Does the yield curve signal recessions? New evidence from an international panel data analysis

Hasse, Jean‐Baptiste; Lajaunie, Quentin

doi:10.1016/j.qref.2022.01.001

Cited by 15 publications

(3 citation statements)

References 58 publications

(105 reference statements)

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“…Thus, heightened uncertainty about interest rates is associated with a low degree of curvature. This finding accords with numerous studies contending that a decrease in the curvature, manifested in an inverted or flattened yield curve, indicates a subsequent decrease in future output growth and signifies a heightened likelihood of recession (e.g., Chauvet & Senyuz, 2016;Erdogan et al, 2015;Hasse & Lajaunie, 2022;Rudebusch & Williams, 2009).…”

Section: Scientific Backgroundsupporting

confidence: 90%

Interest rate uncertainty and the shape of the yield curve of U.S. treasury bonds

Bayaa,

Qadan

2024

Eurasian Econ Rev

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We decompose the yield curve of U.S. Treasury bonds into three components—the level, slope, and curvature. We then explore the interaction between these factors and uncertainty in the U.S. bond market. We assess this uncertainty using a VIX-style estimate originating in options on the CBOE’s Treasury Note futures. Using monthly data for 2003–2020, we find that interest rate uncertainty drives the evolution in the shape of the yield curve, but not vice versa. Specifically, the bond market’s VIX-style metric not only correlates with but also influences the yield curve’s level and slope. Moreover, increased uncertainty about interest rates is negatively associated with, and can significantly influence, the yield curve’s curvature. The results of this study are crucial for both policymakers and money managers.

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Section: Scientific Backgroundsupporting

confidence: 90%

Interest rate uncertainty and the shape of the yield curve of U.S. treasury bonds

Bayaa,

Qadan

2024

Eurasian Econ Rev

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“…The term spread (TS) is now considered as a transition variable. It is well known that TS is a good predictor of future growth (see, inter alia, Estrella and Hardouvelis (1991), Breitung and Candelon (2006) or more recently Chinn and Kucko (2015) and Hasse and Lajaunie (2022)) and thus should impact mutual fund performance. In Figure 2, it is possible to clearly detect the dot-com bubble, the 2008 crisis and the most recent period where the term spread is below the threshold of 0.49 and turns negative, signalling future weak economic growth.…”

Section: Testing and Estimating The T-icapmmentioning

confidence: 99%

Towards a macroprudential regulatory framework for mutual funds?

et al. 2023

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This paper highlights the procyclical and unstable behaviour of mutual funds, characterized by a varying sensitivity on common asset pricing factors. It proposes a novel factor model that allows for regime changes associated with macroeconomic and financial state variables. Estimated on a panel covering 825 US equity mutual funds over a period of 30 years, it appears that the yield curve, the dividend yield, short term interest rates and the industrial production coincide with regimes switches in the Fama–French factors. Furthermore, the estimated regimes coincide with financial crises and economic downturns, thus confirming the procyclical behaviour of mutual funds' returns. These findings, coupled with the emerging systemic role of mutual funds, promote the consideration for a specific macroprudential regulatory framework targeted at the mutual fund industry.

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“…This includes, for example, Bernanke and Blinder (1992), Plosser and Rouwenhorst (1994), Harvey (1997), Estrella and Mishkin (1997), Ahrens (2002) and Hamilton and Kim (2002). More recent evidence is provided and includes Hvozdenska (2015), Lange (2018) and Hasse and Lajaunie (2022). As with the stock return literature, contrary evidence exists.…”

Section: Introductionmentioning

confidence: 99%

Do financial markets predict macroeconomic performance? US evidence from risk‐based measures

McMillan

2023

The Manchester School

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Financial markets are expected to predict macroeconomic conditions as movement in the former depends upon expectations of future performance for the latter.However, existing evidence is mixed. We argue that this arises because the stock return and term structure series typically used in studies, fail to sufficiently capture investor risk preferences. For US data, we use the variance risk premium (VRP) and default yield (DFY) to better capture such a risk measure and demonstrate that these variables exhibit greater evidence of predictive power for key macroeconomic series. In addition to VRP and DFY, we include further variables that may also capture market risk. Given similar dynamics between different risk measures and the potential for multicollinearity in estimation, we consider variable combinations. Using results obtained through predictive regressions, out-of-sample forecasting and a probit model designed to capture periods of expansion and contraction, we show that these combination variables can predict future movements in macroeconomic conditions as well as results using individual variables. Of key interest, combinations that include the VRP and DFY are preferred across all macro-series.

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Does the yield curve signal recessions? New evidence from an international panel data analysis

Cited by 15 publications

References 58 publications

Interest rate uncertainty and the shape of the yield curve of U.S. treasury bonds

Interest rate uncertainty and the shape of the yield curve of U.S. treasury bonds

Towards a macroprudential regulatory framework for mutual funds?

Do financial markets predict macroeconomic performance? US evidence from risk‐based measures

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