Investors Should Avoid Risk And Embrace Uncertainty

Scenario analysis is a risk analysis technique that considers both the sensitivity of expected payoff to changes in key variables and the likely range of variable values.

Uncertainty and Risk Management - Forbes

In other words, risk assessment means constructing the random variable that describes the risk.
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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.

Risk assessment is a procedure of quantifying the loss or gain values and supplying them with proper values of probabilities.
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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.

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@RISK can also be used in Six Sigma and quality analysis to improve processes, reduce variability, and enhance the quality of products and services, and save money. @RISK includes a range of Six Sigma statistics, functions, and reports. With these tools, you can identify, measure, and root out the causes of variability in your production and service processes and designs.

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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.

Business practices need to be dialed in to this uncertainty

The focus of an @RISK analysis can be narrowed using TopRank. Especially with large models, this saves time and improves accuracy of your @RISK analysis. @RISK functions can also be used by TopRank to represent a wider range of values than TopRank’s standard functions.

Loch, Arnoud DeMeyer, Michael Pich: Books

Sixteen new distribution functions have been added to @RISK, along with six new statistical functions. The new functions are important for accurate, insightful modeling of uncertainty in finance, insurance, reliability, and other applications.

@RISK is the world's most widely used risk analysis tool

Designed for professional-grade problems in any industry, @RISK Professional is perfect for most commercial uses. It provides a balance of advanced analysis and point-and-click ease of use, and includes: