Benefits on Sales Generated by Innovation

The object of the research is to assess whether organizations’ ability to innovate may be able to explain abnormal returns to firms by composing risk factor models. Using R&D investment indicators and published patents from a global sample of companies for the period 1992 to 2018, the 3-factor, 4-factor and 5-factor risk models were applied. Partly the case is that increased investment in innovation contributes to better sales performance and, consequently, excess returns. Regarding the rolling-regression method, the results show few scenarios in which the ability to innovate is an explanatory factor for financial performance.

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Risk models vs characteristic models from an investor’s perspective

The Journal of Risk Finance ◽

10.1108/jrf-10-2018-0163 ◽

2019 ◽

Vol 20 (2) ◽

pp. 201-222

Author(s):

Christian Fieberg ◽

Armin Varmaz ◽

Thorsten Poddig

Keyword(s):

Risk Factor ◽

Versus Characteristic ◽

Design Methodology ◽

Factor Models ◽

Expected Returns ◽

Risk Models ◽

Content Type ◽

Risk Factor Models ◽

Mean Variance ◽

Academic Debate

Purpose The purpose of this paper is to analyze the implications of the risk versus characteristic debate from the perspective of a mean-variance investor. Design/methodology/approach Expected returns and the variance-covariance matrix are estimated based on various characteristic and risk models and evaluated for the purpose of mean-variance portfolios. Findings Return estimates from characteristic models are most informative to investors. Risk-factor models provide the most informative estimates of the risk. A mean-variance investor should rely on combinations of the two model types. Originality/value Although the risk vs characteristic debate is a binary academic debate, our findings from an investor's perspective suggest to make use of the best of both worlds.

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Maturity adjustments under asymptotic single risk factor models: a comparative analysis

The Journal of Credit Risk ◽

10.21314/jcr.2008.074 ◽

2008 ◽

Vol 4 (3) ◽

pp. 103-135

Author(s):

Eric McCoy

Keyword(s):

Risk Factor ◽

Comparative Analysis ◽

Factor Models ◽

Single Risk Factor ◽

Risk Factor Models

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The Contributions of Propensity, Delinquent Peers, Low Parental Supervision, and Empathy to the Emergence of Antisocial Behavior in Childhood and Adolescence: Testing Developmental Path Models Combining Psychological- and Sociological-Criminological Approaches

International Journal of Developmental Science ◽

10.3233/dev-200285 ◽

2020 ◽

pp. 1-14

Author(s):

Susanne Wallner ◽

Stemmler Mark ◽

Jost Reinecke

Keyword(s):

Risk Factor ◽

Antisocial Behavior ◽

Action Theory ◽

Cumulative Risk ◽

Factor Models ◽

Individual Risk ◽

Parental Supervision ◽

Childhood And Adolescence ◽

Path Models ◽

Risk Factor Models

Psychological- and sociological-criminological research refers to, for example, cumulative risk factor models (e.g., Lösel & Bender, 2003) and Situational Action Theory (SAT; e.g., Wikström, 2006). The German longitudinal study “Chances and Risks in the Life Course“ (research project A2, Collaborative Research Center 882; e.g., Reinecke, Stemmler, & Wittenberg, 2016) focuses upon the development of antisocial behavior from a psychological and sociological point of view. Two-wave panel data of two cohorts (children and adolescents) were utilized to test the power of developmental path models investigating the development of antisocial behavior. Individual risk seems to have both direct and indirect influences on antisocial behavior, supporting the ideas of risk factor models; antisocial behavior might be the outcome of the interaction between propensity and criminogenic exposure, so there is evidence for SAT. Additionally, empathy seems to be related to both propensity and low parental supervision. Implications for the study of antisocial behavior in childhood and adolescence are discussed in line with developmental criminology.

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Ordering risk bounds in factor models

Dependence Modeling ◽

10.1515/demo-2018-0015 ◽

2018 ◽

Vol 6 (1) ◽

pp. 259-287 ◽

Cited By ~ 2

Author(s):

Jonathan Ansari ◽

Ludger Rüschendorf

Keyword(s):

Risk Factor ◽

Systemic Risk ◽

Factor Models ◽

Worst Case ◽

Sign Changes ◽

Risk Factor Models ◽

Risk Bounds ◽

Derivatives Of ◽

Dependence Structures

AbstractConditionally comonotonic risk vectors have been proved in [4] to yield worst case dependence structures maximizing the risk of the portfolio sum in partially specified risk factor models. In this paper we investigate the question how risk bounds depend on the specification of the pairwise copulas of the risk components Xiwith the systemic risk factor. As basic toolwe introduce a new ordering based on sign changes of the derivatives of copulas. This together with discretization by n-grids and the theory of supermodular transfers allows us to derive concrete ordering criteria for the maximal risks.

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