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The Role of an Aligned Investor Sentiment Index in Predicting Bond Risk Premia of the United States

Author

Listed:
  • Oguzhan Cepni

    (Central Bank of the Republic of Turkey, Haci Bayram Mah. Istiklal Cad. No:10 06050, Ankara,Turkey)

  • I. Ethem Guney

    (Central Bank of the Republic of Turkey, Haci Bayram Mah. Istiklal Cad. No:10 06050, Ankara,Turkey)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Pretoria, 0002, South Africa)

  • Mark E. Wohar

    (College of Business Administration, University of Nebraska at Omaha, 6708 Pine Street, Omaha, NE 68182, USA; School of Business and Economics, Loughborough University, Leicestershire, LE11 3TU, UK)

Abstract

In this paper, we develop a new investor sentiment index that is aligned with the purpose of predicting the excess returns on government bonds of the United States (US) of maturities of 2-, 3-, 4-, 5-year. By eliminating a common noise component in underlying sentiment proxies using the partial least squares (PLS) approach, the new index is shown to have much greater predictive power than the original principal component analysis (PCA)-based sentiment index both in- and out-of-sample, with the predictability being statistically significant, especially for bond premia with shorter maturities, even after controlling for a large number of financial and macro factors, as well as investor attention and manager sentiment indexes. Given the role of Treasury securities in forecasting of output and inflation, and portfolio allocation decisions, our findings have significant implications for investors, policymakers and researchers interested in accurately forecasting return dynamics for these assets.

Suggested Citation

  • Oguzhan Cepni & I. Ethem Guney & Rangan Gupta & Mark E. Wohar, 2019. "The Role of an Aligned Investor Sentiment Index in Predicting Bond Risk Premia of the United States," Working Papers 201973, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:201973
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    More about this item

    Keywords

    Bond premia; Investor attention; Investor sentiment; Predictability; Out-of-sample forecasts;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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