The Filippov-Wazewski relaxation theorem revisited

The converse statement of the Filippov-Wazewski relaxation theorem is proven, more precisely, two differential inclusions have the same closure of their solution sets if and only if the right-hand sides have the same convex hull. The idea of the proof is examining the contingent derivatives to the attainable sets.

An Elementary Core Equivalence Theorem in a Countable Economy

We consider an infinite exchange economy with countably many traders, which can be regarded as a natural extension of finite exchange economies to an infinite one. In our countable economy the core defined in the traditional manner would be empty. To avoid this unwanted situation we have to strengthen the notion of “improves upon”. We will achieve this based on the idea that forming coalitions involve costs.

A Dalang, Morton, Willinger tétel (On the theorem of Dalang-Morton-Willinger)

In the article we shortly discuss the proof of the theorem of Dalang-Morton-Willinger. We show that the proof of the theorem depends on some interesting general properties of the stochastic convergence.

A pénzügyi eszközök árazásának alaptétele, lokálisan korlátos szemimartingál árfolyamok esetén (The fundamental theorem of asset pricing for locally bounded semimartingales)

A pénzügyi eszközök árazásának alaptétele - kissé pongyolán megfogalmazva - azt állítja, hogy egy értékpapírpiacon akkor nincs arbitrázs, ha létezik egy az eredetivel ekvivalens valószínűségi mérték, amelyre vonatkozóan az értékpapírok árait leíró folyamat egy bizonyos értelemben "martingál". Az első ilyen jellegű állítást M. Harrison és S. R. Pliska bizonyították arra esetre, amikor a valószínűségi mező végesen generált. Azóta a tételnek számos általánosítása született. Ezek közül az egyik legismertebb a Dalang{Morton{ Willinger-tétel, ami már teljesen általános valószínűségi mezőből indul ki, de felteszi, hogy az időparaméter diszkrét, és az időhorizont véges. Időközben a tételnek számos folytonos időparaméterű folyamatokra vonatkozó változata is született. Az alaptételt általános esetben, vagyis amikor valószínűségi mező teljesen általános, és az értékpapírok piaci árait leíró folyamat lokálisan korlátos szemimartingál, Delbaen és W. Schachermayer bizonyították be. A Delbaen{Schachermayer-féle alaptétel a maga nemében egy igen általános áll ítás. A tétel bizonyítása igen hosszadalmas, és a funkcionálanalízis valamint a sztochasztikus folyamatok általános elméletének mély eredményeit használja. Utóbbi tudományterület nagy részét P. A. Meyer és a francia strassbourgi iskola matematikusai dolgozták ki a 60-as évek végétől kezdve. A terület megértését tehát alaposan megnehezíti, hogy a felhasznált matematikai apparátus viszonylag friss, egy része pedig csak francia nyelven érhető el. Meggyőződésünk szerint az eredeti, 1994-es Delbaen és Schachermayer-féle bizonyítás csak kevesek által hozzáférhető. A tételnek tudomásunk szerint azóta sem született tankönyvi feldolgozása, annak ellenére, hogy maga az állítás közgazdász körökben is széles körben ismerté vált, és az eredeti cikket számos szerző idézi. Az itt bemutatott bizonyítás Delbaen és Schachermayer 1992 és 2006 közötti írásain alapul. ______ The Delbaen and Schachermayer's theorem is one of the deepest results of mathematical finance. In this article we tried to rethink and slightly simplify the original proof of the theorem to make understandable for nonspecialists who are familiar with general theory of stochastic processes. We give a detailed proof of the theorem and we give new proofs for some of the used statements.

Az eszközárazás második alaptétele (The second fundamental theorem of asset pricing)

A dolgozatban röviden bemutatjuk az eszközárazás második alaptételét. A bizonyítás során felhasználjuk a Dalang-Morton-Wilinger tétel bizonyításában használt állításokat. ______ In the article we summarize the results about the second fundamental theorem of asset pricing.

Development of safety performance functions for empirical Bayes estimation of crash reduction factors

Crash reduction factors (CRFs) are used to estimate the potential number of traffic crashes expected to be prevented from investment in safety improvement projects. The method used to develop CRFs in Florida has been based on the commonly used before-and-after approach. This approach suffers from a widely recognized problem known as regression-to-the-mean (RTM). The Empirical Bayes (EB) method has been introduced as a means to addressing the RTM problem. This method requires the information from both the treatment and reference sites in order to predict the expected number of crashes had the safety improvement projects at the treatment sites not been implemented. The information from the reference sites is estimated from a safety performance function (SPF), which is a mathematical relationship that links crashes to traffic exposure. The objective of this dissertation was to develop the SPFs for different functional classes of the Florida State Highway System. Crash data from years 2001 through 2003 along with traffic and geometric data were used in the SPF model development. SPFs for both rural and urban roadway categories were developed. The modeling data used were based on one-mile segments that contain homogeneous traffic and geometric conditions within each segment. Segments involving intersections were excluded. The scatter plots of data show that the relationships between crashes and traffic exposure are nonlinear, that crashes increase with traffic exposure in an increasing rate. Four regression models, namely, Poisson (PRM), Negative Binomial (NBRM), zero-inflated Poisson (ZIP), and zero-inflated Negative Binomial (ZINB), were fitted to the one-mile segment records for individual roadway categories. The best model was selected for each category based on a combination of the Likelihood Ratio test, the Vuong statistical test, and the Akaike's Information Criterion (AIC). The NBRM model was found to be appropriate for only one category and the ZINB model was found to be more appropriate for six other categories. The overall results show that the Negative Binomial distribution model generally provides a better fit for the data than the Poisson distribution model. In addition, the ZINB model was found to give the best fit when the count data exhibit excess zeros and over-dispersion for most of the roadway categories. While model validation shows that most data points fall within the 95% prediction intervals of the models developed, the Pearson goodness-of-fit measure does not show statistical significance. This is expected as traffic volume is only one of the many factors contributing to the overall crash experience, and that the SPFs are to be applied in conjunction with Accident Modification Factors (AMFs) to further account for the safety impacts of major geometric features before arriving at the final crash prediction. However, with improved traffic and crash data quality, the crash prediction power of SPF models may be further improved.

Centralizers of normal subgroups and the Z*-theorem

Peer reviewed

Centralizers of normal subgroups and the Z*-theorem

Peer reviewed

Centralizers of normal subgroups and the Z*-theorem

Peer reviewed

Exact Solution of Bayes and Minimax Change-Detection Problems

The challenge of detecting a change in the distribution of data is a sequential decision problem that is relevant to many engineering solutions, including quality control and machine and process monitoring. This dissertation develops techniques for exact solution of change-detection problems with discrete time and discrete observations. Change-detection problems are classified as Bayes or minimax based on the availability of information on the change-time distribution. A Bayes optimal solution uses prior information about the distribution of the change time to minimize the expected cost, whereas a minimax optimal solution minimizes the cost under the worst-case change-time distribution. Both types of problems are addressed. The most important result of the dissertation is the development of a polynomial-time algorithm for the solution of important classes of Markov Bayes change-detection problems. Existing techniques for epsilon-exact solution of partially observable Markov decision processes have complexity exponential in the number of observation symbols. A new algorithm, called constellation induction, exploits the concavity and Lipschitz continuity of the value function, and has complexity polynomial in the number of observation symbols. It is shown that change-detection problems with a geometric change-time distribution and identically- and independently-distributed observations before and after the change are solvable in polynomial time. Also, change-detection problems on hidden Markov models with a fixed number of recurrent states are solvable in polynomial time. A detailed implementation and analysis of the constellation-induction algorithm are provided. Exact solution methods are also established for several types of minimax change-detection problems. Finite-horizon problems with arbitrary observation distributions are modeled as extensive-form games and solved using linear programs. Infinite-horizon problems with linear penalty for detection delay and identically- and independently-distributed observations can be solved in polynomial time via epsilon-optimal parameterization of a cumulative-sum procedure. Finally, the properties of policies for change-detection problems are described and analyzed. Simple classes of formal languages are shown to be sufficient for epsilon-exact solution of change-detection problems, and methods for finding minimally sized policy representations are described.

Inductive Theorem Proving and Computer Algebra in the Mathweb Software Bus

Reasoning systems have reached a high degree of maturity in the last decade. However, even the most successful systems are usually not general purpose problem solvers but are typically specialised on problems in a certain domain. The MathWeb SOftware Bus (Mathweb-SB) is a system for combining reasoning specialists via a common osftware bus. We described the integration of the lambda-clam systems, a reasoning specialist for proofs by induction, into the MathWeb-SB. Due to this integration, lambda-clam now offers its theorem proving expertise to other systems in the MathWeb-SB. On the other hand, lambda-clam can use the services of any reasoning specialist already integrated. We focus on the latter and describe first experimnents on proving theorems by induction using the computational power of the MAPLE system within lambda-clam.

An Afriat theorem for the collective model of household consumption

We provide a nonparametric 'revealed preference’ characterization of rational household behavior in terms of the collective consumption model, while accounting for general (possibly non-convex) individual preferences. We establish a Collective Axiom of Revealed Preference (CARP), which provides a necessary and sufficient condition for data consistency with collective rationality. Our main result takes the form of a ‘collective’ version of the Afriat Theorem for rational behavior in terms of the unitary model. This theorem has some interesting implications. With only a finite set of observations, the nature of consumption externalities (positive or negative) in the intra-household allocation process is non-testable. The same non-testability conclusion holds for privateness (with or without externalities) or publicness of consumption. By contrast, concavity of individual utility functions (representing convex preferences) turns out to be testable. In addition, monotonicity is testable for the model that assumes all household consumption is public.