The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Recurrence Quantification Analysis of Financial Markets
Abstract
Recurrence quantification analysis is a nonlinear time series analysis technique that detects deterministic dependencies in time series. This technique is particularly appropriate for modeling financial time series since it requires no assumptions on stationarity, statistical distribution, and minimum number of observations. This chapter illustrates two applications of recurrence quantification analysis to financial data: a set of international stock indices, and zero-coupon yields of US government bonds.
Related Content
|
Yuvika Singh, Esha Bansal, Nisha Chanana.
© 2024.
26 pages.
|
|
Nitish Kumar Minz, Anshika Prakash, Meenal Arora, Rishi Chaudhary, Saurav Dixit.
© 2024.
14 pages.
|
|
Manoj Govindaraj, Chandramowleeswaran Gnanasekaran, R. Kandavel, Parvez Khan, Sinh Duc Hoang.
© 2024.
20 pages.
|
|
Ravishankar Krishnan, Elantheraiyan Perumal, Manoj Govindaraj, Logasakthi Kandasamy.
© 2024.
22 pages.
|
|
Sanjay Taneja, Rishi Prakash Shukla, Amandeep Singh.
© 2024.
11 pages.
|
|
Mune Moğol Sever.
© 2024.
23 pages.
|
|
Sujay Vikram Singh, Terrance Ancheary, Anish Mondal, Shashank Rajauria.
© 2024.
17 pages.
|
|
|