Privatization and governance regulation in frontier emerging markets: The case of Romania

We investigate the link between the regulation of control transactions and the institutional and corporate features of public companies, by analyzing the massive delisting activity in the Romanian capital market. The peculiar ownership reforms involving a large number of listed companies offer a unique opportunity to test Bebchuk and Roe’s (2000) theory of path dependence. Over time, the Romanian authorities have undertaken wide-ranging institutional reforms, most of which favoring blockholders over small and dispersed shareholders. Our empirical approach, based on logit and duration models, allows us to analyze the evolution of public companies over this period and sheds light on the likely events causing the eclipse of frontier emerging markets. Our main findings reveal that delisting is more likely to occur when (i) the shareholdings acquired from the privatization authority by circumventing the capital market are high; (ii) the company experiences frequent takeover bids; and (iii) the stock liquidity is low.ou

New rr-Matrices for Lie Bialgebra Structures over Polynomials

For a finite dimensional simple complex Lie algebra $\mathfrak{g}$, Lie bialgebra structures on $\mathfrak{g}[[u]]$ and $\mathfrak{g}[u]$ were classified by Montaner, Stolin and Zelmanov. In our paper, we provide an explicit algorithm to produce $r$-matrices which correspond to Lie bialgebra structures over polynomials

Strangeness Production in pp,pA,AA Interactions at SPS Energies.HIJING Approach

In this report we have made a systematic study of strangeness production in proton-proton(pp),proton-nucleus(pA) and nucleus- nucleus(AA) collisions at CERN Super Proton Synchroton energies, using$\,\,\, HIJING\,\,\, MONTE \,\,\,CARLO \,\,\,MODEL$ \\ (version $HIJ.01$). Numerical results for mean multiplicities of neutral strange particles ,as well as their ratios to negatives hadrons($$) for p-p,nucleon-nucleon(N-N),\,\,p-S,\,\,p-Ag,\,\,p-Au('min. bias')collisions and p-Au,\,\,S-S,\,\,S-Ag,\,\,S-Au ('central')collisions are compared to experimental data available from CERN experiments and also with recent theoretical estimations given by others models. Neutral strange particle abundances are quite well described for p-p,N-N and p-A interactions ,but are underpredicted by a factor of two in A-A interactions for $\Lambda,\bar{\Lambda}, K^{0}_{S}$ in symmetric collisions(S-S,\,\,Pb-Pb)and for $\Lambda,\bar{\Lambda}\,\,$in asymmetric ones(S-Ag,\,\,S-Au,\,\,S-W). A qualitative prediction for rapidity, transverse kinetic energy and transverse momenta normalized distributions are performed at 200 GeV/Nucleon in p-S,S-S,S-Ag and S-Au collisions in comparison with recent experimental data. HIJING model predictions for coming experiments at CERN for S-Au, S-W and Pb-Pb interactions are given. The theoretical calculations are estimated in a full phase space.Comment: 33 pages(LATEX),18 figures not included,available in hard copy upon request , Dipartamento di Fisica Padova,report DFPD-94-NP-4

Lin-Kernighan Heuristic Adaptations for the Generalized Traveling Salesman Problem

The Lin-Kernighan heuristic is known to be one of the most successful heuristics for the Traveling Salesman Problem (TSP). It has also proven its efficiency in application to some other problems. In this paper we discuss possible adaptations of TSP heuristics for the Generalized Traveling Salesman Problem (GTSP) and focus on the case of the Lin-Kernighan algorithm. At first, we provide an easy-to-understand description of the original Lin-Kernighan heuristic. Then we propose several adaptations, both trivial and complicated. Finally, we conduct a fair competition between all the variations of the Lin-Kernighan adaptation and some other GTSP heuristics. It appears that our adaptation of the Lin-Kernighan algorithm for the GTSP reproduces the success of the original heuristic. Different variations of our adaptation outperform all other heuristics in a wide range of trade-offs between solution quality and running time, making Lin-Kernighan the state-of-the-art GTSP local search.Comment: 25 page