion website, allowing readers to try their hands at reproducing the authors' results"--




Improving Inquiry in Social Science


Book Description

This volume celebrates Lee J. Cronbach's considerable contributions to the methodology of social and behavioral science. Comprised of chapters written by colleagues and contemporaries of the highly influential scholar, it offers a range of ideas, perspectives, and new approaches to improving social science inquiry.




Large Dimensional Factor Analysis


Book Description

Large Dimensional Factor Analysis provides a survey of the main theoretical results for large dimensional factor models, emphasizing results that have implications for empirical work. The authors focus on the development of the static factor models and on the use of estimated factors in subsequent estimation and inference. Large Dimensional Factor Analysis discusses how to determine the number of factors, how to conduct inference when estimated factors are used in regressions, how to assess the adequacy pf observed variables as proxies for latent factors, how to exploit the estimated factors to test unit root tests and common trends, and how to estimate panel cointegration models.




Encyclopedia of Financial Models, Volume I


Book Description

Volume 1 of the Encyclopedia of Financial Models The need for serious coverage of financial modeling has never been greater, especially with the size, diversity, and efficiency of modern capital markets. With this in mind, the Encyclopedia of Financial Models has been created to help a broad spectrum of individuals ranging from finance professionals to academics and students understand financial modeling and make use of the various models currently available. Incorporating timely research and in-depth analysis, Volume 1 of the Encyclopedia of Financial Models covers both established and cutting-edge models and discusses their real-world applications. Edited by Frank Fabozzi, this volume includes contributions from global financial experts as well as academics with extensive consulting experience in this field. Organized alphabetically by category, this reliable resource consists of thirty-nine informative entries and provides readers with a balanced understanding of today's dynamic world of financial modeling. Volume 1 addresses Asset Pricing Models, Bayesian Analysis and Financial Modeling Applications, Bond Valuation Modeling, Credit Risk Modeling, and Derivatives Valuation Emphasizes both technical and implementation issues, providing researchers, educators, students, and practitioners with the necessary background to deal with issues related to financial modeling The 3-Volume Set contains coverage of the fundamentals and advances in financial modeling and provides the mathematical and statistical techniques needed to develop and test financial models Financial models have become increasingly commonplace, as well as complex. They are essential in a wide range of financial endeavors, and the Encyclopedia of Financial Models will help put them in perspective.