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The role of term spread and pattern changes in predicting stock returns and volatility of the United Kingdom: Evidence from a nonparametric causality-in-quantiles test using over 250 years of data

Rangan Gupta (), Marian Risse, David A. Volkman and Mark Wohar ()

The North American Journal of Economics and Finance, 2019, vol. 47, issue C, 391-405

Abstract: Given the existence of nonlinear relationship between equity premium and term spread, as well as pattern changes and the interaction of pattern changes with the term-spread and changes in the shape of the yield curve, we use a nonparametric k-th order causality-in-quantiles test to predict the movement in excess returns and volatility based on changes in the shape of the yield curve. With the test applied to over 250 years of monthly data for the UK covering the period 1753:08 to 2017:02, we find that pattern changes and the interaction of pattern changes with the term-spread, besides the term spread itself, tends to also play an important role in predicting volatility at the upper end of its conditional distribution. In addition, the effect on excess returns from term spread, pattern changes and the interaction is found to have improved markedly over time, barring at the conditional median of the equity premium. Finally, comparisons are made with historical data of the US and South Africa, and implications of our results are discussed.

Keywords: Stock returns; Volatility; Yield curve changes; Conditional term spreads; Nonparametric causality-in-quantiles test (search for similar items in EconPapers)
Date: 2019
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Working Paper: The Role of Term Spread and Pattern Changes in Predicting Stock Returns and Volatility of the United Kingdom: Evidence from a Nonparametric Causality-in-Quantiles Test Using Over 250 Years of Data (2017)
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