### Abstract

Lingua originale | English |
---|---|

pagine (da-a) | 159-172 |

Numero di pagine | 13 |

Rivista | Annals of Operations Research |

Volume | 193 |

Stato di pubblicazione | Published - 2012 |

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### All Science Journal Classification (ASJC) codes

- Decision Sciences(all)
- Management Science and Operations Research

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*Annals of Operations Research*,

*193*, 159-172.

**A stochastic programming model for the optimal
issuance of government bonds.** / Staino, A.

Risultato della ricerca: Article

*Annals of Operations Research*, vol. 193, pagg. 159-172.

}

TY - JOUR

T1 - A stochastic programming model for the optimal issuance of government bonds

AU - Staino, A

AU - Consiglio, Andrea

PY - 2012

Y1 - 2012

N2 - Sovereign states issue fixed and floating securities to fund their public debt. The value of such portfolios strongly depends on the fluctuations of the term structure of interest rates. This is a typical example of planning under uncertainty, where decisions have to be taken on the base of the key stochastic economic factors underneath the model. We propose a multistage stochastic programming model to select portfolios of bonds, where the aim of the decision maker is to minimize the cost of the decision process. At the same time, we bound the conditional Value-at-Risk, a measure of risk which accounts for the losses of the tail distribution. We build an efficient frontier to trade-off the optimal cost versus the conditional Value-at-Risk and analyse the results obtained.

AB - Sovereign states issue fixed and floating securities to fund their public debt. The value of such portfolios strongly depends on the fluctuations of the term structure of interest rates. This is a typical example of planning under uncertainty, where decisions have to be taken on the base of the key stochastic economic factors underneath the model. We propose a multistage stochastic programming model to select portfolios of bonds, where the aim of the decision maker is to minimize the cost of the decision process. At the same time, we bound the conditional Value-at-Risk, a measure of risk which accounts for the losses of the tail distribution. We build an efficient frontier to trade-off the optimal cost versus the conditional Value-at-Risk and analyse the results obtained.

KW - Stochastic programming; sovereign debt; optimal debt issuance; debt structuring

UR - http://hdl.handle.net/10447/61177

M3 - Article

VL - 193

SP - 159

EP - 172

JO - Annals of Operations Research

JF - Annals of Operations Research

SN - 0254-5330

ER -