Long-Memory in High-Frequency Exchange Rate Volatility under Temporal Aggregations

David Gordon McMillan, A Speight

    Research output: Contribution to journalArticlepeer-review

    3 Citations (Scopus)

    Abstract

    This paper applies log-periodogram estimators of the fractional difference parameter to the volatility of the US dollar exchange rate returns of 11 European currencies, and under temporal aggregation from an underlying half-hourly intra-day frequency. Particular attention is paid to the sequencing of the nonlinear transformation of returns and their temporal aggregation. The results reported confirm that long-memory in absolute returns constitutes an intrinsic and empirically significant characteristic of the exchange rates considered. At the practical level, our results lend support to the proposal that nonlinear transformation prior to temporal aggregation can return meaningful long-memory parameter estimates. Our findings also illustrate the advantages of long-memory parameter estimation based on the smoothed periodogram applied to absolute returns in controlling for noise induced by temporal aggregation in the processing of high-frequency data.

    Original languageEnglish
    Pages (from-to)251-261
    Number of pages11
    JournalQuantitative Finance
    Volume8
    Issue number3
    DOIs
    Publication statusPublished - 2008

    Keywords

    • market efficiency
    • behavioural finance
    • empirical asset pricing
    • mutual funds
    • RANGE DEPENDENCE
    • CONDITIONAL HETEROSKEDASTICITY
    • SEMIPARAMETRIC ESTIMATION
    • STOCHASTIC VOLATILITY
    • MARKET VOLATILITY
    • INTRADAY
    • RETURNS
    • MODEL
    • PERSISTENCE
    • REGRESSION

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