Stock market declines and market fundamentals / Ho Yew Joe

Ho, Yew Joe (2017) Stock market declines and market fundamentals / Ho Yew Joe. PhD thesis, University of Malaya.

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      This research investigates if market fundamentals are significant in predicting stock market declines in an ex-ante fashion. The dates of stock market declines are determined via a list of ex-post models which comprise the approaches of parametric, non-parametric, semi-parametric and scale-invariant. This includes the Markov-switching model (with various extractions of probabilities for predictability tests), naïve moving average, Brys-Boschan algorithm (the Lunde & Timmermann variant and Candelon, Piplak & Straetman variant), and the integrated identifications with the JLS model and JLS "negative bubble" model. This research also improvises the existing methodologies and introduces the semi-parametric model of “naïve moving average negative return” in identifying bear market and in using the “dichotomised smoothed probabilities” which is transformed from the output of the Markov-switching model for predictability tests. Market fundamentals such as dividend growth, change in the cyclically adjusted price earnings ratio, change in Commerce Department composite index of 11 leading indicators, term spreads (both 3M-10Y and 5M-10Y), Chicago Fed National Activity Index and ISM manufacturing survey (inventories index) are found to be among the most consistent best predictors for stock market declines. The significance of these market fundamentals varies according to different forecasting horizons.

      Item Type: Thesis (PhD)
      Additional Information: Thesis (PhD) – Faculty of Economics & Administration, University of Malaya, 2017.
      Uncontrolled Keywords: Stock market declines; Dividend growth; Forecasting horizons; ISM manufacturing survey; Market fundamentals
      Subjects: H Social Sciences > HC Economic History and Conditions
      Divisions: Faculty of Economics & Administration
      Depositing User: Mr Mohd Safri Tahir
      Date Deposited: 02 Nov 2017 16:33
      Last Modified: 03 Jun 2020 03:54

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