An invariance property of Farebrother's procedure for estimation with aggregated data

A procedure proposed by Farebrother (1979) for estimating the parameters of a standard Gauss-Markov model from aggregated data is shown to be invariant with respect to the choice of a generalized inverse of the matrix designated to approximate the unknown dispersion matrix of a transformed model, thus correcting Farebrother's statement that this desirable property cannot be attributed to his procedure.     

Forward rate models with linear volatilities

The existence of solutions to the Heath?CJarrow?CMorton equation of the bond market with linear volatility and general Lévy random factor is studied. Conditions for the existence and non-existence of solutions in the class of bounded fields are presented. For the existence of solutions, the Lévy process should necessarily be without a Gaussian part and without negative jumps. If this is the case, then necessary and sufficient conditions for the existence are formulated either in terms of the behavior of the Lévy measure of the noise near the origin or the behavior of the Laplace exponent of the noise at infinity.     

Cost of Equity and S&P 500 Index Revisions

We examine how the cost of equity changes when firms are added to or removed from the S&P 500 Index during index revisions. Newly added firms experience a significant decline in the cost of equity, while recently removed firms show a significant increase. Liquidity improves for addition firms and declines for removed firms. Addition firms also experience a decline in shadow cost. Changes in cost of equity for included firms are explained by changes in liquidity, shadow cost, and firm size. Finally, included firms with greater investment opportunities benefit more from the reduction in cost of capital.     

Applying free random variables to random matrix analysis of financial data. Part I: The Gaussian case

We apply the concept of free random variables to doubly correlated (Gaussian) Wishart random matrix models, appearing, for example, in a multivariate analysis of financial time series, and displaying both inter-asset cross-covariances and temporal auto-covariances. We give a comprehensive introduction to the rich financial reality behind such models. We explain in an elementary way the main techniques of free random variables calculus, with a view to promoting them in the quantitative finance community. We apply our findings to tackle several financially relevant problems, such as a universe of assets displaying exponentially decaying temporal covariances, or the exponentially weighted moving average, both with an arbitrary structure of cross-covariances.     

After retrotopia? The future of organizing and the thought of Zygmunt Bauman

The main body of work of Zygmunt Bauman concerns his home discipline of sociology, but his insights have been influential also in the field of organization studies. In this text, we provide an overview of the extent of this influence, providing some additional context for positioning the other contributions to this special section. Afterwards, we explore in more detail two notions central for Bauman’s late thought: that of liquidity and retrotopia. The former constitutes the root metaphor for theorizing the current global predicament. In this text, we analyse how two modes of interpreting it, using the assumptions behind Kurt Lewin’s CATS model and the alchemical tradition underpinning Carl Gustav Jung’s conception of archetypes respectively, can help us theorize the alternative modes of organizing and managing encountered in a study of contemporary alternative organizations.These insights form the starting point for our second goal: to explore Bauman’s notion of retrotopia as a potentially fruitful starting point for discussing both the deficiencies of current visions of our future society, and the possibilities and vicissitudes of developing new forms of organizing and managing. Such new forms, both as practice and as theoretical constructs, are urgently needed if we are to face the numerous, and potentially catastrophic global challenges facing our society today.     

Demographic impacts in central and eastern European countries

All countries undergoing socioeconomic transformation in the central, eastern, and southeastern parts of Europe, regardless of the progress made in systemic transformation, have witnessed significant changes in their population. This paper presents some of these demographic changes and considers the dynamics produced by a drop in reproduction rates and the declining frequency of marriages. The intensity of these changes tended to vary. All of the countries, with the exception of Albania, are characterized by low birth rates approaching nominally the level of death rates. Infant mortality rates in the majority of the countries were relatively high at the beginning of the 1990s compared with their minimum.     

An Alternative for Time Series Models

Two methods for construction of new stochastic processes with discrete time are presented. One of the methods employs as the defining tool “triangular （more specifically ＇pseudoaffine＇） transformations” which are extended from the Euclidean R^n to infinite dimension space. They transform any well-known discrete time stochastic process into the constructed one. The other more flexible method is the “method of parameter dependence”, extended to infinite dimension. Properties of the obtained stochastic processes （by either method） indicate the possibility to apply them for financial analysis, as an alternative for the classical time series models. The advantage of the presented models over the existing ones first of all relies on expected better accuracy. This follows from the fact that the typically held assumption on Markovianity in the existing models can easily be relaxed. The defined processes may incorporate a quite long memory including, among others, the k-Markovian cases for k _〉 2. Regardless the non-Markovianity of the models they still are tractable in an analytical or numerical way. The stochastic processes defined in this paper provide more flexible and more general tools than the existing time series models for modeling financial problems. Among others, they make it possible to incorporate the influence of environmental （explanatory） random variables on the underlying stochastic models＇ behavior. These additional features turn out to be describable by the method of parameter dependence. Some suggestions for an associated preliminary statistical analysis are included.     

Going private transactions,bondholder returns,and wealth transfer effects

We examine how buyout activity and deal characteristics drive bondholder returns and the wealth transfer effects between bondholders and stockholders in going private transactions from 1981 to 2006. We find that various deal characteristics are major determinants of the cross-sectional variation in bondholder returns. In particular, a single private equity acquirer mitigates bondholder losses. On the other hand, bondholders have larger losses when a reputable buyout firm is involved in the deal. Bondholders experience losses in the 1980s and 2000s, but enjoy gains in the 1990s. Our findings remain robust to consideration of deal financing, relative cost of credit, and level of market overheating. We find a negative and significant relationship between stockholder and bondholder wealth effects, which supports the wealth transfer hypothesis.     

Effect of Business Group Affiliation on Firm Internationalization: The Case of India Under Reforms

The authors investigate how diversified business groups influence the structural reform–firm strategy relations given its effect on strategic choice and its implementation in a large emerging economy: India. By integrating business group, industrial organization, and international business literature, the authors predict considerable differences in the exporting behavior of business group–affiliated firms on the basis of their market competitiveness and governance dynamics. The authors test their predictions empirically with longitudinal data of 6,119 Indian firms over a 21-year period starting from 1991–1992 to 2011–2012 and find support for most of the hypotheses. These findings suggest that knowledge of the heterogeneity within business groups are essential for understanding the response of business group affiliates in light of the progression of reform process in India. This study thus contributes to a more complete conceptual understanding of the strategic responses of promarket reforms of business group affiliates in emerging economies.     

Combining predictive distributions for the statistical post-processing of ensemble forecasts

Statistical post-processing techniques are now used widely for correcting systematic biases and errors in the calibration of ensemble forecasts obtained from multiple runs of numerical weather prediction models. A standard approach is the ensemble model output statistics (EMOS) method, which results in a predictive distribution that is given by a single parametric law, with parameters that depend on the ensemble members. This article assesses the merits of combining multiple EMOS models based on different parametric families. In four case studies with wind speed and precipitation forecasts from two ensemble prediction systems, we investigate the performances of state of the art forecast combination methods and propose a computationally efficient approach for determining linear pool combination weights. We study the performance of forecast combination compared to that of the theoretically superior but cumbersome estimation of a full mixture model, and assess which degree of flexibility of the forecast combination approach yields the best practical results for post-processing applications.