Continuous-time random-walk model for financial distributions

We apply the formalism of the continuous-time random walk to the study of financial data. The entire distribution of prices can be obtained once two auxiliary densities are known. These are the probability densities for the pausing time between successive jumps and the corresponding probability density for the magnitude of a jump. We have applied the formalism to data on the U.S. dollardeutsche mark future exchange, finding good agreement between theory and the observed data.

Tuning clustering in random networks with arbitrary degree distributions

We present a generator of random networks where both the degree-dependent clustering coefficient and the degree distribution are tunable. Following the same philosophy as in the configuration model, the degree distribution and the clustering coefficient for each class of nodes of degree k are fixed ad hoc and a priori. The algorithm generates corresponding topologies by applying first a closure of triangles and second the classical closure of remaining free stubs. The procedure unveils an universal relation among clustering and degree-degree correlations for all networks, where the level of assortativity establishes an upper limit to the level of clustering. Maximum assortativity ensures no restriction on the decay of the clustering coefficient whereas disassortativity sets a stronger constraint on its behavior. Correlation measures in real networks are seen to observe this structural bound.

Free inertial processes driven by Gaussian noise: Probability distributions, anomalous diffusion and fractal behavior

We study the motion of an unbound particle under the influence of a random force modeled as Gaussian colored noise with an arbitrary correlation function. We derive exact equations for the joint and marginal probability density functions and find the associated solutions. We analyze in detail anomalous diffusion behaviors along with the fractal structure of the trajectories of the particle and explore possible connections between dynamical exponents of the variance and the fractal dimension of the trajectories.

Integrated random processes exhibiting long tails, finite moments, and power-law spectra

A dynamical model based on a continuous addition of colored shot noises is presented. The resulting process is colored and non-Gaussian. A general expression for the characteristic function of the process is obtained, which, after a scaling assumption, takes on a form that is the basis of the results derived in the rest of the paper. One of these is an expansion for the cumulants, which are all finite, subject to mild conditions on the functions defining the process. This is in contrast with the Lévy distribution¿which can be obtained from our model in certain limits¿which has no finite moments. The evaluation of the spectral density and the form of the probability density function in the tails of the distribution shows that the model exhibits a power-law spectrum and long tails in a natural way. A careful analysis of the characteristic function shows that it may be separated into a part representing a Lévy process together with another part representing the deviation of our model from the Lévy process. This

Generalized Langevin equations: Anomalous diffusion and probability distributions

We study the motion of a particle governed by a generalized Langevin equation. We show that, when no fluctuation-dissipation relation holds, the long-time behavior of the particle may be from stationary to superdiffusive, along with subdiffusive and diffusive. When the random force is Gaussian, we derive the exact equations for the joint and marginal probability density functions for the position and velocity of the particle and find their solutions.

Estimation of jump-diffusion processes via empirical characteristic functions

Preface The starting point for this work and eventually the subject of the whole thesis was the question: how to estimate parameters of the affine stochastic volatility jump-diffusion models. These models are very important for contingent claim pricing. Their major advantage, availability T of analytical solutions for characteristic functions, made them the models of choice for many theoretical constructions and practical applications. At the same time, estimation of parameters of stochastic volatility jump-diffusion models is not a straightforward task. The problem is coming from the variance process, which is non-observable. There are several estimation methodologies that deal with estimation problems of latent variables. One appeared to be particularly interesting. It proposes the estimator that in contrast to the other methods requires neither discretization nor simulation of the process: the Continuous Empirical Characteristic function estimator (EGF) based on the unconditional characteristic function. However, the procedure was derived only for the stochastic volatility models without jumps. Thus, it has become the subject of my research. This thesis consists of three parts. Each one is written as independent and self contained article. At the same time, questions that are answered by the second and third parts of this Work arise naturally from the issues investigated and results obtained in the first one. The first chapter is the theoretical foundation of the thesis. It proposes an estimation procedure for the stochastic volatility models with jumps both in the asset price and variance processes. The estimation procedure is based on the joint unconditional characteristic function for the stochastic process. The major analytical result of this part as well as of the whole thesis is the closed form expression for the joint unconditional characteristic function for the stochastic volatility jump-diffusion models. The empirical part of the chapter suggests that besides a stochastic volatility, jumps both in the mean and the volatility equation are relevant for modelling returns of the S&P500 index, which has been chosen as a general representative of the stock asset class. Hence, the next question is: what jump process to use to model returns of the S&P500. The decision about the jump process in the framework of the affine jump- diffusion models boils down to defining the intensity of the compound Poisson process, a constant or some function of state variables, and to choosing the distribution of the jump size. While the jump in the variance process is usually assumed to be exponential, there are at least three distributions of the jump size which are currently used for the asset log-prices: normal, exponential and double exponential. The second part of this thesis shows that normal jumps in the asset log-returns should be used if we are to model S&P500 index by a stochastic volatility jump-diffusion model. This is a surprising result. Exponential distribution has fatter tails and for this reason either exponential or double exponential jump size was expected to provide the best it of the stochastic volatility jump-diffusion models to the data. The idea of testing the efficiency of the Continuous ECF estimator on the simulated data has already appeared when the first estimation results of the first chapter were obtained. In the absence of a benchmark or any ground for comparison it is unreasonable to be sure that our parameter estimates and the true parameters of the models coincide. The conclusion of the second chapter provides one more reason to do that kind of test. Thus, the third part of this thesis concentrates on the estimation of parameters of stochastic volatility jump- diffusion models on the basis of the asset price time-series simulated from various "true" parameter sets. The goal is to show that the Continuous ECF estimator based on the joint unconditional characteristic function is capable of finding the true parameters. And, the third chapter proves that our estimator indeed has the ability to do so. Once it is clear that the Continuous ECF estimator based on the unconditional characteristic function is working, the next question does not wait to appear. The question is whether the computation effort can be reduced without affecting the efficiency of the estimator, or whether the efficiency of the estimator can be improved without dramatically increasing the computational burden. The efficiency of the Continuous ECF estimator depends on the number of dimensions of the joint unconditional characteristic function which is used for its construction. Theoretically, the more dimensions there are, the more efficient is the estimation procedure. In practice, however, this relationship is not so straightforward due to the increasing computational difficulties. The second chapter, for example, in addition to the choice of the jump process, discusses the possibility of using the marginal, i.e. one-dimensional, unconditional characteristic function in the estimation instead of the joint, bi-dimensional, unconditional characteristic function. As result, the preference for one or the other depends on the model to be estimated. Thus, the computational effort can be reduced in some cases without affecting the efficiency of the estimator. The improvement of the estimator s efficiency by increasing its dimensionality faces more difficulties. The third chapter of this thesis, in addition to what was discussed above, compares the performance of the estimators with bi- and three-dimensional unconditional characteristic functions on the simulated data. It shows that the theoretical efficiency of the Continuous ECF estimator based on the three-dimensional unconditional characteristic function is not attainable in practice, at least for the moment, due to the limitations on the computer power and optimization toolboxes available to the general public. Thus, the Continuous ECF estimator based on the joint, bi-dimensional, unconditional characteristic function has all the reasons to exist and to be used for the estimation of parameters of the stochastic volatility jump-diffusion models.

RECOVERY OF AN OXISOL DEGRADED BY THE CONSTRUCTION OF A HYDROELECTRIC POWER PLANT

ABSTRACT The removal of thick layers of soil under native scrubland (Cerrado) on the right bank of the Paraná River in Selvíria (State of Mato Grosso do Sul, Brazil) for construction of the Ilha Solteira Hydroelectric Power Plant caused environmental damage, affecting the revegetation process of the stripped soil. Over the years, various kinds of land use and management systems have been tried, and the aim of this study was to assess the effects of these attempts to restore the structural quality of the soil. The experiment was conducted considering five treatments and thirty replications. The following treatments were applied: stripped soil without anthropic intervention and total absence of plant cover; stripped soil treated with sewage sludge and planted to eucalyptus and grass a year ago; stripped soil developing natural secondary vegetation (capoeira) since 1969; pastureland since 1978, replacing the native vegetation; and soil under native vegetation (Cerrado). In the 0.00-0.20 m layer, the soil was chemically characterized for each experimental treatment. A 30-point sampling grid was used to assess soil porosity and bulk density, and to assess aggregate stability in terms of mean weight diameter (MWD) and geometric mean diameter (GMD). Aggregate stability was also determined using simulated rainfall. The results show that using sewage sludge incorporated with a rotary hoe improved the chemical fertility of the soil and produced more uniform soil pore size distribution. Leaving the land to develop secondary vegetation or turning it over to pastureland produced an intermediate level of structural soil quality, and these two treatments produced similar results. Stripped soil without anthropic intervention was of the lowest quality, with the lowest values for cation exchange capacity (CEC) and macroporosity, as well as the highest values of soil bulk density and percentage of aggregates with diameter size <0.50 mm, corroborated by its lower organic matter content. However, the percentage of larger aggregates was higher in the native vegetation treatment, which boosted MWD and GMD values. Therefore, assessment of some land use and management systems show that even decades after their implementation to mitigate the degenerative effects resulting from the installation of the Hydroelectric Plant, more efficient approaches are still required to recover the structural quality of the soil.

The Power of Images in Antonio Agustin's. Diálogos de Medallas, inscripciones y otras antigüedades (1587)

Socias ofereix una àmplia mirada sobre l'ús de les imatges en les obres de numismàtica primerenques. Diàlegs de medalles, d'Antonio Agustín

Price transmission and market power analysis in the Spanish seafood market chain

[cat] Espanya és un dels principals mercats de productes pesquers d’Europa i del món. El consum de productes pesquers ha estat tradicionalment molt important a Espanya, el 2005 es varen consumir 36,7 kg per persona (MAPA, diversos anys). Malgrat això, el mercat i cóm interactuen els diversos nivells de la cadena de comercialització han gaudit de poca atenció. En aquest estudi, utilitzant dades setmanals, s’analitza per als dotze principals productes pesquers, l’elasticitat en la transmissió de preus al llarg de la cadena de comercialització a Espanya (llotja, mercat central i detallista). Finalment s’investiga la presència d’assimetria en la transmissió de preus entre aquests nivells de mercat. Els resultats obtinguts tenen importants implicacions a l’hora d’analitzar la demanda, poder de mercat i marges al llarg del mercat per als productes pesquers.

Iowa Power Fund Board Project Report Update, July 29, 2009

Amana Farms is using an anaerobic digestion, which is a two-stage digester that converts manure and other organic wastes into three valuable by-products: 1) Biogas – to fuel an engine/generator set to create electricity; 2) Biosolids - used as a livestock bedding material or as a soil amendment; 3) Liquid stream - will be applied as a low-odor fertilizer to growing crops. (see Business Plan appendix H) The methane biogas will be collected from the two stages of the anaerobic digestion vessel and used for fuel in the combined heat and power engine/generator sets. The engine/generator sets are natural gasfueled reciprocating engines modified to burn biogas. The electricity produced by the engine/generator sets will be used to offset on-farm power consumption and the excess power will be sold directly to Amana Society Service Company as a source of green power. The waste heat, in the form of hot water, will be collected from both the engine jacket liquid cooling system and from the engine exhaust (air) system. Approximately 30 to 60% of this waste heat will be used to heat the digester. The remaining waste heat will be used to heat other farm buildings and may provide heat for future use for drying corn or biosolids. The digester effluent will be pumped from the effluent pit at the end of the anaerobic digestion vessel to a manure solids separator. The mechanical manure separator will separate the effluent digested waste stream into solid and liquid fractions. The solids will be dewatered to approximately a 35% solid material. Some of the separated solids will be used by the farm for a livestock bedding replacement. The remaining separated solids may be sold to other farms for livestock bedding purposes or sold to after-markets, such as nurseries and composters for soil amendment material. The liquid from the manure separator, now with the majority of the large solids removed, will be pumped into the farm’s storage lagoon. A significant advantage of the effluent from the anaerobic digestion treatment process is that the viscosity of the effluent is such that the liquid effluent can now be pumped through an irrigation nozzle for field spreading.

Iowa Power Fund Board Project Report Update, July 29, 2009

Climate refers to the long-term course or condition of weather, usually over a time scale of decades and longer. It has been documented that our global climate is changing (IPCC 2007, Copenhagen Diagnosis 2009), and Iowa is no exception. In Iowa, statistically significant changes in our precipitation, streamflow, nighttime minimum temperatures, winter average temperatures, and dewpoint humidity readings have occurred during the past few decades. Iowans are already living with warmer winters, longer growing seasons, warmer nights, higher dew-point temperatures, increased humidity, greater annual streamflows, and more frequent severe precipitation events (Fig. 1-1) than were prevalent during the past 50 years. Some of the impacts of these changes could be construed as positive, and some are negative, particularly the tendency for greater precipitation events and flooding. In the near-term, we may expect these trends to continue as long as climate change is prolonged and exacerbated by increasing greenhouse gas emissions globally from the use of fossil fuels and fertilizers, the clearing of land, and agricultural and industrial emissions. This report documents the impacts of changing climate on Iowa during the past 50 years. It seeks to answer the question, “What are the impacts of climate change in Iowa that have been observed already?” And, “What are the effects on public health, our flora and fauna, agriculture, and the general economy of Iowa?”

End of Project Report to the Iowa Power Fund, October 31, 2008

The 2008 Biobased Industry Outlook Conference was held September 7-10 on the Iowa State University campus. Over 750 people attended the plenary sessions on the morning of September 8th; 580 people registered for the full conference. Sponsorships: $92,500 in sponsorships in addition to the IPF was secured for the conference (considered “match” to the IPF grant). Including the $11,250 IPF sponsorship ($12,500 minus overhead charges of $1,250), the total amount contributed for conference sponsorships was $103,750. A list of sponsors and the amount of sponsorship is listed in Appendix A. Sponsorship funds received from the Iowa Power Fund were used for supplies and materials. Please see Appendix B which documents the transfer of IPF grant funds internally at ISU and their use.

Union power, minimum wage legislation endogenous labor supplies and production

The objective of this work is to study the impact of the unions' bargaining power on production and wages. We present a model where a competitive final good is produced through two substitutable intermediate goods, one produced by unskilled labor and the other by skilled labor. Potential workers decide at their cost to become skilled or unskilled and, thus, labor supplies are determined endogenously. We find that the reallocation of the labor supplies due to changes in the unskilled (or skilled) unions¿ bargaining power may have a positive impact on the final goods production. At the same time, total labor earnings increase with the unskilled unions¿ bargaining power if the final goods production increases too. We also show that the minimum wage legislation has efects similar to an increase in the bargaining power of the unskilled unions.