This accessible guide helps readers build a useful repertoire of mathematical tools in decision making under uncertainty, especially in investment science. It uses real data and statistical procedures, such as hypothesis testing, to show how SD theory is applied in financial situations. The book introduces utility theory for decision making under risk and discusses various research issues, such as how to use empirical data to arrive at decisions and how to conduct statistical tests when the data is coarse. It also explores numerous applications, including financial diversification, evaluating hedge funds, and income inequality.
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