Open Access
Issue
RAIRO-Oper. Res.
Volume 56, Number 5, September-October 2022
Page(s) 3611 - 3634
DOI https://doi.org/10.1051/ro/2022162
Published online 19 October 2022
  • L.E. Dubins and L.J. Savage, How to Gamble if You Must: Inequalities for Stochastic Processes, 1965 edition. McGraw-Hill, New York (1965). 1976 edition. Dover, New York (1976). [Google Scholar]
  • V.C. Pestien and W.D. Sudderth, Continuous-time red and black: How to control a diffusion to a goal. Math. Oper. Res. 10 (1985) 599–611. [CrossRef] [MathSciNet] [Google Scholar]
  • S. Browne, Optimal investment policies for a firm with random risk process: Exponential utility and minimizing the probability of ruin. Math. Oper. Res. 20 (1995) 937–958. [CrossRef] [MathSciNet] [Google Scholar]
  • S. Browne, Survival and growth with a liability: Optimal portfolio strategies in continuous time. Math. Oper. Res. 22 (1997) 468–493. [CrossRef] [MathSciNet] [Google Scholar]
  • S. Browne, Reaching goals by a deadline: Digital options and continuous-time active portfolio management. Adv. Appl. Probab. 31 (1999) 551–577. [CrossRef] [MathSciNet] [Google Scholar]
  • S. Browne, Beating a moving target: Optimal portfolio strategies for outperforming a stochastic benchmark. Finance Stoch. 3 (1999) 275–294. [CrossRef] [MathSciNet] [Google Scholar]
  • I. Karatzas, Adaptive control of a diffusion to a goal, and a parabolic Monge-Ampre-type equation. Asian J. Math 1 (1997) 295–313. [CrossRef] [MathSciNet] [Google Scholar]
  • X. Liang and V.R. Young, Reaching a bequest goal with life insurance. ASTIN Bull.: J. IAA 50 (2020) 187–221. [CrossRef] [Google Scholar]
  • E. Bayraktar and V.R. Young, Optimally investing to reach a bequest goal. Insur.: Math. Econ. 70 (2016) 1–10. [CrossRef] [Google Scholar]
  • E. Bayraktar, S.D. Promislow and V.R. Young, Purchasing life insurance to reach a bequest goal. Insur.: Math. Econ. 58 (2014) 204–216. [CrossRef] [Google Scholar]
  • E. Bayraktar, S.D. Promislow and V.R. Young, Purchasing term life insurance to reach a bequest goal while consuming. SIAM J. Financial Math. 7 (2016) 183–214. [CrossRef] [MathSciNet] [Google Scholar]
  • X. Han, Z. Liang, K. Yuen and Y. Yuan, Minimizing the probability of absolute ruin under ambiguity aversion. Appl. Math. Optim. 84 (2021) 2495–2525. [CrossRef] [MathSciNet] [Google Scholar]
  • D. Li and V.R. Young, Optimal reinsurance to minimize the probability of ruin under ambiguity. Insur.: Math. Econ. 87 (2019) 143–152. [CrossRef] [Google Scholar]
  • H. Schmidli, On minimizing the ruin probability of investment and reinsurance. J. Appl. Probab. 12 (2002) 890–907. [Google Scholar]
  • D. Promislow and V.R. Young, Minimizing the probability of ruin when claims follow Brownian motion with drift. N. Am. Actuar. J. 9 (2005) 109–128. [CrossRef] [MathSciNet] [Google Scholar]
  • S. Luo, Ruin minimization for insurers with borrowing constraints. N. Am. Actuar. J. 12 (2008) 143–174. [CrossRef] [MathSciNet] [Google Scholar]
  • H. Yener, Maximizing survival, growth and goal reaching under borrowing constraints. Quant. Finance 15 (2015) 2053–2065. [CrossRef] [MathSciNet] [Google Scholar]
  • X. Han, Z. Liang and C. Zhang, Optimal proportional reinsurance with common shock dependence to minimize the probability of drawdown. Ann. Actuar. Sci. 13 (2019) 268–294. [CrossRef] [MathSciNet] [Google Scholar]
  • S. Luo, M. Wang and W. Zhu, Maximizing a robust goal-reaching probability with penalization on ambiguity. J. Comput. Appl. Math. 348 (2019) 261–281. [CrossRef] [MathSciNet] [Google Scholar]
  • M.A. Milevsky and C. Robinson, Self-annuitization and ruin in retirement with discussion. N. Am. Actuar. J. 4 (2000) 112–129. [CrossRef] [MathSciNet] [Google Scholar]
  • V.R. Young, Optimal investment strategy to minimize the probability of lifetime ruin. N. Am. Actuar. J. 8 (2004) 105–126. [MathSciNet] [Google Scholar]
  • S. Wang, Aggregation of correlated risk portfolios: Models and algorithms. Proc. Casualty Actuar. Soc. 85 (1998) 848–939. [Google Scholar]
  • K.C. Yuen, J. Guo and X. Wu, On a correlated aggregate claim model with Poisson and Erlang risk process. Insur.: Math. Econ. 31 (2002) 205–214. [CrossRef] [Google Scholar]
  • K.C. Yuen, J. Guo and X. Wu, On the first time of ruin in the bivariatecompound Poisson model. Insur.: Math. Econ. 38 (2006) 298–308. [CrossRef] [Google Scholar]
  • M. Centeno, Dependent risks and excess of loss reinsurance. Insur.: Math. Econ. 37 (2005) 229–238. [Google Scholar]
  • L. Bai, J. Cai and M. Zhou, Optimal reinsurance policies for an insurer with abivariate reserve risk process in a dynamic setting. Insur.: Math. Econ. 53 (2013) 664–670. [CrossRef] [Google Scholar]
  • K.C. Yuen, Z. Liang and M. Zhou, Optimal proportional reinsurance with common shock dependence. Insur.: Math. Econ. 64 (2015) 1–13. [CrossRef] [Google Scholar]
  • Z. Liang and K.C. Yuen, Optimal dynamic reinsurance with dependent risks: Variance premium principle. Scand. Actuar. J. 2016 (2016) 18–36. [CrossRef] [Google Scholar]
  • X. Liang and V.R. Young, Minimizing the probability of lifetime ruin: Two riskless assets with transaction costs. ASTIN Bull.: J. IAA 49 (2019) 847–883. [CrossRef] [Google Scholar]
  • J. Bi, Z. Liang and K.C. Yuen, Optimal mean variance investment/reinsurance with common shock in a regime-switching market. Math. Methods Oper. Res. 90 (2019) 109–135. [CrossRef] [MathSciNet] [Google Scholar]
  • J. Grandell, Aspects of Risk Theory. Springer-Verlag, New York (1991). [CrossRef] [Google Scholar]

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