Dissecting the Yield Curve: The International Evidence

We develop a term structure model that decomposes nominal yields into the sum of an expectation, term premium, and convexity term and in turn of their real and inflation counterparts. The model explicitly captures the interrelation between yield-only and macroeconomic factors while allowing for aggregate stochastic volatility. We extract the components from the nominal and real yield curve of the United States, the Euro Area, the United Kingdom, and Japan. We find that short-rate expectations have steadily declined over the last two decades and account for the bulk of yield dynamics. Term premia increase with maturity but explain a smaller fraction of yield forecast error variance than previously documented. With regard to yield comovement, the United States generates the strongest spillovers at the long end of the yield curve, whereas the Japanese market is the top importer of shocks

Valuation in US Commercial Real Estate

We consider a log-linearized version of a discounted rents model to price commercial real estate as an alternative to traditional hedonic models. First, we verify a key implication of the model, namely, that cap rates forecast commercial real estate returns. We do this using two different methodologies: time series regressions of 21 US metropolitan areas and mixed data sampling (MIDAS) regressions with aggregate REITs returns. Both approaches confirm that the cap rate is related to fluctuations in future returns. We also investigate the provenance of the predictability. Based on the model, we decompose fluctuations in the cap rate into three parts: (i) local state variables (demographic and local economic variables); (ii) growth in rents; and (iii) an orthogonal part. About 30% of the fluctuation in the cap rate is explained by the local state variables and the growth in rents. We use the cap rate decomposition into our predictive regression and find a positive relation between fluctuations in economic conditions and future returns. However, a larger and significant part of the cap rate predictability is due the orthogonal part, which is unrelated to fundamentals. This implies that economic conditions, which are also used in hedonic pricing of real estate, cannot fully account for future movements in returns. We conclude that commercial real estate prices, at least at an aggregate level, are better modeled as financial assets and that the discounted rent model might be more suitable than traditional hedonic models, at least at an aggregate level

Mind the (Convergence) Gap: Bond Predictability Strikes Back!

We show that the difference between the natural rate of interest and the current level of monetary policy stance, which we label Convergence Gap (CG), contains information that is valuable for bond predictability. Adding CG in forecasting regressions of bond excess returns significantly raises the R squared, and restores countercyclical variation in bond risk premia that is otherwise missed by forward rates. Consistent with the argument that CG captures the effect of real imbalances on the path of rates, our factor has predictive ability for real bond excess returns. The importance of the gap remains robust out-of-sample and in countries other than the U.S. Furthermore, its inclusion brings significant economic gains in the context of dynamic conditional asset allocation

Expected returns and expected erowth in rents of commercial real estate

Commercial real estate expected returns and expected rent growth rates are time-varying. Relying on transactions data from a cross-section of U.S. metropolitan areas, we find that up to 30% of the variability of realized returns to commercial real estate can be accounted for by expected return variability, while expected rent growth rate variability explains up to 45% of the variability of realized rent growth rates. The cap rate - that is, the rent-price ratio in commercial real estate - captures fluctuations in expected returns for apartments, retail properties, as well as industrial properties. For offices, by contrast, cap rates do not forecast (in-sample) returns even though expected returns on o±ces are also time-varying. As implied by the present value relation, cap rates marginally forecast o±ce rent growth but not rent growth of apartments, retail properties, and industrial properties. We link these differences in in-sample predictability to differences in the stochastic properties of the underlying commercial real estate data- generating processes. Also, rent growth predictability is observed mostly in locations characterized by higher population density and stringent land use restrictions. The opposite is true for return predictability. The dynamic portfolio implications of time-varying commercial real estate returns are also explored in the context of a portfolio manager investing in the aggregate stock market, Treasury bills, as well as commercial real estate

Inflation Risk Premia, Yield Volatility, and Macro Factors

AbstractWe incorporate a latent stochastic volatility factor and macroeconomic expectations in an affine model for the term structure of nominal and real rates. We estimate the model over 1999–2016 on U.S. data for nominal and TIPS yields, the realized and implied volatility of T-bonds, and survey forecasts of GDP growth and inflation. We find relatively stable inflation risk premia averaging at 40 basis points at the long-end, and which are strongly related to the volatility factor and conditional mean of output growth. We also document real risk premia that turn negative in the post-crisis period, and a non-negligible variance risk premium.</jats:p

The Brain Correlates of Laugh and Cataplexy in Childhood Narcolepsy

The brain suprapontine mechanisms associated with human cataplexy have not been clarified. Animal data suggest that the amygdala and the ventromedial prefrontal cortex are key regions in promoting emotion-induced cataplectic attacks. Twenty-one drug-naive children/adolescent (13 males, mean age 11 years) with recent onset of narcolepsy type 1 (NT1) were studied with fMRI while viewing funny videos using a "naturalistic" paradigm. fMRI data were acquired synchronously with EEG, mylohyoid muscle activity, and the video of the patient's face. Whole-brain hemodynamic correlates of (1) a sign of fun and amusement (laughter) and of (2) cataplexy were analyzed and compared. Correlations analyses between these contrasts and disease-related variables and behavioral findings were performed

Complex movement disorders at disease onset in childhood narcolepsy with cataplexy

Narcolepsy with cataplexy is characterized by daytime sleepiness, cataplexy (sudden loss of bilateral muscle tone triggered by emotions), sleep paralysis, hypnagogic hallucinations and disturbed nocturnal sleep. Narcolepsy with cataplexy is most often associated with human leucocyte antigen-DQB1*0602 and is caused by the loss of hypocretin-producing neurons in the hypothalamus of likely autoimmune aetiology. Noting that children with narcolepsy often display complex abnormal motor behaviours close to disease onset that do not meet the classical definition of cataplexy, we systematically analysed motor features in 39 children with narcolepsy with cataplexy in comparison with 25 age- and sex-matched healthy controls. We found that patients with narcolepsy with cataplexy displayed a complex array of ‘negative’ (hypotonia) and ‘active’ (ranging from perioral movements to dyskinetic–dystonic movements or stereotypies) motor disturbances. ‘Active’ and ‘negative’ motor scores correlated positively with the presence of hypotonic features at neurological examination and negatively with disease duration, whereas ‘negative’ motor scores also correlated negatively with age at disease onset. These observations suggest that paediatric narcolepsy with cataplexy often co-occurs with a complex movement disorder at disease onset, a phenomenon that may vanish later in the course of the disease. Further studies are warranted to assess clinical course and whether the associated movement disorder is also caused by hypocretin deficiency or by additional neurochemical abnormalities

GBA variants in REM sleep behavior disorder: a multicenter study

To study the role of GBA variants in the risk for isolated rapid-eye-movement (REM)-sleep behavior disorder (iRBD) and conversion to overt neurodegeneration

The cross-sectional dispersion of commercial real estate returns and rent growth: time variation and economic fluctuations

We estimate the cross-sectional dispersions of returns and growth in rents for commercial real estate using data on U.S. metropolitan areas over the sample period 1986 to 2002. The cross- sectional dispersion of returns is a measure of the risk faced by commercial real estate investors. We document that, for apartments, offices, industrial and retail properties, the cross-sectional dispersions are time varying. Interestingly, their time-series fluctuations can be explained by macroeconomic variables such as the term and credit spreads, inflation and the short rate of interest. The cross-sectional dispersions also exhibit an asymmetrically larger response to negative economics shocks, which may be attributable to credit channel effects impacting the availability of external debt financing to commercial real estate investments. Finally, we find a statistically reliable positive relation between commercial real estate returns and their cross-sectional dispersion, suggesting that idiosyncratic fluctuations are priced in the commercial real estate market

Valuation in US commercial real estate

We consider a log-linearized version of a discounted rents model to price commercial real estate as an alternative to traditional hedonic models. First, we verify a key implication of the model, namely, that cap rates forecast commercial real estate returns. We do this using two different methodologies: time series regressions of 21 US metropolitan areas and mixed data sampling (MIDAS) regressions with aggregate REIT returns. Both approaches confirm that the cap rate is related to fluctuations in future returns. We also investigate the provenance of the predictability. Based on the model, we decompose fluctuations in the cap rate into three parts: (i) local state variables (demographic and local economic variables); (ii) growth in rents; and (iii) an orthogonal part. About 30% of the fluctuation in the cap rate is explained by the local state variables and the growth in rents. We use the cap rate decomposition into our predictive regression and find a positive relation between fluctuations in economic conditions and future returns. However, a larger and significant part of the cap rate predictability is due to the orthogonal part, which is unrelated to fundamentals. This implies that economic conditions, which are also used in hedonic pricing of real estate, cannot fully account for future movements in returns. We conclude that commercial real estate prices are better modelled as financial assets and that the discounted rent model might be more suitable than traditional hedonic models, at least at an aggregate level