On the economic link between asset prices and real activity.

This paper presents a model linking two financial markets (stocks and bonds) with real business cycle, in the framework of the Consumption Capital Asset Pricing Model with Generalized Isoelastic Preferences. Besides interest rate term spread, the model includes a new variable to forecast economic activity: stock market term spread. This is the slope of expected stock market returns. The empirical evidence documented in this paper suggests systematic relationships between business cycle’s state and the shapes of two yield curves (interest rates and expected stock returns). Results are robust to changes in measures of economic growth, stock prices, interest rates and expectations generating mechanisms.Stock market; Interest rates; Economic growth; Term structure;

Clustering and classifying images with local and global variability

A procedure for clustering and classifying images determined by three classification variables is presented. A measure of global variability based on the singular value decomposition of the image matrices, and two average measures of local variability based on spatial correlation and spatial changes. The performance of the procedure is compared using three different databases

Can output explain the predictability and volatility of stock returns?.

This paper examines whether a general equilibrium asset pricing model can explain two important empirical regularities of asset returns, extensively documented in the literature: (i) returns can be predicted by a set of macro variables, and (ii) returns are very volatile. We derive a closed-form solution for the equilibrium asset pricing model that relates asset returns to output by using an approximate method proposed by Campbell (Am. Econ. Rev. 83 (1993) 487) and Restoy and Weil (W.P. NBER, No. 6611 (1998)). We obtain evidence on eight OECD economies using both quarterly and annual observations. Equilibrium models seem to fin fewer difficultie in explaining the volatility of returns than their predictability for general output processes. In the case of the US, the observed predictability and volatility of asset returns, for annual frequencies, are broadly compatible with the predictions of equilibrium models for a reasonableGeneralized isoelastic preferences; Asset returns; Real activity; Volatility;

Tail risk of electricity futures

This paper compares the in-sample and out-of-sample performance of several models for computing the tail risk of one-month and one-year electricity futures contracts traded in the NordPool, French, German, and Spanish markets in 2008–2017. As measures of tail risk, we use the one-day-ahead Value-at-Risk (VaR) and the Expected Shortfall (ES). With VaR, the AR (1)-GARCH (1,1) model with Student-t distribution is the best-performing specification with 88% cases in which the Fisher test accepts the model, with a success rate of 94% in the left tail and of 81% in the right tail. The model passes the test of model adequacy in the 100% of the cases in the NordPool and German markets, but only in the 88% and 63% of the cases in the Spanish and French markets. With ES, this model passes the test of model adequacy in 100% of cases in all markets. Historical Simulation and Quantile Regression-based approaches misestimate tail risks. The right-hand tail of the returns is more difficult to model than the left-hand tail and therefore financial regulators and the administrators of futures markets should take these results into account when setting additional regulatory capital requirements and margin account regulations to short positions.We acknowledge financial support from FUNCAS, through grant PRELEC2020–2017/00085/00, from DGICYT, through grant ECO2016–77807-P, and from CAM, through grant EARLYFIN-CM, #S2015/HUM-335

Modelling Electricity Swaps with Stochastic Forward Premium Models

We present a new model for pricing electricity swaps. Two general factors affect contracts but unique risk elements affect each contract. General factors are average swap prices and deterministic trend-seasonal components, and unique elements are forward premiums. Innovations follow MNIG distributions. We estimate the model with data from the European Energy Exchange. The model outperforms four competitors, both in in-sample valuation and in out-of-sample forecasting, and in fitting the term structure of volatilities by market segments. Competitor models are (i) diffusion spot prices, (ii) jump-diffusion spot prices with time dependent volatility, (iii) HJM-based and (iv) Levy multifactor model with NIG distributions. Value-at-Risk measures based on normality strongly underestimate tail risk but our model gives estimates that are more exact.Juan Ignacio Peña and Rosa Rodriguez acknowledge financial support from the Ministry of Economics and Competitiveness, respectively, through grants ECO2012-35023, ECO2016-77807-P, and ECO2012-3655

A general equilibrium approach to the stock returns and real activity relationship

This paper brings together two separate and important topics in finance: the predictability of aggregated stock returns and the intertemporal asset pricing models. We present empirical evidence about the predictability of stock returns with a sample of OECD economies and investigate whether such evidence is consistent with a simple general equilibrium model. Our framework allow us to formalize the extensively documented empirical relationship between asset returns and real activity. The principal parameters in this relationship are the relative risk aversion and the elasticity of intertemporal substitution for the first moment of the returns and only the elasticity of substitution for the second moments. Except for the United States annual case, the puzzle of volatility remains in our model

Handwritten digit classification

Pattern recognition is one of the major challenges in statistics framework. Its goal is the feature extraction to classify the patterns into categories. A well-known example in this field is the handwritten digit recognition where digits have to be assigned into one of the 10 classes using some classification method. Our purpose is to present alternative classification methods based on statistical techniques. We show a comparison between a multivariate and a probabilistic approach, concluding that both methods provide similar results in terms of test-error rate. Experiments are performed on the known MNIST and USPS databases in binary-level image. Then, as an additional contribution we introduce a novel method to binarize images, based on statistical concepts associated to the written trace of the digi

Communication: Transition State Theory for dissipative systems without a dividing surface

Transition state theory is a central cornerstone in reaction dynamics. Its key step is the identification of a dividing surface that is crossed only once by all reactive trajectories. This assumption is often badly violated, especially when the reactive system is coupled to an environment. The calculations made in this way then overestimate the reaction rate and the results depend critically on the choice of the dividing surface. In this Communication, we study the phase space of a stochastically driven system close to an energetic barrier in order to identify the geometric structure unambiguously determining the reactive trajectories, which is then incorporated in a simple rate formula for reactions in condensed phase that is both independent of the dividing surface and exact

Impact of glucose oxidase treatment in high sugar and pH musts on volatile composition of white wines

Producción CientíficaClimate change is modifying the composition of the grapes, increasing sugar and pH levels, which produces unbalanced wines with high alcohol degree, low acidity and poor aromatic notes. In this study, glucose oxidase (GOX) and catalase (CAT) were applied in white must with high sugar content and pH (>3.8) to simultaneously decrease glucose concentration and pH. The effect of enzyme treatment on volatile composition of wine was investigated. A concentration of 0.17 mkat/L for both GOX and CAT was sufficient to produce a remarkable reduction of glucose concentration in the must (61.5 g/L), achieving similar results within the pH range of 3–4. The musts subjected to enzymatic treatment yielded more balanced wines, lowering their alcohol content by 10–27 mL/L and pH by 0.3–0.5, while leaving their chromatic characteristics unchanged compared to the control wines. As positive effects, enzyme treatment reduced the concentrations of C6-alcohols with green-herbaceous notes and high-chain ethyl esters with soapy notes in wines, and did not modify the concentrations of short-chain ethyl esters, acids and higher alcohols. However, the concentrations of heptyl acetate and 2-phenylethanol with floral notes, and some ketones with floral and fruit notes, were lower in wines from treated musts

Fortalecimiento del proceso de lectura a través de estrategias lúdico-pedagógicas en los estudiantes del grado primero de la institución educativa liceo Quindío sede Andrés bello del municipio de Salento

Esta investigación adopta como modalidad la investigación acción-participativa, desde la visión de J. Eliot; así mismo, plantea el diseño y aplicación de estrategias pedagógicas en “El proyecto lúdico pedagógico de aula” desde el enfoque del aprendizaje significativo. Orientada al fortalecimiento del proceso de lectura, en los estudiantes del grado primero de la Institución Educativa Liceo Quindío Sede Andrés Bello del Municipio de Salento. Para ello, inicialmente, toma como marco central de referencia desde la temática, la lúdica y la pedagogía, en cada una de sus etapas y fases de desarrollo, el enfoque de aprendizaje significativo de David Ausubel; igualmente, aborda el proceso de lectura de Kenneth Goodman. Consecutivamente, para el diseño y ejecución del plan de intervención recurre a la estrategia de lectura de Isabel Solé; finalmente, una vez aplicada la estrategia didáctica y analizados los resultados obtenidos a través del registro en el diario de campo, se evaluará el impacto de la estrategia pedagógica