Computational Methods for Risk Management in Economics and Finance
At present, computational methods have received considerable attention in economics and finance as an alternative to conventional analytical and numerical paradigms. This Special Issue brings together both theoretical and application-oriented contributions, with a focus on the use of computational t...
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| Year of Publication: | 2020 |
| Language: | English |
| Physical Description: | 1 electronic resource (234 p.) |
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| 520 | |a At present, computational methods have received considerable attention in economics and finance as an alternative to conventional analytical and numerical paradigms. This Special Issue brings together both theoretical and application-oriented contributions, with a focus on the use of computational techniques in finance and economics. Examined topics span on issues at the center of the literature debate, with an eye not only on technical and theoretical aspects but also very practical cases. | ||
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| 653 | |a conditional Value-at-Risk (CoVaR) | ||
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| 653 | |a utility functions | ||
| 653 | |a current drawdown | ||
| 653 | |a risk measure | ||
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| 653 | |a fractional Kelly allocation | ||
| 653 | |a independence assumption | ||
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| 653 | |a financial regulation | ||
| 653 | |a data science | ||
| 653 | |a efficient frontier | ||
| 653 | |a weighted logistic regression | ||
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| 653 | |a multi-step ahead forecasts | ||
| 653 | |a target matrix | ||
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| 653 | |a credit risk | ||
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| 653 | |a convex programming | ||
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| 653 | |a quantile regression | ||
| 653 | |a Markowitz portfolio theory | ||
| 653 | |a shrinkage | ||
| 653 | |a loss given default | ||
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