Long Memory versus Structural Breaks in Modeling and Forecasting Realized Volatility

By Kyongwook Choi, Wei-Choun Yu, Eric Zivot. 2010

113 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/031aac159fbdbee88284bd0de1b4820a707dee0d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Duc Khuong Nguyen
2. Amine Lahiani
3. Mohamed Arouri
4. Perry Sadorsky
5. George Filis
6. Aldo Levy
7. Stavros Degiannakis *
8. Sang Hoon Kang

In Finance

1. Duc Khuong Nguyen
2. Amine Lahiani
3. Mohamed Arouri
4. Aldo Levy
5. Perry Sadorsky
6. George Filis
7. Stavros Degiannakis *
8. Sang Hoon Kang

Citations in the corpus

• Forecasting the conditional volatility of oil spot and futures prices with structural breaks and long memory models (2012, background): “More importantly, recent research shows that the presence of structural breaks or regime switches can generate “spurious long memory process” in the observed data series (see, e.g., Granger and Hyung, 2004; Choi and Zivot, 2007; Choi et al., 2010).”
• Long memory and regime switching: A simulation study on the Markov Regime-Switching ARFIMA model (2015, unknown): “Apart from the actual persistent effects in ACFs, it is well known that regime switching can also induce long memory (Diebold and Inoue, 2001; Choi et al., 2010; Arouri et al., 2012; Charfeddine and Guégan, 2012; Yalama and Celik, 2013; Wang and Vasilakis, 2012).”