Uncertainty and Risk Management - Forbes
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Political uncertainty and firm risk in China - ScienceDirect
Provides a comprehensive discussion of motivation for sources of uncertainty in decision process, and a good discussion on minmax regret and its advantages over other criteria.
In decision making under pure uncertainty, the decision-maker has no knowledge regarding any of the states of nature outcomes, and/or it is costly to obtain the needed information.
Difference between Risk and Uncertainty | Risk vs Uncertainty
Depending on the amount and degree of knowledge we have, the three most widely used types are:In decision-making under pure uncertainty, the decision maker has absolutely no knowledge, not even about the likelihood of occurrence for any state of nature.
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Analytic Solver Simulation | solver
However, in probabilistic models, the decision-maker is concerned not only with the outcome value but also with the each decision carriesAs an example of deterministic versus probabilistic models, consider : Nothing we can do can change the past, but everything we do influences and changes the future, although the future has an element of uncertainty.
Economic Development Project Evaluation | …
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@RISK provides you with sensitivity and scenario analyses to determine the critical factors in your models. Use sensitivity analysis to rank the distribution functions in your model according to the impact they have on your outputs. See the results clearly with an easy-to-interpret Tornado diagram, or uncover relationships with Scatter Plots. Sensitivity analysis pre-screens all inputs based on their precedence in formulas to outputs in your model, thus reducing irrelevant data. In addition, you can use @RISK’s Make Input function to select a formula whose value will be treated as an @RISK input for sensitivity analysis. In this way, multiple distributions can be combined into a single input, streamlining your sensitivity reports.