CONTINUOUS‐TIME MEAN‐VARIANCE PORTFOLIO SELECTION WITH BANKRUPTCY PROHIBITION

By Tomasz R. Bielecki, Hanqing Jin, Stanley R. Pliska, Xun Yu Zhou. 2005

361 citations recorded by the source corpus.

Subfields: Finance, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/cc12835c8f72fc52cb317dcee9f84d5aa528cb00

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Finance

1. Peter A. Forsyth
2. Elena Vigna
3. Xun Yu Zhou
4. Xun Li
5. Xiang Lin
6. Yiping Qian
7. Jian Wang
8. Xiangyu Cui

In Management Science and Operations Research

1. Peter A. Forsyth
2. Elena Vigna
3. Xun Yu Zhou
4. Xun Li
5. Xiang Lin
6. Yiping Qian
7. Jian Wang
8. Xiangyu Cui

Citations in the corpus

• On efficiency of mean–variance based portfolio selection in defined contribution pension schemes (2014, background): “V approach was mentioned by Bielecki et al. (2005).”
• BETTER THAN DYNAMIC MEAN‐VARIANCE: TIME INCONSISTENCY AND FREE CASH FLOW STREAM (2012, background): “…mean-variance portfolio selection theory, see for examples, Li, Zhou, and Lim (2001), Lim and Zhou (2002), Zhou and Yin (2003), Hu and Zhou (2005), Bielecki et al. (2005), Li and Zhou (2006), Chiu and Li (2006), Xiong and Zhou (2007) in continuous-time settings and Leippold, Trojani, and Vanini…”
• Mean-Variance Policy for Discrete-time Cone Constrained Markets: The Consistency in Efficiency and Minimum-Variance Signed Supermartingale Measure (2014, neutral): “ ,T −1. Constrained dynamic mean-variance portfolio selection problems with various constraints have been attracting increasing attention in the last decade, e.g., Li et al (2002), Zhu et al. (2004), Bielecki et al (2005), Sun and Wang (2006), Labb´e and Heunis(2007) andCzichowsky and Schweizer (201”
• MEAN–VARIANCE PORTFOLIO OPTIMIZATION WITH STATE‐DEPENDENT RISK AVERSION (2014, background): “Further extensions and improvements are carried out in, among many others, [13], [12], [3], and [20].”
• A Hamilton-Jacobi-Bellman approach to optimal trade execution (2011, methodology): “We can eliminate the constraint in problem (2.14) by using a Lagrange multiplier [23, 11 , 33, 5, 4], which we denote by . Problem (2.14) can then be posed as [12]”
• Numerical solution of the Hamilton-Jacobi-Bellman formulation for continuous time mean variance asset allocation (2010, positive): “However, we will see later in Section 6 that the efficient frontier given by our approach (using the proportion as the control) converges to the analytic solution given in (Bielecki et al., 2005) (using the monetary amount as the control).”
• Time-consistent mean-variance reinsurance-investment strategy for insurers under CEV model (2016, methodology): “Continuous-time mean-variance portfolio selection with bankruptcy prohibition was solved in Bielecki et al. (2005) using a decomposition approach.”
• Continuous-time mean-variance efficiency: the 80% rule (2006, background): “Assumption A1 and that ∫ T 0 |θ(t)|2 dt < +∞ are to ensure that the market is arbitrage-free and complete, whereas that ∫ T 0 |θ(t)|2 dt > 0 is to guarantee that the mean-variance problem is feasible for any z > 0 (see [2], Theorem 3.”
• MEAN–VARIANCE PORTFOLIO CHOICE: QUADRATIC PARTIAL HEDGING (2005, neutral): “In this case, the method of Lagrange multipliers can be used to solve (3.1), as done by Bielecki et al. (2005).”