Occasional structural breaks and long memory with an application to the S&P 500 absolute stock returns

By Clive W. J. Granger, Namwon Hyung. 2004

828 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/786a88eb0b7a34f19bdd63a5079a74bafd9f3552

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Citations in the corpus

Long memory and regime switching: A simulation study on the Markov Regime-Switching ARFIMA model (2015, neutral): “Thus, the long memory observed for such data is “spurious”, as it could be caused by the regime switching (Mikosch and Starica, 2004; Granger and Hyung, 2004; Charfeddine and Guégan, 2012).”
Volatility is rough (2014, neutral): “edu Hull and White (1993), the Heston model Heston (1993) and the SABR model Hagan et al.”
Simple (but effective) tests of long memory versus structural breaks (2006, methodology): “The stated result then follows because (W (0) n ,W (1) n , · · · ,W (b) n ) →d N (0,Ω) from (27) in the proof of Lemma 2.”
Modelling long memory volatility in the Bitcoin market: Evidence of persistence and structural breaks (2018, background): “9 On the other hand, many authors argue that long memory can be a spurious phenomenon caused by the existence of structural breaks not taking into account (Diebold and Inoue, 2001; Granger and Hyung, 2004).”
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).”
An Analytical Evaluation of the Log-periodogram Estimate in the Presence of Level Shifts (2006, background): “The basis of the algorithm is the fact that conditional on J(1)∗ = u, we have (d̂− 1) =MT (u) + √ m ST HT (u) + op(1) withMT (u) defined by (14),HT (u) ∼ N(0, V2(u))with V2(u) = p limT→∞(1/4m) Pm j=1 a 2 j(ΛT,j− ET,j|u)(2) as defined by (16) and with ΛT,j defined by (12).”
The Volatility of Realized Volatility (2005, background): “A profoundly different view on the source of long memory is instead offered by, among others, Diebold and Inoue (2001), Gourieroux and Jasiak (2001), Granger and Hyung (2004), Granger and Teräsvirta (1999), and Mikosch and Starica (2004), who provide theoretical justification and Monte Carlo…”
Long Memory versus Structural Breaks in Modeling and Forecasting Realized Volatility (2010, neutral): “…of stationary series (Granger and Ding 1996); (2) mixture of numerous heterogeneous short-run information arrivals (Andersen and Bollerslev 1997); (3) non-linear models, such as structural breaks (changes) or regime switches (Granger and Hyung 2004; Choi and Zivot 2006; Diebold and Inoue 2001).”
Nonlinearity in cap-and-trade systems: The EUA price and its fundamentals (2013, methodology): “The model allows for structural changes in financial volatility, which may generate the observed persistence in volatility, see e.g. Diebold and Inoue (2001), Granger and Hyung (2004) and Mikosch and Stărică (2004).”
A simple test of changes in mean in the possible presence of long‐range dependence (2011, background): “Related references on the issue of spurious long memory include: Granger and Hyung (2004), Lobato and Savin (1998), Mikosch and Stărică (2004), Perron and Qu (2007) and Teverovsky and Taqqu (1997), among others.”
Testing for Structural Breaks in Variance with Additive Outliers and Measurement Errors (2006, background): “…there is a growing interest to analyze variance stability in financial markets (see, among others, De Santis and Imrohoroglu 1997) and the effects of neglected breaks in time-series modelling (see Lamoureaux and Lastrapes 1990, Granger and Hyung 2004, Mikosch and Stărică 2004, and Hillebrand 2005).”
A Practical Guide to Forecasting Financial Market Volatility (2005, methodology): “Examples of such nonlinear models include the break model (Granger and Hyung, 2004), the volatility component model (Engle and Lee, 1999), and the regime-switching model (Hamilton and Susmel, 1994; Diebold and Inoue, 2001).”