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A multistage linear stochastic programming model for optimal corporate debt management

Listed author(s):
  • Valladão, Davi M.
  • Veiga, Álvaro
  • Veiga, Geraldo
Registered author(s):

    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.

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    Article provided by Elsevier in its journal European Journal of Operational Research.

    Volume (Year): 237 (2014)
    Issue (Month): 1 ()
    Pages: 303-311

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    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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    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. Willem Klein Haneveld & Matthijs Streutker & Maarten Vlerk, 2010. "An ALM model for pension funds using integrated chance constraints," Annals of Operations Research, Springer, vol. 177(1), pages 47-62, June.
    6. 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.
    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. 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.
    9. 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.
    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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