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The second approach studies human learning to clarify the conditions under which people quickly learn to maximize expected return.
Review of basic learning research suggests that, under these conditions, people quickly learn to maximize expected return.
This approach generates optimal weights of investment to each stage of the groundwater management and helps maximize expected return while minimizing overall risk in the future.
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Just as financial managers seek to balance risks and benefits through systematic analysis, this planning exercise provides a framework for systematically deciding how to invest funds to maximize expected returns in environmental health where returns are measured in terms of decreases in overall population disease burden.
Conclusions: The strategic planning exercise described here provides a framework for systematically deciding how to invest public funds to maximize expected returns in environmental health, where returns are measured in terms of reductions in a population's environmental burden of disease.
In this paper, we applied a portfolio theory-based decision support tool that helps determine resource allocation in a way that maximizes expected return and minimizes uncertainty.
Investing, though, is about more than maximizing expected returns.
Why choose acts that maximize expected utility?
If expected utilities are partition-sensitive, then acts that maximize expected utility may be partition-sensitive.
The ability to maximize expected value improved with age.
Classical mean variance portfolio selection aims at simultaneously maximizing the expected return of the portfolio and minimizing portfolio variance.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com