Modeling long memory in stock market volatility

By Ming Liu. 2000

122 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/7403ee87ca3e764f54497494c7caa4c1371db5eb

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Citations in the corpus

Breaks and persistency: macroeconomic causes of stock market volatility (2006, background): “Some recent contributions have cast doubts on the hypothesis that long memory is a real feature of the data generating process of the volatility of financial returns (Granger and Hyung [46], Mikosch and Starica [70], Liu [63], Ryden et al.”
Recent Advances in ARCH Modelling (2007, methodology): “Liu (2000), Leipus et al. (2003) discussed regime switching SV model r t = σ t ε t , where volatility σ t = ζ j , S j−1 < t ≤ S j (48) assumes i.i.d. values ζ j > 0 on random intervals (S j−1 , S j ] of a stationary renewal process with i.i.d. durations U j = S j − S j−1 .”
Simulation-Based Method of Moments and Efficiency (2002, background): “…volatility models by Monfardini (1998), Calzolari, De Iori, and Firorentini (1998), and Pastorello, Renault, and Touzi (2000); to models of unemployment by Magnac, Robin, and Visser (1995), An and Liu (2000), and Topa (2001); and to rational expectation dynamic models by Collard et al. (2000).”
Modelling structural breaks, long memory and stock market volatility: an overview (2005, background): “From a different viewpoint, Liu (2000) studies the case of high persistence/long memory in volatility caused by regime switching.”
Long range dependence in financial markets (2005, unknown): “As argued by Liu [41], though the presence of a Markovian regime switching mechanism in volatility can lead to volatility clustering, is not sufficient to generate long-range dependence in absolute returns.”
Level Shifts and the Illusion of Long Memory in Economic Time Series (2004, methodology): “McCulloch and Tsay (1993) used the Gibbs sampler to estimate a RLS model of retail gasoline prices.”