Author
Listed:
- Onur Polat
(Department of Public Finance, Bilecik Seyh Edebali University, Bilecik, Turkiye)
- Rangan Gupta
(Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa)
- Riza Demirer
(Department of Economics and Finance, Southern Illinois University Edwardsville, Edwardsville, IL 62026-1102, USA)
- Elie Bouri
(School of Business, Lebanese American University, Lebanon)
Abstract
This paper extends the discussion on the predictive role of bond market information over the stock market to a novel context by proposing a new predictor of stock market bubbles for the United States (US), namely the implied skewness of the Treasury yield. Using daily data from January 1988 to April 2025, we first implement the Multi-Scale Log-Period Power Law Confidence Indicator (MS-LPPLS-CI) framework to detect positive and negative bubbles at the short-, medium- and long-term. Next, employing a nonparametric causality-in-quantiles framework, we show that bond market signals inferred from the implied skewness of the Treasury yield carry significant predictive content for US and international stock market bubbles. While the predictive effect of Treasury yield skewness is found to be asymmetric across the short-, medium-, and long-term of the positive and negative bubble indicators, the strongest influence is observed at the lowest conditional quantiles of the bubble indicators, suggesting that bond market information captured by forward-looking skewness of interest rate implied by Treasury options can be used to forecast impending crashes in the stock market. These results hold when considering the remaining G7 and BRICS countries, providing support for the determinant role of interest rate signals by the Fed over risky asset dynamics in global stock markets and can be used by investors and policy authorities to have timely insights on imminent boom-bust cycles.
Suggested Citation
Onur Polat & Rangan Gupta & Riza Demirer & Elie Bouri, 2025.
"Implied Skewness of the Treasury Yield: A New Predictor for Stock Market Bubbles,"
Working Papers
202539, University of Pretoria, Department of Economics.
Handle:
RePEc:pre:wpaper:202539
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JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
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