Non-Linear Forecasting FTSE Returns: Does Volume Help?

David Gordon McMillan

    Research output: Contribution to journalArticlepeer-review

    26 Citations (Scopus)

    Abstract

    The testing for and estimation of non-linear dynamics in equity returns is a growing area of empirical finance research. This paper extends this line of research by examining whether a hitherto unconsidered variable, namely volume, imparts nonlinear dynamics within equity returns and whether it has forecasting power. A significant amount of evidence supports a negative relationship between volume and future returns, which in turn suggests that volume could act as a suitable threshold variable. The results presented here provide evidence of a logistic smooth-transition model for four international stock market returns, with lagged volume as the threshold. Further, this model provides better out-of-sample forecasts than a corresponding logistic smooth-transition autoregressive model, a simple AR model and a random walk model based on a trading rule. In addition, this model also provides better forecasting performance in three cases against alternate non-linear specifications. This provides evidence in favour of non-linear dynamics, in contrast with previous evidence, which had suggested the relative failure of non-linear models in forecasting exercises. (c) 2006 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.

    Original languageEnglish
    Pages (from-to)115-126
    Number of pages12
    JournalInternational Journal of Forecasting
    Volume23
    DOIs
    Publication statusPublished - 2007

    Keywords

    • stock market returns
    • volume
    • LSTR model
    • forecasting
    • TRANSITION AUTOREGRESSIVE MODELS
    • TIME-SERIES
    • TECHNICAL ANALYSIS
    • MARKET RETURNS
    • TRADING VOLUME
    • PREDICTABILITY
    • ADJUSTMENT
    • COINTEGRATION
    • PERSPECTIVE
    • RATES

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