Risk-sensitive Dynamic Programming
Risk-Sensitive Dynamic Programming is a dynamic programming framework that incorporates risk measures into the optimization of sequential decision-making under uncertainty, distinguishing itself from risk-neutral approaches by explicitly accounting for the variability and higher moments of cumulative rewards.
32
Publications
1.5K
Citations
70
Authors
49
Institutions
Publications per year
2017–2026
11
32
Dynamic programming and mean-variance hedging
Jean‐Paul Laurent, Huy x EA n Pham · Finance and Stochastics · 1999 · 162 citations
Risk‐Sensitive Control and an Optimal Investment Model
Wendell H. Fleming, Shuenn‐Jyi Sheu · Mathematical Finance · 2000 · 162 citations
Risk-Sensitive Markov Control Processes
Yun Shen, Wilhelm Stannat, Klaus Obermayer · SIAM Journal on Control and Optimization · 2013 · 80 citations · Full text
The dynamics of risk-sensitive allocations
Evan W. Anderson · Journal of Economic Theory · 2004 · 77 citations
1–5 of 32
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Universidad Autónoma Agraria Antonio Narro, Mexico
2 publications · 28 citations
2
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2
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1–5 of 70
49
University of Maryland, College Park
College Park, United States
2 h-index
5 publications
92 citations

Universidad Autónoma Agraria Antonio Narro
Saltillo, Mexico
2 h-index
3 publications
40 citations

Sun Yat-sen University
Guangzhou, China
2 h-index
2 publications
44 citations

Chinese Academy of Sciences
Beijing, China
1 h-index
1 publications
16 citations
Bernstein Center for Computational Neuroscience Berlin
Berlin, Germany
1 h-index
2 publications
160 citations
University of Science and Technology of China
Hefei, China
1 h-index
1 publications
17 citations

Idaho National Laboratory
Idaho Falls, United States
1 h-index
5 publications
110 citations
Science Oxford
Oxford, United Kingdom
1 h-index
1 publications
23 citations
1–8 of 49
3 publications · 199 citations
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2 publications · 56 citations
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2 publications · 458 citations
2
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2 publications · 43 citations
2
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OR · 2 publications · 29 citations
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