Financial Analytics and A Binomial Pricing Model

Charles S. Tapiero () and Jiangyi Qi
Additional contact information
Charles S. Tapiero: New York University Polytechnic School of Engineering
Jiangyi Qi: New York University Polytechnic School of Engineering

A chapter in Future Perspectives in Risk Models and Finance, 2015, pp 287-313 from Springer

Abstract: Abstract The physical fact that we are always in a present has motivated our quest to define a virtual past (model) as a memory and a virtual future as a rational expectation of future prices (though current option prices for example). To frame a future in a cognitive manner, “expectations-models” and scenarios generating approaches are constructed based on experience, memory, information, needs and attitudes. These are the factors that define our predictions and expectations of future financial prices for example. In a broad sense, we do have memory of stock prices and these dictate our actions that contribute to financial modeling by the manners we use to structure both memory and future expectations. This paper considers a binomial memory-less price model and memory prone extensions including Short run and Bayesian Learning models.

Keywords: Financial Market; Stock Price; Option Price; Price Model; Future State (search for similar items in EconPapers)
Date: 2015
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:isochp:978-3-319-07524-2_8

Ordering information: This item can be ordered from
http://www.springer.com/9783319075242

DOI: 10.1007/978-3-319-07524-2_8

Access Statistics for this chapter

More chapters in International Series in Operations Research & Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().