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Distinguishing short and long memory volatility specifications

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Distinguishing short and long memory volatility specifications. / Pong, S; Shackleton, M B; Taylor, S J.
In: The Econometrics Journal, Vol. 11, No. 3, 2008, p. 617-637.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Pong, S, Shackleton, MB & Taylor, SJ 2008, 'Distinguishing short and long memory volatility specifications', The Econometrics Journal, vol. 11, no. 3, pp. 617-637. https://doi.org/10.1111/j.1368-423X.2008.00251.x

APA

Pong, S., Shackleton, M. B., & Taylor, S. J. (2008). Distinguishing short and long memory volatility specifications. The Econometrics Journal, 11(3), 617-637. https://doi.org/10.1111/j.1368-423X.2008.00251.x

Vancouver

Pong S, Shackleton MB, Taylor SJ. Distinguishing short and long memory volatility specifications. The Econometrics Journal. 2008;11(3):617-637. doi: 10.1111/j.1368-423X.2008.00251.x

Author

Pong, S ; Shackleton, M B ; Taylor, S J. / Distinguishing short and long memory volatility specifications. In: The Econometrics Journal. 2008 ; Vol. 11, No. 3. pp. 617-637.

Bibtex

@article{f19ab4fea15b489ea9e6968a0de36c09,
title = "Distinguishing short and long memory volatility specifications",
abstract = "Asset price volatility appears to be more persistent than can be captured by individual, short memory, autoregressive or moving average components. Fractional integration offers a very parsimonious and tempting formulation of this long memory property of volatility but other explanations such as structural models (aggregates of several autoregressive components) are possible. Given the ability of the latter to mimic the former, we investigate the extent to which it is possible to distinguish short from long memory volatility specifications. For a likelihood ratio test in the spectral domain, we investigate size and power characteristics by Monte Carlo simulation. Finally applying the same test to Sterling/Dollar returns, we draw conclusions about the minimum number of structural factors that must be present to mimic the long memory volatility properties that are empirically observed.",
author = "S Pong and Shackleton, {M B} and Taylor, {S J}",
year = "2008",
doi = "10.1111/j.1368-423X.2008.00251.x",
language = "English",
volume = "11",
pages = "617--637",
journal = "The Econometrics Journal",
issn = "1368-4221",
publisher = "Wiley-Blackwell",
number = "3",

}

RIS

TY - JOUR

T1 - Distinguishing short and long memory volatility specifications

AU - Pong, S

AU - Shackleton, M B

AU - Taylor, S J

PY - 2008

Y1 - 2008

N2 - Asset price volatility appears to be more persistent than can be captured by individual, short memory, autoregressive or moving average components. Fractional integration offers a very parsimonious and tempting formulation of this long memory property of volatility but other explanations such as structural models (aggregates of several autoregressive components) are possible. Given the ability of the latter to mimic the former, we investigate the extent to which it is possible to distinguish short from long memory volatility specifications. For a likelihood ratio test in the spectral domain, we investigate size and power characteristics by Monte Carlo simulation. Finally applying the same test to Sterling/Dollar returns, we draw conclusions about the minimum number of structural factors that must be present to mimic the long memory volatility properties that are empirically observed.

AB - Asset price volatility appears to be more persistent than can be captured by individual, short memory, autoregressive or moving average components. Fractional integration offers a very parsimonious and tempting formulation of this long memory property of volatility but other explanations such as structural models (aggregates of several autoregressive components) are possible. Given the ability of the latter to mimic the former, we investigate the extent to which it is possible to distinguish short from long memory volatility specifications. For a likelihood ratio test in the spectral domain, we investigate size and power characteristics by Monte Carlo simulation. Finally applying the same test to Sterling/Dollar returns, we draw conclusions about the minimum number of structural factors that must be present to mimic the long memory volatility properties that are empirically observed.

U2 - 10.1111/j.1368-423X.2008.00251.x

DO - 10.1111/j.1368-423X.2008.00251.x

M3 - Journal article

VL - 11

SP - 617

EP - 637

JO - The Econometrics Journal

JF - The Econometrics Journal

SN - 1368-4221

IS - 3

ER -