Exogenous expectations on endogenous uncertainty: recursive equilibrium and survival

This paper analyses general equilibrium models with finite heterogeneous agents having exogenous expectations on endogenous uncertainty. It is shown that there exists a recursive equilibrium with the state space consisting of the past aggregate portfolio distribution and the current state of the nature and that it implements the sequential equilibrium. We establish conditions under which the recursive equilibrium is continuous. Moreover, we use the continuous recursive relation of the aggregate variables to prove that if the economy has two types of agents, the one who commits persistent mistakes on the expectation rules of the future endogenous variables is driven out of the market by the others with correct anticipations of the variables, that is, the rational expectations agents.

Essays in recursive equilibrium and market selection hypothesis

Este trabalho consiste em estudar modelos incluindo agentes com informação completa e incompleta sobre o ambiente econômico. Prova-se a existência de equilíbrio em que esses dois agentes coexistem e sob, algumas condições, obtêm-se que esse equilíbrio é recursivo e contínuo, ou seja, pode ser implementado por uma função contínua de transição que relaciona as variáveis de equilíbrio entre dois períodos consecutivos. Mostra-se, sob algumas hipóteses, que em equilíbrios recursivos contínuos, os agentes que cometem erros persistentes nas antecipações dos preços de equilíbrio são eliminados do mercado. Finalmente, exibimos diversos exemplos numéricos, no caso de mercados incompletos e informação completa, em que os agentes com expectativas racionais são eliminados do mercado. Usam-se métodos numéricos alternativos que possibilitam computar um equilíbrio em modelos com agentes heterogêneos.

Approximate recursive equilibrium with minimal state space

This paper shows existence of approximate recursive equilibrium with minimal state space in an environment of incomplete markets. We prove that the approximate recursive equilibrium implements an approximate sequential equilibrium which is always close to a Magill and Quinzii equilibrium without short sales for arbitrarily small errors. This implies that the competitive equilibrium can be implemented by using forecast statistics with minimal state space provided that agents will reduce errors in their estimates in the long run. We have also developed an alternative algorithm to compute the approximate recursive equilibrium with incomplete markets and heterogeneous agents through a procedure of iterating functional equations and without using the rst order conditions of optimality.

Simulation-based smoothing and filtering in factor stochastic volatility models : two econometric applications

In this article we use factor models to describe a certain class of covariance structure for financiaI time series models. More specifical1y, we concentrate on situations where the factor variances are modeled by a multivariate stochastic volatility structure. We build on previous work by allowing the factor loadings, in the factor mo deI structure, to have a time-varying structure and to capture changes in asset weights over time motivated by applications with multi pIe time series of daily exchange rates. We explore and discuss potential extensions to the models exposed here in the prediction area. This discussion leads to open issues on real time implementation and natural model comparisons.

Simulation -based smoothing and filtering in factor stochastic volatility models : two econometric applications (July-2001)

The past decade has wítenessed a series of (well accepted and defined) financial crises periods in the world economy. Most of these events aI,"e country specific and eventually spreaded out across neighbor countries, with the concept of vicinity extrapolating the geographic maps and entering the contagion maps. Unfortunately, what contagion represents and how to measure it are still unanswered questions. In this article we measure the transmission of shocks by cross-market correlation\ coefficients following Forbes and Rigobon's (2000) notion of shift-contagion,. Our main contribution relies upon the use of traditional factor model techniques combined with stochastic volatility mo deIs to study the dependence among Latin American stock price indexes and the North American indexo More specifically, we concentrate on situations where the factor variances are modeled by a multivariate stochastic volatility structure. From a theoretical perspective, we improve currently available methodology by allowing the factor loadings, in the factor model structure, to have a time-varying structure and to capture changes in the series' weights over time. By doing this, we believe that changes and interventions experienced by those five countries are well accommodated by our models which learns and adapts reasonably fast to those economic and idiosyncratic shocks. We empirically show that the time varying covariance structure can be modeled by one or two common factors and that some sort of contagion is present in most of the series' covariances during periods of economical instability, or crisis. Open issues on real time implementation and natural model comparisons are thoroughly discussed.

Rational expectations and the service of public debt: a recursive approach

This paper uses dynamic programming to study the time consistency of optimal macroeconomic policy in economies with recurring public deficits. To this end, a general equilibrium recursive model introduced in Chang (1998) is extended to include govemment bonds and production. The original mode! presents a Sidrauski economy with money and transfers only, implying that the need for govemment fmancing through the inflation tax is minimal. The extended model introduces govemment expenditures and a deficit-financing scheme, analyzing the SargentWallace (1981) problem: recurring deficits may lead the govemment to default on part of its public debt through inflation. The methodology allows for the computation of the set of alI sustainable stabilization plans even when the govemment cannot pre-commit to an optimal inflation path. This is done through value function iterations, which can be done on a computeI. The parameters of the extended model are calibrated with Brazilian data, using as case study three Brazilian stabilization attempts: the Cruzado (1986), Collor (1990) and the Real (1994) plans. The calibration of the parameters of the extended model is straightforward, but its numerical solution proves unfeasible due to a dimensionality problem in the algorithm arising from limitations of available computer technology. However, a numerical solution using the original algorithm and some calibrated parameters is obtained. Results indicate that in the absence of govemment bonds or production only the Real Plan is sustainable in the long run. The numerical solution of the extended algorithm is left for future research.

Recursive hierarchic segmentation analysis of bone mineral density changes on digital panoramic images

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Recursive renormalization of the singlet one-pion-exchange plus point-like interactions

The subtracted kernel approach is shown to be a powerful method to be implemented recursively in scattering equations with regular plus point-like interactions. The advantages of the method allows one to recursively renormalize the potentials, with higher derivatives of the Dirac-delta, improving previous results. The applicability of the method is verified in the calculation of the 1 So nucleon-nucleon phase-shifts, when considering a potential with one-pion-exchange plus a contact interaction and its derivatives. The S-1(0) renormalization parameters are fitted to the data. The method can in principle be extended to any derivative order of the contact interaction, to higher partial waves and to coupled channels. (c) 2005 Elsevier B.V. All rights reserved.

Another prefiltering algorithm for adaptive IIR filtering

An algorithm for adaptive IIR filtering that uses prefiltering structure in direct form is presented. This structure has an estimation error that is a linear function of the coefficients. This property greatly simplifies the derivation of gradient-based algorithms. Computer simulations show that the proposed structure improves convergence speed.

Differential dispersion relations with an arbitrary number of subtractions: A recursive approach

Making use of a recursive approach, derivative dispersion relations are generalized for an arbitrary number of subtractions. The results for both cross even and odd amplitudes are theoretically consistent at sufficiently high energies and in the region of small momentum transfer. © 1999 Published by Elsevier Science B.V. All rights reserved.

Harmonics filtering and detection of disturbances using wavelets

Traditional mathematical tools, like Fourier Analysis, have proven to be efficient when analyzing steady-state distortions; however, the growing utilization of electronically controlled loads and the generation of a new dynamics in industrial environments signals have suggested the need of a powerful tool to perform the analysis of non-stationary distortions, overcoming limitations of frequency techniques. Wavelet Theory provides a new approach to harmonic analysis, focusing the decomposition of a signal into non-sinusoidal components, which are translated and scaled in time, generating a time-frequency basis. The correct choice of the waveshape to be used in decomposition is very important and discussed in this work. A brief theoretical introduction on Wavelet Transform is presented and some cases (practical and simulated) are discussed. Distortions commonly found in industrial environments, such as the current waveform of a Switched-Mode Power Supply and the input phase voltage waveform of motor fed by inverter are analyzed using Wavelet Theory. Applications such as extracting the fundamental frequency of a non-sinusoidal current signal, or using the ability of compact representation to detect non-repetitive disturbances are presented.

Line based camera calibration in machine vision dynamic applications

The problem of dynamic camera calibration considering moving objects in close range environments using straight lines as references is addressed. A mathematical model for the correspondence of a straight line in the object and image spaces is discussed. This model is based on the equivalence between the vector normal to the interpretation plane in the image space and the vector normal to the rotated interpretation plane in the object space. In order to solve the dynamic camera calibration, Kalman Filtering is applied; an iterative process based on the recursive property of the Kalman Filter is defined, using the sequentially estimated camera orientation parameters to feedback the feature extraction process in the image. For the dynamic case, e.g. an image sequence of a moving object, a state prediction and a covariance matrix for the next instant is obtained using the available estimates and the system model. Filtered state estimates can be computed from these predicted estimates using the Kalman Filtering approach and based on the system model parameters with good quality, for each instant of an image sequence. The proposed approach was tested with simulated and real data. Experiments with real data were carried out in a controlled environment, considering a sequence of images of a moving cube in a linear trajectory over a flat surface.

Identification and filtering of uncharacteristic noise in the CMS hadron calorimeter

Commissioning studies of the CMS hadron calorimeter have identified sporadic uncharacteristic noise and a small number of malfunctioning calorimeter channels. Algorithms have been developed to identify and address these problems in the data. The methods have been tested on cosmic ray muon data, calorimeter noise data, and single beam data collected with CMS in 2008. The noise rejection algorithms can be applied to LHC collision data at the trigger level or in the offline analysis. The application of the algorithms at the trigger level is shown to remove 90% of noise events with fake missing transverse energy above 100 GeV, which is sufficient for the CMS physics trigger operation. © 2010 IOP Publishing Ltd and SISSA.

Filtering for discrete-time Markov jump systems with network transmitted mode

This paper is concerned with ℋ 2 and ℋ ∞ filter design for discrete-time Markov jump systems. The usual assumption of mode-dependent design, where the current Markov mode is available to the filter at every instant of time is substituted by the case where that availability is subject to another Markov chain. In other words, the mode is transmitted to the filter through a network with given transmission failure probabilities. The problem is solved by modeling a system with N modes as another with 2N modes and cluster availability. We also treat the case where the transition probabilities are not exactly known and demonstrate our conditions for calculating an ℋ ∞ norm bound are less conservative than the available results in the current literature. Numerical examples show the applicability of the proposed results. ©2010 IEEE.

Adaptive filter feature identification for structural health monitoring in aeronautical panel

This paper presents an approach for structural health monitoring (SHM) by using adaptive filters. The experimental signals from different structural conditions provided by piezoelectric actuators/sensors bonded in the test structure are modeled by a discrete-time recursive least square (RLS) filter. The biggest advantage to use a RLS filter is the clear possibility to perform an online SHM procedure since that the identification is also valid for non-stationary linear systems. An online damage-sensitive index feature is computed based on autoregressive (AR) portion of coefficients normalized by the square root of the sum of the square of them. The proposed method is then utilized in a laboratory test involving an aeronautical panel coupled with piezoelectric sensors/actuators (PZTs) in different positions. A hypothesis test employing the t-test is used to obtain the damage decision. The proposed algorithm was able to identify and localize the damages simulated in the structure. The results have shown the applicability and drawbacks the method and the paper concludes with suggestions to improve it. ©2010 Society for Experimental Mechanics Inc.