Demand Forecasting Method Based on Stochastic Processes and Its Validation Using Real-World Data

Autor:	Yinggao Zheng, Hideo Kawarada, Hiroshi Suito
Rok vydání:	2009
Předmět:	Financial engineering Supply chain management Computer science Valuation of options Stochastic process Econometrics Option price Demand forecasting Newsvendor model Real world data
Zdroj:	Computational Methods in Applied Sciences ISBN: 9789048132386
DOI:	10.1007/978-90-481-3239-3_11
Popis:	Demand forecasting problems frequently arise in logistics and supply chain management. The Newsboy Problem is one such problem. In this paper, we present an improved solution method using application of the Black–Scholes model incorporating stochastic processes used in financial engineering for option pricing. Through numerical experiments using real-world data, the proposed model is demonstrated to be effective.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::eaf3c852e6eaf59016703a4a7f98ed20 https://doi.org/10.1007/978-90-481-3239-3_11 Zobrazit plný text záznamu