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FT50 UTD24 A*
This paper explores the time-series relation between expected returns and risk for a large cross section of industry and size/book-to-market portfolios. I use a bivariate generalized autoregressive conditional heteroskedasticity (GARCH) model to estimate a portfolio's conditional covariance with the market and then test whether the conditional covariance predicts time–variation in the portfolio's expected return. Restricting the slope to be the same across assets, the risk-return coefficient is highly significant with a risk–aversion coefficient (slope) between one and five. The results are robust to different portfolio formations, alternative GARCH specifications, additional state variables, and small sample biases. When conditional covariances are replaced by conditional betas, the risk premium on beta is estimated to be in the range of 3% to 5% per annum and is statistically significant.
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FT50 UTD24 A*
Long-term reversals in corporate bonds are economically and statistically significant in a comprehensive sample spanning the period 1977 to 2017. Such reversals are stronger for bonds with high credit risk and more binding regulatory, capital, and funding liquidity constraints. Bond long-term reversal is not a manifestation of the equity counterpart and is mainly driven by long-term losers. A long-term reversal factor carries a sizable premium and is not explained by long-established equity and bond market factors. Thus, past returns capture investors’ ex-ante risk assessment and the degree of institutional constraints they face, so losing bonds command higher expected returns.
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FT50 UTD24 A*
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FT50 A*
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FT50 UTD24 A*
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FT50 A*
We examine the role of macroeconomic uncertainty in the cross section of corporate bonds and find a significant uncertainty premium for both investment-grade (IG) (0.40% per month) and non-investment-grade (NIG) (0.81% per month) bonds. The economic-uncertainty premium declines as we progressively remove downgraded bonds, indicating that the premium represents an increase in required returns for bonds with higher credit and macroeconomic risk. The economic-uncertainty premia vary across equities and bonds in a manner consistent with the heterogeneous risk-aversion levels of dominant players in equities (retail investors) versus bonds (institutional investors).
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FT50 UTD24 A*
[We derive a measure of aggregate systemic risk, designated CATFIN, that complements bank-specific systemic risk measures by forecasting macroeconomic downturns six months into the future using out-of-sample tests conducted with U.S., European, and Asian bank data. Consistent with bank "specialness," the CATFIN of both large and small banks forecasts macroeconomic declines, whereas a similarly defined measure for both nonfinancial firms and simulated "fake banks" has no marginal predictive ability. High levels of systemic risk in the banking sector impact the macroeconomy through aggregate lending activity. A conditional asset pricing model shows that CATFIN is priced for financial and nonfinancial firms.]
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