Mortgage Timing

The fraction of newly-originated mortgages that are of the adjustable-rate (ARM) versus the fixed-rate (FRM) type exhibits a surprising amount of time variation. A simple utility framework of mortgage choice points to the bond risk premium as theoretical determinant: when the bond risk premium is high, FRM payments are high, making ARMs more attractive. We confirm empirically that the bulk of the time variation in household mortgage choice can be explained by time variation in the bond risk premium. This is true regardless of whether bond risk premia are measured using forecasters' data, a VAR term structure model, or a simple rule-of-thumb based on adaptive expectations. This simple rule-of-thumb moves in lock-step with mortgage choice, thereby lending further credibility to a theory of strategic mortgage timing by households.

Optimal Decentralized Investment Management

We study a decentralized investment problem in which a CIO employs multiple asset managers to implement and execute investment strategies in separate asset classes. The CIO allocates capital to the managers who, in turn, allocate these funds to the assets in their asset class. This two-step investment process causes several misalignments of objectives between the CIO and his managers and can lead to large utility costs on the part of the CIO. We focus on i) loss of diversification ii) different appetites for risk, iii) different investment horizons, and iv) the presence of liabilities. We derive an optimal unconditional linear performance benchmark and show that this benchmark can be used to better align incentives within the firm. The optimal benchmark substantially mitigates the utility costs of decentralized investment management. These costs can be further reduced when the CIO can screen asset managers on the basis of their risk appetites. Each manager%u2019s optimal level of risk aversion depends on the asset class he manages and can differ substantially from the CIO%u2019s level of risk aversion.

Wave transformation across a macrotidal shore platform under low to moderate energy conditions

We investigate how waves are transformed across a shore platform as this is a central question in rock coast geomorphology. We present results from deployment of three pressure transducers over four days, across a sloping, wide (~200 m) cliff-backed shore platform in a macrotidal setting, in South Wales, United Kingdom. Cross shore variations in wave heights were evident under the predominantly low to moderate (significant wave height < 1.4 m) energy conditions measured. At the outer transducer 50 m from the seaward edge of the platform (163 m from the cliff) high tide water depths were 8+ m meaning that waves crossed the shore platform without breaking. At the mid platform position water depth was 5 m. Water depth at the inner transducer (6 m from the cliff platform junction) at high tide was 1.4 m. This shallow water depth forced wave breaking, thereby limiting wave heights on the inner platform. Maximum wave height at the middle and inner transducers were 2.41 and 2.39 m respectively and significant wave height 1.35 m and 1.34 m respectively. Inner platform high tide wave heights were generally larger where energy was up to 335% greater than near the seaward edge where waves were smaller. Infragravity energy was less than 13% of the total energy spectra with energy in the swell, wind and capillary frequencies accounting for 87% of the total energy. Wave transformation is thus spatially variable and is strongly modulated by platform elevation and the tidal range. While shore platforms in microtidal environments have been shown to be highly dissipative, in this macro-tidal setting up to 90% of the offshore wave energy reached the landward cliff at high tide, so that the shore platform cliff is much more reflective

Predictability of Returns and Cash Flows

We review the literature on return and cash flow growth predictability form the perspective of the present-value identity. We focus predominantly on recent work. Our emphasis is on U.S. aggregate stock return predictability, but we also discuss evidence from other asset classes and countries.

The Term Structure of Interest Rates in a DSGE Model with Recursive Preferences

We solve a dynamic stochastic general equilibrium (DSGE) model in which the representative household has Epstein and Zin recursive preferences. The parameters governing preferences and technology are estimated by means of maximum likelihood using macroeconomic data and asset prices, with a particular focus on the term structure of interest rates. We estimate a large risk aversion, an elasticity of intertemporal substitution higher than one, and substantial adjustment costs. Furthermore, we identify the tensions within the model by estimating it on subsets of these data. We conclude by pointing out potential extensions that might improve the model’s fit.DSGE models, Epstein-Zin preferences, likelihood estimation, yield curve

Mortgage Timing

Mortgages can be broadly classified into adjustable-rate mortgages (ARMs) and fixed-rate mortgages (FRMs). We document a surprising amount of time variation in the fraction of newly-originated mortgages that are of either type in the US and UK. A simple utility framework points to the importance of term structure variables in explaining this variation. In particular, the inflation risk premium, real interest rate risk premium and both the real rate and expected inflation volatility arise as potential determinants. We use a flexible VAR-model to measure these four term structure variables and show that they account for the bulk of variation in the ARM share. Risk premia alone explain sixty percent of the time variation in mortgage choice. Other term structure variables, such as the yield spread, seem only weakly related to the ARM share. We uncover interesting differences between the US and the UK. In the US, the inflation risk premium is most strongly related to the ARM share, while in the UK it is the real rate risk premium. In the US, FRMs contain a prepayment option. We analyze the impact of the prepayment option on optimal mortgage choice

Predictive Regressions: A Present-value Approach

We propose a latent variables approach within a present-value model to estimate the expected returns and expected dividend growth rates of the aggregate stock market. This approach aggregates information contained in the history of price-dividend ratios and dividend growth rates to predict future returns and dividend growth rates. We find that returns and dividend growth rates are predictable with R-squared values ranging from 8.2% to 8.9% for returns and 13.9% to 31.6% for dividend growth rates. Both expected returns and expected dividend growth rates have a persistent component, but expected returns are more persistent than expected dividend growth rates.

The Cross-Section and Time-Series of Stock and Bond Returns

Value stocks have higher exposure to innovations in the nominal bond risk premium, which measures the markets' perception of cyclical variation in future output growth, than growth stocks. The ICAPM then predicts a value risk premium provided that good news about future output lowers the marginal utility of investors' wealth today. In support of the business cycle as a priced state variable, we show that low value minus growth returns, typically realized at the start of recessions when nominal bond risk premia are low and declining, are associated with lower future dividend growth rates on value minus growth and with lower future output growth in the short term. Because of this new nexus between stock and bond returns, a parsimonious three-factor model can jointly price the book-to-market stock and maturity-sorted bond portfolios and reproduce the time-series variation in expected bond returns. Structural dynamic asset pricing models need to impute a central role to the business cycle as a priced state variable to be quantitatively consistent with the observed value, equity, and nominal bond risk premia.

Complex shock structure in the western hot-spot of Pictor A

We have carried out simulations of supersonic light jets in order to model the features observed in optical and radio images of the western hot-spot in the radio galaxy Pictor A. We have considered jets with density ratios η =10[superscript −2] − 10[superscript −4], and Mach numbers ranging between 5 and 50. From each simulation, we have generated raytraced maps of radio surface brightness at a variety of jet inclinations, in order to study the appearance of time-dependent luminous structures in the vicinity of the western hotspot. We compare these rendered images with observed features of Pictor A. A remarkable feature of Pictor A observations is a bar-shaped “filament” inclined almost at right angles to the inferred jet direction and extending 24" (10.8h[superscript −1] kpc) along its longest axis. The constraints of reproducing the appearance of this structure in simulations indicate that the jet of Pictor A lies nearly in the plane of the sky. The results of the simulation are also consistent with other features found in the radio image of Pictor A. This filament arises from the surging behaviour of the jet near the hot-spot; the surging is provoked by alternate compression and decompression of the jet by the turbulent backflow in the cocoon. We also examine the arguments for the jet in Pictor A being at a more acute angle to the line of sight and find that our preferred orientation is just consistent with the limits on the brightness ratio of the X-ray jet and counter-jet. We determine from our simulations, the structure function of hot-spot brightness and also the cumulative distribution of the ratio of intrinsic hot-spot brightnesses. The latter may be used to quantify the use of hot-spot ratios for the estimation of relativistic effects

On the Timing and Pricing of Dividends

We recover prices of dividend strips on the aggregate stock market using data from derivatives markets. The price of a k-year dividend strip is the present value of the dividend paid in k years. The value of the stock market is the sum of all dividend strip prices across maturities. We study the properties of strips and find that expected returns, Sharpe ratios, and volatilities on short-term strips are higher than on the aggregate stock market, while their CAPM betas are well below one. Short-term strip prices are more volatile than their realizations, leading to excess volatility and return predictability.