Citation Analysis

Risk-Aware Deep Reinforcement Learning for Dynamic Portfolio Optimization
Emmanuel Lwele, Sabuni Emmanuel, Sitali Gabriel Sitali
https://arxiv.org/abs/2511.11481

Citation mentions

Cited references

Sections

3,873

Words (approx)

References by Citation Intensity

Ordered by composite index (descending). Higher values indicate more intensive citation.

#	Reference	Year	Mentions	Breadth	Sec. Wtd	Share	Composite	Main %
1	Zuzana Jankova	2021	2	2	3.0	0.167	0.644	100%
2	Zhong, Xiao and Enke, David	2019	2	2	3.0	0.167	0.644	100%
3	Kilimci, Zeynep Hilal and Duvar, Ramazan	2020	1	1	2.0	0.083	0.406	100%
4	Harnpadungkij, Thammasorn and Chaisangmongkon, War...	2019	1	1	2.0	0.083	0.406	100%
5	Ghasemzadeha, Mohammad and Mohammad-Karimi, Naeime...	2020	1	1	2.0	0.083	0.406	100%
6	Lim, Shiau Hong and Malik, Ilyas	2022	1	1	2.0	0.083	0.406	100%
7	Molina, Gabriel	2016	1	1	2.0	0.083	0.406	100%
8	Moody, John and Wu, Lizhong and Liao, Yuansong and...	1998	1	1	2.0	0.083	0.406	100%
9	Basak, Suryoday and Kar, Saibal and Saha, Snehansh...	2019	1	1	2.0	0.083	0.406	100%
10	Reddy, V Kranthi Sai and Sai, Kranthi	2018	1	1	2.0	0.083	0.406	100%

Measures: Mentions = total in-text citations; Breadth = distinct sections; Sec. Wtd = section-weighted count (body ×2, lit review/appendix ×0.5); Share = mentions / total citations in paper; Composite = geometric mean of normalised count, breadth, and main-text ratio; Main % = fraction of mentions in main text (excl. appendix). (self) = self-citation.