The optimal use of return predictability : an empirical study

In this paper we study the economic value and statistical significance of asset return predictability, based on a wide range of commonly used predictive variables. We assess the performance of dynamic, unconditionally efficient strategies, first studied by Hansen and Richard (1987) and Ferson and Siegel (2001), using a test that has both an intuitive economic interpretation and known statistical properties. We find that using the lagged term spread, credit spread, and inflation significantly improves the risk-return trade-off. Our strategies consistently outperform efficient buy-and-hold strategies, both in and out of sample, and they also incur lower transactions costs than traditional conditionally efficient strategies

Optimal Compensation for Fund Managers of Uncertain Type: Informational Advantages of Bonus Schemes

Performance-sensitivity of compensation schemes for portfolio managers is well explained by classic principal-agent theory as a device to provide incentives for managers to exert effort or bear the cost of acquiring information. However, the majority of compensation packages observed in reality display in addition a fair amount of convexity in the form of performance-related bonus schemes. While convex contracts may be explained by principal-agent theory in some rather specific situations, they have been criticized, both by the financial press as well as the academic literature, on the grounds that they may lead to excessive risk-taking. In this paper, we show that convex compensation packages, though likely to be myopically not optimal, may serve as a device to extract information about the ex-ante uncertain type of portfolio managers. Optimal contracts are thus determined by the trade-off between maximizing short-run expected returns on one hand, and long-run informational benefits on the other. In a discrete-time model, combining dynamic principal-agent theory with the theory of learning by experimentation, we characterize optimal incentive schemes and optimal retention rules for fund managers, consistent with empirical observations

Market Volatility and Feedback Effects from Dynamic Hedging

In this paper we analyze in what way the demand generated by dynamic hedging strategies affects the equilibrium prices of the underlying asset. We derive an explicit expression for the transformation of market volatility under the impact of hedging. It turns out that market volatility increases and becomes price-dependent. The strength of the effects depend not only on the market share of portfolio insurance but also crucially on the heterogeneity of insured payoffs. We finally discuss in what sense hedging strategies calculated under the assumption of constant volatility are still appropriate, even if this assumption is obviously violated by their implementation.Black--Scholes Model, Dynamic Hedging, Volatility, Option Pricing, Feedback Effects

Using ground-based solar and lunar infrared spectroscopy to study the diurnal trend of carbon monoxide in the Mexico City boundary layer

Carbon monoxide (CO) is an important pollutant in urban agglomerations. Quantifying the total burden of this pollutant in a megacity is challenging because not only its surface concentration but also its vertical dispersion present different behaviours and high variability. The diurnal trend of columnar CO in the boundary layer of Mexico City has been measured during various days with ground-based infrared absorption spectroscopy. Daytime CO total columns are retrieved from solar spectra and for the first time, nocturnal CO total columns using moonlight have been retrieved within a megacity. The measurements were taken at the Universidad Nacional Autónoma de México (UNAM) campus located in Mexico City (19.33° N, 99.18° W, 2260 m a.s.l.) from October 2007 until February 2008 with a Fourier-transform infrared spectrometer at 0.5 cm<sup>−1</sup> resolution. The atmospheric CO background column was measured from the high altitude site Altzomoni (19.12° N, 98.65° W, 4010 m a.s.l.) located 60 km southeast of Mexico City. The total CO column within the city presents large variations. Fresh CO emissions at the surface, the transport of cleaner or more polluted air masses within the field-of-view of the instrument and other processes contribute to this variability. The mean background value above the boundary mixing layer was found to be (8.4±0.5)×10<sup>17</sup> molecules/cm<sup>2</sup>, while inside the city, the late morning mean on weekdays and Sundays was found to be (2.73±0.41)×10<sup>18</sup> molecules/cm<sup>2</sup> and (2.04±0.57)×10<sup>18</sup> molecules/cm<sup>2</sup>, respectively. Continuous CO column retrieval during the day and night (when available), in conjunction with surface CO measurements, allow for a reconstruction of the effective mixing layer height. The limitations from this simplified approach, as well as the potential of using continuous column measurements in order to derive top-down CO emissions from a large urban area, are discussed. Also, further monitoring will provide more insight in daily and weekly emission patterns and a usable database for the quantitative validation of CO from satellite observations in a megacity

Stratospheric and tropospheric NO₂ variability on the diurnal and annual scale: a combined retrieval from ENVISAT/SCIAMACHY and solar FTIR at the Permanent Ground-Truthing Facility Zugspitze/Garmisch

International audienceColumnar NO2 retrievals from solar FTIR measurements at the Zugspitze (47.42° N, 10.98° E, 2964 m a.s.l.), Germany were investigated synergistically with columnar NO2 retrieved from SCIAMACHY data by the University of Bremen scientific algorithm UB1.5 for the time span July 2002-October 2004. A new concept to match FTIR data to the time of satellite overpass makes use of the NO2 daytime increasing rate retrieved from the FTIR data set itself [+1.02(6)E+14 cm-2/h]. This measured increasing rate shows no significant seasonal variation. SCIAMACHY data within a 200-km radius around Zugspitze were considered, and a pollution-clearing scheme was developed to select only pixels corresponding to clean background (free) tropospheric conditions, and exclude local pollution hot spots. The resulting difference between SCIAMACHY and FTIR columns (without correcting for the different sensitivities of the instruments) varies between 0.60-1.24E+15 cm-2 with an average of 0.83E+15 cm-2. A day-to-day scatter of daily means of ?7-10% could be retrieved in mutual agreement from FTIR and SCIAMACHY. Both data sets are showing sufficient precisions to make this assessment. Analysis of the averaging kernels gives proof that at high-mountain-site FTIR is a highly accurate measure for the pure stratospheric column, while SCIAMACHY shows significant tropospheric sensitivity. Based on this finding, we set up a combined a posteriori FTIR-SCIAMACHY retrieval for tropospheric NO2, based upon the averaging kernels. It yields an annual cycle of the clean background (free) tropospheric column (-2, an average of 1.09E+15 cm-2, and an intermediate phase between that of the well known boundary layer and stratospheric annual cycles. The outcome is a concept for an integrated global observing system for tropospheric NO2 that comprises DOAS nadir satellite measurements and a set of latitudinally distributed mountain-site or clean-air FTIR stations

CAY revisited: can optimal scaling resurrect the (C)CAPM?

In this paper, we evaluate specification and pricing error for the Consumption (C-) CAPM in the case where the model is optimally scaled by consumption-wealth ratio (CAY). Lettau and Ludvigson (2001b) show that the C-CAPM successfully explains a large portion (about 70%) of the cross-section of expected returns on Fama and French’s size and book-to-market portfolios, when the model is scaled linearly by CAY. In contrast, we use the methodology developed in Basu and Stremme (2005) to construct the optimal factor scaling as a (possibly non-linear) function of the conditioning variable (CAY), designed to minimize the model’s pricing error. We use a new measure of specification error, also developed in Basu and Stremme (2005), which allows us to analyze the performance of the model both in and out-of-sample. We find that the optimal factor loadings are indeed non-linear in the instrument, in contrast to the linear specification prevalent in the literature. While our optimally scaled C-CAPM explains about 80% of the cross-section of expected returns on the size and book-to-market portfolios (thus in fact out-performing the linearly scaled model of Lettau and Ludvigson (2001b)), it fails to explain the returns on portfolios sorted by industry. Moreover, although the optimal use of CAY does dramatically improve the performance of the model, even the scaled model fails our specification test (for either set of base assets), implying that the model still has large pricing errors. Out-of-sample, the performance of the model deteriorates further, failing even to explain any significant portion of the cross-section of expected returns. For comparison, we also test a scaled version of the classic CAPM and find that it has in fact smaller pricing errors than the scaled C-CAPM

NITROGEN DIOXIDE DOAS MEASUREMENTS FROM GROUND AND SPACE: COMPARISON OF ZENITH SCATTERED SUNLIGHT GROUND-BASED MEASUREMENTS AND OMI DATA IN CENTRAL MEXICO

The use of satellite data in combination with ground-based measurements can provide valuable information about atmospheric chemistry and air quality. In this study, ground-based Differential Optical Absorption Spectroscopy (DOAS) measurements of nitrogen dioxide (NO2) conducted in central Mexico are compared with the space-borne Ozone Monitoring Instrument (OMI) dataset of 2006-2011. Ground-based measurements exhibited large day-to-day variations and were on average three times higher than the space-borne derived average over the observation site. This difference is attributed to strong horizontal inhomogeneity of the lower layer of the measured NO2 columns, sampled over a large footprint from the satellite instrument. Also, a reduced sensitivity of the satellite observation near the surface, where the largest concentrations are expected, could be responsible for this large discrepancy. From the analyzed OMI dataset, distribution maps of NO2 above central Mexico were reconstructed, allowing to identify three main areas with increased NO2 column densities: The dominating metropolitan area of Mexico City, the heavily industrialized region of Tula to the north and the Cuernavaca valley to the south. In this analysis, seasonal variability of NO2 columns over central Mexico was detected, finding higher NO2 columns during the dry and cold season, followed by the dry and warm period, and finally the lowest NO2 columns were found during the rainy season. Pollution transport of this gas from Tula into Mexico City, as well as towards the Cuernavaca valley, is evident from this dataset.El uso de datos satelitales en combinación con mediciones realizadas en superficie puede proporcionar información valiosa acerca de la química atmosférica y la calidad del aire. En este estudio se comparan mediciones en superficie de dióxido de nitrógeno (NO2) realizadas mediante la técnica de espectroscopia óptica de absorción diferencial (DOAS, por sus siglas en inglés) con mediciones del instrumento satelital para la medición de ozono (OMI, por sus siglas en inglés) realizadas de 2006 a 2011. Las mediciones realizadas desde la superficie presentaron grandes variaciones diarias y fueron en promedio tres veces más altas que las columnas medidas desde el espacio. La diferencia se atribuye a una fuerte heterogeneidad horizontal presente en la capa inferior de las columnas de NO2, las cuales fueron muestreadas por el instrumento satelital a partir de un área extensa; de igual manera, esta discrepancia se atribuye a la sensibilidad reducida del satélite cerca de la superficie, donde se encuentran las mayores concentraciones. A partir de los datos del OMI analizados se reconstruyeron mapas de distribución de NO2 sobre el centro de México, y se identificaron tres áreas principales de interés: la zona metropolitana de la Ciudad de México, que fue el área predominante; la zona altamente industrializada de Tula, al norte, y el valle de Cuernavaca, al sur. En este análisis se detectaron de igual forma variaciones estacionales de columnas de NO2 sobre el centro de México: se encontraron columnas más altas durante la estación fría y seca, seguidas por las de la estación caliente y seca; las columnas más bajas se encontraron durante la época de lluvias. Este conjunto de datos evidencia el transporte de contaminación de este gas desde Tula hasta la Ciudad de México, así como al Valle de Cuernavaca

Portfolio efficiency and discount factor bounds with conditioning information: a unified approach

In this paper, we develop a unified framework for the study of mean-variance efficiency and discount factor bounds in the presence of conditioning information. We extend the framework of Hansen and Richard (1987) to obtain new characterizations of the efficient portfolio frontier and variance bounds on discount factors, as functions of the conditioning information. We introduce a covariance-orthogonal representation of the asset return space, which allows us to derive several new results, and provide a portfolio-based interpretation of existing results. Our analysis is inspired by, and extends the recent work of Ferson and Siegel (2001,2002), and Bekaert and Liu (2004). Our results have several important applications in empirical asset pricing, such as the construction of portfolio-based tests of asset pricing models, conditional measures of portfolio performance, and tests of return predictability

Trend analysis of greenhouse gases over Europe measured by a network of ground-based remote FTIR instruments

This paper describes the statistical analysis of annual trends in long term datasets of greenhouse gas measurements taken over ten or more years. The analysis technique employs a bootstrap resampling method to determine both the long-term and intra-annual variability of the datasets, together with the uncertainties on the trend values. The method has been applied to data from a European network of ground-based solar FTIR instruments to determine the trends in the tropospheric, stratospheric and total columns of ozone, nitrous oxide, carbon monoxide, methane, ethane and HCFC-22. The suitability of the method has been demonstrated through statistical validation of the technique, and comparison with ground-based in-situ measurements and 3-D atmospheric models.Peer reviewe