A Note on Earnings Risk and the Coefficient of Variation

Brief, Richard P.; Owen, Joel

doi:10.1111/j.1540-6261.1969.tb01701.x

Cited by 20 publications

(15 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To understand the gravity of ignoring or improperly valuing IP rights see Jarrett [23,24]. This result debated previously by Brief and Owen, Pappas' and Brief [14,16,21] indicated that including earnings risk may not fully reflect all risk in estimating earnings, but at least, reflects that part of risk from the variation in earnings.…”

Section: Introductionmentioning

confidence: 60%

Intangible Assets, Intellectual Property and the Misreporting of Financial Events

Jarrett¹

2017

J Bus Fin Aff

View full text Add to dashboard Cite

Section: Introductionmentioning

confidence: 60%

Intangible Assets, Intellectual Property and the Misreporting of Financial Events

Jarrett¹

2017

J Bus Fin Aff

View full text Add to dashboard Cite

“…Coefficients of variation were used as an initial metric of change likelihood as it facilitated comparison across diverse forest C pools and has been used in risk assessments in the biological sciences [26] and finance [27]. If indeed CC occurred such that a forest experienced a climate shift from “temperate” to “equatorial,” then the contemporary range in variation in C densities between those climates may indicate likelihood of C emission.…”

Section: Discussionmentioning

confidence: 99%

A Framework for Assessing Global Change Risks to Forest Carbon Stocks in the United States

et al. 2013

View full text Add to dashboard Cite

Among terrestrial environments, forests are not only the largest long-term sink of atmospheric carbon (C), but are also susceptible to global change themselves, with potential consequences including alterations of C cycles and potential C emission. To inform global change risk assessment of forest C across large spatial/temporal scales, this study constructed and evaluated a basic risk framework which combined the magnitude of C stocks and their associated probability of stock change in the context of global change across the US. For the purposes of this analysis, forest C was divided into five pools, two live (aboveground and belowground biomass) and three dead (dead wood, soil organic matter, and forest floor) with a risk framework parameterized using the US's national greenhouse gas inventory and associated forest inventory data across current and projected future Köppen-Geiger climate zones (A1F1 scenario). Results suggest that an initial forest C risk matrix may be constructed to focus attention on short- and long-term risks to forest C stocks (as opposed to implementation in decision making) using inventory-based estimates of total stocks and associated estimates of variability (i.e., coefficient of variation) among climate zones. The empirical parameterization of such a risk matrix highlighted numerous knowledge gaps: 1) robust measures of the likelihood of forest C stock change under climate change scenarios, 2) projections of forest C stocks given unforeseen socioeconomic conditions (i.e., land-use change), and 3) appropriate social responses to global change events for which there is no contemporary climate/disturbance analog (e.g., severe droughts in the Lake States). Coupling these current technical/social limits of developing a risk matrix to the biological processes of forest ecosystems (i.e., disturbance events and interaction among diverse forest C pools, potential positive feedbacks, and forest resiliency/recovery) suggests an operational forest C risk matrix remains elusive.

show abstract

“…In the next paragraph we present a few examples regarding the CV nancial eld applications. Brief and Owen (1969) show how the CV can be considered in order to evaluate the projects risks, assuming the rate of return as a random variable. The authors used the CV of the future cash ows distribution as a measure of earnings risk and developed a mechanism for relating the CV to risk in a situation of uncertainty.…”

Section: Introductionmentioning

confidence: 99%

The coefficient of variation asymptotic distribution in the case of non-iid random variables

Curto

Pinto

2008

Journal of Applied Statistics

View full text Add to dashboard Cite

Due to the coecient of variation's widespread use in empirical nance, in this paper we derive its asymptotic sampling distribution in case of non-iid random variables to deal with autocorrelation and/or conditional heteroscedascity stylized facts of nancial returns. We propose also statistical tests for the comparison of two coecients of variation based on asymptotic normality and studentized time series bootstrap. In an illustrative example we analyze the monthly returns' volatility of six stock markets indexes during the years 1990-2007.

show abstract

A Note on Earnings Risk and the Coefficient of Variation

Cited by 20 publications

References 3 publications

Intangible Assets, Intellectual Property and the Misreporting of Financial Events

Intangible Assets, Intellectual Property and the Misreporting of Financial Events

A Framework for Assessing Global Change Risks to Forest Carbon Stocks in the United States

The coefficient of variation asymptotic distribution in the case of non-iid random variables

Contact Info

Product

Resources

About