Identification of the Demand Curve and Forecasts in Subsequent Periods Using the Metropolis-Hastings Algorithm

Lukasz Golabek, Konrad Gauda, Krzysztof Zuk and Edward Kozlowski

European Research Studies Journal, 2021, vol. XXIV, issue Special 1 - Part 2, 523-533

Abstract: Purpose: The main purpose of the article is to identify the demand curve and to forecast demand in subsequent periods using the Metropolis-Hastings algorithm. Design/Methodology/Approach: The Metropolis-Hastings algorithm belonging to the Markov Chain Monte Carlo was used to identify the demand curve and to forecast the demand in subsequent periods. This method consists in generating (drawing) a sample in accordance with the modified distribution and the possibility of rejecting a new sample in case of insufficient improvement of the quality index. Findings: The results of the conducted research indicate that the presented solution of generating a sample in accordance with the modified distribution and the possibility of rejecting a new sample in the event of insufficient improvement of the quality index is effective in identifying and forecasting the demand. Practical Implications: The algorithm presented in the article can be used to forecast stays taking into account the product life curve. Originality/Value: A novelty is the use of the Metropolis-Hastings algorithm to identify the demand curve and the forecast of demand in subsequent periods to determine the strategy of long-term products by analyzing the sales volume of the product.

Keywords: Machine learning; Markov Chain Monte Carlo; Metropolis-Hastings algorithm; forecasting. (search for similar items in EconPapers)
JEL-codes: C50 C53 O10 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://ersj.eu/journal/2282/download (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ers:journl:v:xxiv:y:2021:i:special1-part2:p:523-533

Access Statistics for this article

More articles in European Research Studies Journal from European Research Studies Journal
Bibliographic data for series maintained by Marios Agiomavritis ().