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A multistage linear stochastic programming model for optimal corporate debt management

Author

Listed:
  • Valladão, Davi M.
  • Veiga, Álvaro
  • Veiga, Geraldo

Abstract

Large corporations fund their capital and operational expenses by issuing bonds with a variety of indexations, denominations, maturities and amortization schedules. We propose a multistage linear stochastic programming model that optimizes bond issuance by minimizing the mean funding cost while keeping leverage under control and insolvency risk at an acceptable level. The funding requirements are determined by a fixed investment schedule with uncertain cash flows. Candidate bonds are described in a detailed and realistic manner. A specific scenario tree structure guarantees computational tractability even for long horizon problems. Based on a simplified example, we present a sensitivity analysis of the first stage solution and the stochastic efficient frontier of the mean-risk trade-off. A realistic exercise stresses the importance of controlling leverage. Based on the proposed model, a financial planning tool has been implemented and deployed for Brazilian oil company Petrobras.

Suggested Citation

  • Valladão, Davi M. & Veiga, Álvaro & Veiga, Geraldo, 2014. "A multistage linear stochastic programming model for optimal corporate debt management," European Journal of Operational Research, Elsevier, vol. 237(1), pages 303-311.
  • Handle: RePEc:eee:ejores:v:237:y:2014:i:1:p:303-311
    DOI: 10.1016/j.ejor.2014.01.028
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    References listed on IDEAS

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    1. Shapiro, Alexander & Tekaya, Wajdi & da Costa, Joari Paulo & Soares, Murilo Pereira, 2013. "Risk neutral and risk averse Stochastic Dual Dynamic Programming method," European Journal of Operational Research, Elsevier, vol. 224(2), pages 375-391.
    2. Petri Hilli & Matti Koivu & Teemu Pennanen & Antero Ranne, 2007. "A stochastic programming model for asset liability management of a Finnish pension company," Annals of Operations Research, Springer, vol. 152(1), pages 115-139, July.
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    4. Kouwenberg, Roy, 2001. "Scenario generation and stochastic programming models for asset liability management," European Journal of Operational Research, Elsevier, vol. 134(2), pages 279-292, October.
    5. Rudloff, Birgit & Street, Alexandre & Valladão, Davi M., 2014. "Time consistency and risk averse dynamic decision models: Definition, interpretation and practical consequences," European Journal of Operational Research, Elsevier, vol. 234(3), pages 743-750.
    6. Balibek, Emre & Köksalan, Murat, 2010. "A multi-objective multi-period stochastic programming model for public debt management," European Journal of Operational Research, Elsevier, vol. 205(1), pages 205-217, August.
    7. Willem Haneveld & Maarten Vlerk, 2006. "Integrated Chance Constraints: Reduced Forms and an Algorithm," Computational Management Science, Springer, vol. 3(4), pages 245-269, September.
    8. Date, P. & Canepa, A. & Abdel-Jawad, M., 2011. "A mixed integer linear programming model for optimal sovereign debt issuance," European Journal of Operational Research, Elsevier, vol. 214(3), pages 749-758, November.
    9. Chiu, Mei Choi & Wong, Hoi Ying, 2012. "Mean–variance asset–liability management: Cointegrated assets and insurance liability," European Journal of Operational Research, Elsevier, vol. 223(3), pages 785-793.
    10. Lewellen, Wilbur G. & Emery, Douglas R., 1986. "Corporate Debt Management and the Value of the Firm," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 21(04), pages 415-426, December.
    11. Stephen P. Bradley & Dwight B. Crane, 1972. "A Dynamic Model for Bond Portfolio Management," Management Science, INFORMS, vol. 19(2), pages 139-151, October.
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    1. repec:eee:insuma:v:77:y:2017:i:c:p:177-188 is not listed on IDEAS
    2. repec:kap:compec:v:51:y:2018:i:4:d:10.1007_s10614-017-9656-x is not listed on IDEAS
    3. repec:spr:annopr:v:258:y:2017:i:2:d:10.1007_s10479-015-1963-9 is not listed on IDEAS
    4. Shaik, Saleem, 2015. "Impact of liquidity risk on variations in efficiency and productivity: A panel gamma simulated maximum likelihood estimation," European Journal of Operational Research, Elsevier, vol. 245(2), pages 463-469.
    5. repec:eee:transe:v:105:y:2017:i:c:p:1-17 is not listed on IDEAS

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