A Combination of NLP and Monte Carlo Technique to Improve Wind Investment Decisions

Antonio Di Bari (), Luca Grilli, Domenico Santoro () and Giovanni Villani ()
Additional contact information
Antonio Di Bari: University of Bari Aldo Moro, Department of Economics and Finance
Domenico Santoro: University of Bari Aldo Moro, Department of Economics and Finance
Giovanni Villani: University of Bari Aldo Moro, Department of Economics and Finance

A chapter in Mathematical and Statistical Methods for Actuarial Sciences and Finance, 2024, pp 119-123 from Springer

Abstract: Abstract Investment decisions in wind projects can be tough considering the uncertain economic performance depending on the stochastic nature of revenues. Thanks to the recent innovation in Natural Language Processing (NLP), this work tries to present an innovative approach based on the Monte Carlo option pricing model and Sentiment Analysis. Treating it as a financial option, the idea is to price the managerial flexibility of changing investment decisions during the project lifetime depending on the wind investment’s profitability. In this way, the Monte Carlo options pricing technique is combined with the sentiment (polarity) score, allowing the modification of transition probabilities from one phase of the investment to another and, consequently, the profitability of the investment.

Keywords: Wind project; Sentiment analysis; Real Options (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:spr:sprchp:978-3-031-64273-9_20

Ordering information: This item can be ordered from
http://www.springer.com/9783031642739

DOI: 10.1007/978-3-031-64273-9_20

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().