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Filtering of a Partially Observed Inventory System

In: Hidden Markov Models in Finance

Author

Listed:
  • Lakhdar Aggoun

    (Sultan Qaboos University)

Abstract

Summary The vast majority of work done on inventory system is based on the critical assumption of fully observed inventory level dynamics and demands. Modern technology, like the internet, offers a tremendous number of opportunities to businesses to collect imperfect but useful information on potential customers which helps them planning efficiently to meet future demands. For instance visits to commercial web sites provides the management of a business of a source of partial information on future demands. On the other hand it is often the case that it is not economically viable to fully observe the dynamics of inventory levels and only partial information is accessible to the management. In this article, using hidden Markov model techniques we estimate the inventory level as well as future demands of partially observed inventory system. The parameters of the model are updated via the EM algorithm.

Suggested Citation

  • Lakhdar Aggoun, 2007. "Filtering of a Partially Observed Inventory System," International Series in Operations Research & Management Science, in: Rogemar S. Mamon & Robert J. Elliott (ed.), Hidden Markov Models in Finance, chapter 8, pages 121-132, Springer.
    • Handle: RePEc:spr:isochp:978-0-387-71163-8_8
    DOI: 10.1007/0-387-71163-5_8
    as

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