EconPapers    
Economics at your fingertips  
 

Numerical Methods for Stochastic Differential Equations

Geon Ho Choe
Additional contact information
Geon Ho Choe: Korea Advanced Institute of Science and Technology, Department of Mathematical Sciences

Chapter Chapter 8 in Quantitative Methods for Finance with Simulations II, 2026, pp 147-166 from Springer

Abstract: Abstract In this chapter, we introduce numerical methods for solving stochastic differential equations. Stochastic differential equations (SDEs) including the geometric Brownian motion are widely used in the natural sciences and engineering. In finance they are used to model movements of risky asset prices and interest rates. The solutions of SDEs are of a different character compared with the solutions of classical ordinary and partial differential equations in the sense that the solutions of SDEs are stochastic processes. Thus it is a nontrivial matter to measure the efficiency of a given algorithm for finding numerical solutions.

Date: 2026
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:sptchp:978-3-032-12331-2_8

Ordering information: This item can be ordered from
http://www.springer.com/9783032123312

DOI: 10.1007/978-3-032-12331-2_8

Access Statistics for this chapter

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

 
Page updated 2026-05-12
Handle: RePEc:spr:sptchp:978-3-032-12331-2_8