ARCH Models and an Application on Exchange Rate Volatility: ARCH and GARCH Models

Lokman Kantar ()
Additional contact information
Lokman Kantar: Istanbul Gelisim University

A chapter in Handbook of Research on Emerging Theories, Models, and Applications of Financial Econometrics, 2021, pp 287-300 from Springer

Abstract: Abstract The financial liberalization that began in the last quarter of the twentieth century caused sudden movements in the currencies and financial assets of the countries. These sudden movements are called volatility. Sudden price changes in financial assets made it difficult to predict the future and increased the risks of financial assets. Investors wishing to invest in financial assets wanted to estimate the price of assets correctly to minimize their risks; this has revealed the need for accurate determination of volatility. Since the changes in asset prices are not linear, volatilities in prices are determined by nonlinear methods. This chapter discusses the GARCH models (GARCH, GJR, EGARCH), which are nonlinear models, and tests the validity of these models through a Turkey application on exchange rate volatility. The findings of the study have indicated that the GARCH (1,1) model successfully explained the volatility in the exchange rate.

Keywords: Volatility; ARCH; GARCH; EGARCH; TGARCH; Exchange Rate (search for similar items in EconPapers)
Date: 2021
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:978-3-030-54108-8_12

Ordering information: This item can be ordered from
http://www.springer.com/9783030541088

DOI: 10.1007/978-3-030-54108-8_12

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 ().