Stochastic modeling

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Stochastic Modeling

Any of several methods for measuring the probability of distribution of a random variable. That is, a stochastic model measures the likelihood that a variable will equal any of a universe of amounts. It is used in technical analysis to predict market movements. Insurance companies also use stochastic modeling to estimate their assets and liabilities because, due to the nature of the insurance business, these are not known quantities.

Stochastic modeling.

Stochastic modeling is a statistical process that uses probability and random variables to predict a range of probable investment performances.

The mathematical principles behind stochastic modeling are complex, so it's not something you can do on your own.

But based on information you provide about your age, investments, and risk tolerance, financial analysts may use stochastic modeling to help you evaluate the probability that your current investment portfolio will allow you to meet your financial goals.

Appropriately enough, the term stochastic comes from the Greek word meaning "skillful in aiming."

References in periodicals archive ?
With our innovative signal analysis tools, We will extract spatio-temporal signatures of underlying processes, Which we will investigate with stochastic modeling and validate through experimental perturbations.
After surveying the current work being done in swarm robotics, the collection presents recent research results on cooperative movement and control, space deployment and formation control, path planning, target searching, stochastic modeling, cooperative operation and partner recruitment, and human-swarm interaction.
The behavior of solar activity have accomplished by the stochastic modeling in addition to their residual analysis.
As additional context for the public hearing, Armour has provided to the Department a summary report of an independent actuarial firm's stochastic modeling of the proposed closing balance sheet, pro forma as of June 30, 2014.
Their topics include the design and verification process, block diagram modeling and system analysis, multiple domain modeling, statistical and stochastic modeling, design flow, and a complex electronic system design example.
Both deterministic and stochastic modeling approaches were explored and compared to actual submetered lighting energy data.
The topics include: suspensions, bubble and drop dynamics, flow in porous media, interfaces, turbulent flow, injectors and nozzles, particle image velocimetry, macroscale constitutive models, large eddy simulation, biological flows, environmental multiphase flow, and phase changes and stochastic modeling, among others.
Stochastic modeling involves use of computer simulations to determine how a product or company might perform under a wide range of randomly changing conditions.
In addition to answering these capital questions, many other risk management issues can be addressed with stochastic modeling.
Related to financial planning, stochastic modeling is a broad term that describes various methods used to simulate ranges of outcomes for systems that are to some extent random and unpredictable.
Actuaries are excited about this regulation, which not only takes the rules out of stochastic modeling and makes the process principles-based, but brings actuaries to the forefront of risk-based capital negotiations.

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