Small sample properties of GARCH estimates and persistence

By Soosung Hwang, Pedro L. Valls Pereira. 2006

148 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/198ee990a69d7a15d5b0aceb5e64c37447c8b3e4

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. Rataporn Deesomsak
2. J. H. Fan
3. Jun Wang
4. N. Todorova
5. Frankie Chau

In Finance

1. Rataporn Deesomsak
2. Jun Wang
3. Frankie Chau

Citations in the corpus

• Bitcoin for energy commodities before and after the December 2013 crash: diversifier, hedge or safe haven? (2017, unknown): “However, given that the available number of weekly observations on Bitcoin prices so far does not exceed 500, then it is difficult to obtain reliable GARCH estimates in smaller samples (Hwang and Pereira 2006).”
• On the return-volatility relationship in the Bitcoin market around the price crash of 2013 (2017, unknown): “5 Each sub-period includes more than 500 observations to ensure a proper GARCH estimation (Hwang and Pereira, 2006). www.economics-ejournal.org 5 As reported in Table 1, Bitcoin return during the pre-crash period is positive, but it becomes negative in the post-crash period.”
• Dynamics of China’s carbon prices in the pilot trading phase (2017, background): “…are significantly negatively biased in small samples and since at least 500 observations are needed to fit a GARCH (1,1) model (which is one of the most parsimonious model forms) to financial return series (Hwang and Pereira, 2006), the small sample size prohibits the use of more elaborate models.”
• Stock Market Volatility around National Elections (2008, unknown): “Guided by these practical considerations and the results of Hwang and Pereira (2006), we have decided to choose an estimation period of 500 trading days.”
• Political uncertainty and stock market volatility in the Middle East and North African (MENA) countries (2014, methodology): “For example, Hwang and Pereira (2006) suggest using at least 500 daily data for proper GARCH estimation.”