IDEAS home Printed from
   My bibliography  Save this article

Multi-product newsvendor problem with value-at-risk considerations


  • Özler, Aysun
  • Tan, BarIs
  • Karaesmen, Fikri


We consider the single period stochastic inventory (newsvendor) problem with downside risk constraints. The aim in the classical newsvendor problem is maximizing the expected profit. This formulation does not take into account the risk of earning less than a desired target profit or losing more than an acceptable level due to the randomness of demand. We utilize Value at Risk (VaR) as the risk measure in a newsvendor framework and investigate the multi-product newsvendor problem under a VaR constraint. To this end, we first derive the exact distribution function for the two-product newsvendor problem and develop an approximation method for the profit distribution of the N-product case (N>2). A mathematical programming approach is used to determine the solution of the newsvendor problem with a VaR constraint. This approach allows us to handle a wide range of cases including the correlated demand case that yields new results and insights. The accuracy of the approximation method and the effects of the system parameters on the solution are investigated numerically.

Suggested Citation

  • Özler, Aysun & Tan, BarIs & Karaesmen, Fikri, 2009. "Multi-product newsvendor problem with value-at-risk considerations," International Journal of Production Economics, Elsevier, vol. 117(2), pages 244-255, February.
  • Handle: RePEc:eee:proeco:v:117:y:2009:i:2:p:244-255

    Download full text from publisher

    File URL:
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    1. Luciano, Elisa & Peccati, Lorenzo & Cifarelli, Donato M., 2003. "VaR as a risk measure for multiperiod static inventory models," International Journal of Production Economics, Elsevier, vol. 81(1), pages 375-384, January.
    2. Maurice E. Schweitzer & Gérard P. Cachon, 2000. "Decision Bias in the Newsvendor Problem with a Known Demand Distribution: Experimental Evidence," Management Science, INFORMS, vol. 46(3), pages 404-420, March.
    3. Louis Eeckhoudt & Christian Gollier & Harris Schlesinger, 1995. "The Risk-Averse (and Prudent) Newsboy," Management Science, INFORMS, vol. 41(5), pages 786-794, May.
    4. Isabelle Huault & V. Perret & S. Charreire-Petit, 2007. "Management," Post-Print halshs-00337676, HAL.
    5. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    6. E. Sankarasubramanian & S. Kumaraswamy, 1983. "Note---Note on "Optimal Ordering Quantity to Realize a Pre-Determined Level of Profit"," Management Science, INFORMS, vol. 29(4), pages 512-514, April.
    7. Gotoh, Jun-ya & Takano, Yuichi, 2007. "Newsvendor solutions via conditional value-at-risk minimization," European Journal of Operational Research, Elsevier, vol. 179(1), pages 80-96, May.
    8. Tapiero, Charles S., 2005. "Value at risk and inventory control," European Journal of Operational Research, Elsevier, vol. 163(3), pages 769-775, June.
    9. Vishal Gaur & Sridhar Seshadri, 2005. "Hedging Inventory Risk Through Market Instruments," Manufacturing & Service Operations Management, INFORMS, vol. 7(2), pages 103-120, April.
    10. Katerina Simons, 1996. "Value at risk: new approaches to risk management," New England Economic Review, Federal Reserve Bank of Boston, issue Sep, pages 3-13.
    11. Zhou, Yan-ju & Chen, Xiao-hong & Wang, Zong-run, 2008. "Optimal ordering quantities for multi-products with stochastic demand: Return-CVaR model," International Journal of Production Economics, Elsevier, vol. 112(2), pages 782-795, April.
    Full references (including those not matched with items on IDEAS)


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:proeco:v:117:y:2009:i:2:p:244-255. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Haili He). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.