Stochastic Discounting Model Research Articles

Stochastic Integrals in Discounting Proactive Operations

Proactivity constitutes a structural factor of decision making in many practical disciplines. It is generally adopted that stochastic discounting models substantially contribute to the development and implementation of proactive operations. The paper concentrates on the formulation of a stochastic discounting model by incorporating a stochastic integral and a positive random variable. Moreover, the paper provides interpretation of the stochastic discounting model in proactive environments.

Formulation and investigation of a stochastic model for proactive treatment of global risk severity

It is well known that the proactive treatment of global risks constitutes a very strong process of global risk governance. Moreover, it is readily understood that this process is supported by the use of various stochastic discounting models. The present paper concentrates on the formulation and the representation as a random contraction of a stochastic discounting model. The paper also provides an interpretation of the formulated stochastic discounting model in proactive treatment of the severity of a global risk.

Random contractions in continuous discounting of Bernoulli selecting processes arising in systemics

The formulation, investigation, and application of stochastic models constitute research activities of exceptional theoretical and practical importance. In particular, stochastic discounting models are adopted as strong analytical tools with very extensive applicability for solving difficult problems in a very wide variety of practical disciplines. The main research intention of the paper is the theoretical investigation of a formulated stochastic discounting model. More precisely, the paper establishes sufficient conditions for embedding the formulated stochastic discounting model into the extremely useful class of random contractions of Bernoulli selecting processes. Moreover, the paper makes quite clear the role of the formulated stochastic model in the leading discipline of systemics.

Random contractions in continuous discounting of Bernoulli selecting processes arising in systemics

The formulation, investigation, and application of stochastic models constitute research activities of exceptional theoretical and practical importance. In particular, stochastic discounting models are adopted as strong analytical tools with very extensive applicability for solving difficult problems in a very wide variety of practical disciplines. The main research intention of the paper is the theoretical investigation of a formulated stochastic discounting model. More precisely, the paper establishes sufficient conditions for embedding the formulated stochastic discounting model into the extremely useful class of random contractions of Bernoulli selecting processes. Moreover, the paper makes quite clear the role of the formulated stochastic model in the leading discipline of systemics.

Stochastic discounting for cost effective replacements of systems under competing catastrophic risks

The minimum of a random number of nonnegative random variables constitutes a fundamental concept of extreme value theory with significant practical applications. The present paper is mainly devoted to the formulation, investigation, and interpretation in competing risks management of a stochastic discounting model based on this fundamental concept.

Properties and management applications of a modified stochastic discounting model

Stochastic discountingmodels based on fundamental concepts of extreme value theory are considered particularly useful for supporting decision making in a wide variety of practical disciplines. The paper formulates a stochastic discounting model by making use of two fundamental concepts of extreme value theory. Moreover, the paper establishes properties and applications in some areas of management of the formulated stochastic discounting model.

Incorporating concepts of extreme value theory in formulating a discounting model for making optimal decisions in competing risks management

Stochastic discounting models incorporating concepts of extreme value theory constitute very strong analytical tools for making optimal risk management decisions. The paper makes use of two fundamental concepts of extreme value theory for formulating a stochastic discounting model. The paper also establishes properties and applications in optimal competing risks management decisions of the formulated stochastic discounting model.

Discounted minimum of a random number of random variables in replacement of computer systems

The paper concentrates on the formulation, investigation and applications of a stochastic discounting model. More precisely, the paper makes use of the minimum of a random number of nonnegative random variables and a nonnegative random variable for formulating a stochastic discounting model and also establishes applications in replacement of computer systems of such a stochastic model.

Discounted maximum of a random number of random cash flows in optimal decision making

The paper makes use of an important concept of extreme value theory in order to formulate a stochastic discounting model for the present value of a random cash flow under random timing and constant force of interest. Sufficient conditions for evaluating the distribution function of the formulated model are established. Moreover, applications in optimal decision making of the proposed stochastic discounting model are provided.

Thinning of renewal processes in stochastic discounting models and risk frequency reduction operations

The paper considers a thinning of renewal processes in the development of a stochastic model for the present value of a random cash flow under random timing and constant force of interest. The development of this model is based on two random sums of positive, independent and identically distributed random variables. Applications of the proposed stochastic discounting model in the area of risk frequency reduction operations are also provided by the paper.

Risk management operations described by a stochastic discounting model incorporating a random sum of cash flows and a random maximum of recovery times

The paper makes use of two important concepts of probability theory in order to formulate a stochastic discounting model for the present value of a random cash flow under random timing and constant force of interest. Applications in fundamental risk management operations of the proposed stochastic discounting model are provided. Moreover, sufficient conditions for embedding the distribution corresponding to the model into an important class of generalized unimodal distributions are established.

Properties and applications in risk management operations of a stochastic discounting model

Stochastic discounting models have been widely adopted in many practical disciplines. In particular, the contribution of these models to the development of risk management as an organizational discipline has been proved very important. This paper is mainly devoted to the formulation, practical applications and investigation of a stochastic discounting model. More precisely, a stochastic discounting model for the present value of a continuous uniform cash flow, incorporating some fundamental concepts of probability theory, is formulated. Applications of the model in several areas of risk management are also provided. Moreover, sufficient conditions for embedding the distribution corresponding to the model into an important class of transformed distributions are established.

A stochastic discounting model arising in competing risks management

Stochastic discounting models have been proved very important for decision making under conditions of uncertainty in many applied fields. This paper is mainly devoted to the establishment of properties for the distribution of a stochastic discounting model. The paper, also, provides applications of this model in assessing competing risks.

A stochastic model for proactive risk management decisions

The analysis of stochastic discounting models provides one of the more powerful tools available for decision-making under conditions of uncertainty. This paper is mainly devoted to the establishment of properties and applications of a particular stochastic discounting model. More precisely, the paper investigates some of the theoretical problems encountered in a stochastic discounting model when assessing mutually exclusive options, and establishes the advantages of considering risk retention in proactive risk-management programs.