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    Time-varying relationship of news sentiment, implied volatility and stock returns

    241466.pdf (309.5Kb)
    Access Status
    Open access
    Authors
    Smales, Lee
    Date
    2016
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Smales, L. 2016. Time-varying relationship of news sentiment, implied volatility and stock returns. Applied Economics. 48 (51): pp. 4942-4960.
    Source Title
    Applied Economics
    DOI
    10.1080/00036846.2016.1167830
    ISSN
    0003-6846
    School
    Department of Finance and Banking
    Remarks

    This is an Author's Original Manuscript of an article published by Taylor & Francis in Applied Economics on 06/04/2016 available online at <a href="http://www.tandfonline.com/">http://www.tandfonline.com/</a> 10.1080/00036846.2016.1167830

    URI
    http://hdl.handle.net/20.500.11937/25651
    Collection
    • Curtin Research Publications
    Abstract

    I examine the relationship between aggregate news sentiment, S&P 500 index (SPX) returns, and changes in the implied volatility index (VIX). I find a significant negative contemporaneous relationship between changes in VIX and both news sentiment and stock returns. This relationship is asymmetric whereby changes in VIX are larger following negative news and/or stock market declines. Vector autoregression (VAR) analysis of the dynamics and cross-dependencies between variables reveals a strong positive relationship between previous and current period changes in implied volatility and stock returns, while current period and lagged news sentiment has a significant positive (negative) relationship with stock returns (changes in VIX). I develop a simple trading strategy whereby high (low) levels of implied volatility signal attractive opportunities to take short (long) positions in the underlying index, while extremely negative (positive) news sentiment signals opportunities to enter short (long) index positions. The investor fear gauge (VIX) appears to perform better than news sentiment measures in forecasting future returns.

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