Financial distress, financial constraint and investment decision: Evidence from Brazil

This paper analyses the presence of financial constraint in the investment decisions of 367 Brazilian firms from 1997 to 2004, using a Bayesian econometric model with group-varying parameters. The motivation for this paper is the use of clustering techniques to group firms in a totally endogenous form. In order to classify the firms we used a hybrid clustering method, that is, hierarchical and non-hierarchical clustering techniques jointly. To estimate the parameters a Bayesian approach was considered. Prior distributions were assumed for the parameters, classifying the model in random or fixed effects. Ordinate predictive density criterion was used to select the model providing a better prediction. We tested thirty models and the better prediction considers the presence of 2 groups in the sample, assuming the fixed effect model with a Student t distribution with 20 degrees of freedom for the error. The results indicate robustness in the identification of financial constraint when the firms are classified by the clustering techniques. (C) 2010 Elsevier B.V. All rights reserved.

Sampled Control for Mean-Variance Hedging in a Jump Diffusion Financial Market

In this technical note we consider the mean-variance hedging problem of a jump diffusion continuous state space financial model with the re-balancing strategies for the hedging portfolio taken at discrete times, a situation that more closely reflects real market conditions. A direct expression based on some change of measures, not depending on any recursions, is derived for the optimal hedging strategy as well as for the ""fair hedging price"" considering any given payoff. For the case of a European call option these expressions can be evaluated in a closed form.

Multicollinearity and financial constraint in investment decisions: a Bayesian generalized ridge regression

This paper addresses the investment decisions considering the presence of financial constraints of 373 large Brazilian firms from 1997 to 2004, using panel data. A Bayesian econometric model was used considering ridge regression for multicollinearity problems among the variables in the model. Prior distributions are assumed for the parameters, classifying the model into random or fixed effects. We used a Bayesian approach to estimate the parameters, considering normal and Student t distributions for the error and assumed that the initial values for the lagged dependent variable are not fixed, but generated by a random process. The recursive predictive density criterion was used for model comparisons. Twenty models were tested and the results indicated that multicollinearity does influence the value of the estimated parameters. Controlling for capital intensity, financial constraints are found to be more important for capital-intensive firms, probably due to their lower profitability indexes, higher fixed costs and higher degree of property diversification.

The Controllership Relevance or Risk Management in non-Financial Companies: a study of risk managers` and controllers` perceptions

The purpose of this study is to analyze the Controllership relevance as support risk management in non-financial companies. Risk management is a widely discussed and disseminated subject amongst financial institutions. It is obvious that economic uncertainties and, consequently, prevention and. control must also exist in non-financial companies. To enable managers to take safe-decisions, it is essential for them to be able to count on instrumental support that provides timely and adequate information, to ensure lower levels of mistakes and risk exposure. However, discussion concerning risk management in non-financial companies is still in its early stages in Brazil. Considering this gap, this study aims at assessing how Controllership has been acting in? companies under the insight of risk and how it can contribute to risk management in non-financial companies. To achieve the proposed goal, a field research was. carried-out with non-financial companies that are located in the city Sao Paulo and listed in the Sao Paulo Stock Exchange (Bovespa). The research was carried out using questionnaires, which were sent do Risk Officers and Controllers of those companies with the purpose of evaluating their perception on the subject. The results,of the research allow us to conclude that Controllership offers support to risk management, through information that contributes to the mitigation of the risks in non-financial companies.

Diagnosis of Organizational Soft Problems in a Peruvian Financial Institution by Systemic Thinking

Managing financial institutions in an underdeveloped economic context has become a real challenge nowadays. In order to reach the organization`s planned goals, they have to deal with structural, behavioral and informational problems. From the systemic point of view, this situation gets even worse when the company does not present organizational boundaries and a cohesive identification for their stakeholders. Thus, European countries have some special financial lines in order to help the development of micro credit in Latin communities in an attempt to help the local economy. However, institutions like Caixa dos Andes in Peru present management problems when dealing with this complexity. Based on this, how can the systemic eye help in the diagnosis of soft problems of a Peruvian financial company? This study aims to diagnose soft problems of a Peruvian financial company based on soft variables like identity, communication and autonomy and also intends to identify possible ways to redesign its basic framework. The (VSM--Viable System Model) method from Beer (1967), applied in this diagnostic study, was used in a practical way as a management tool for organizations` analysis and planning. By describing the VSM`s five systems, the creation of a systemic vision or a total vision is possible, showing the organization`s complexity from the inside. Some company`s soft problems like double control, inefficient use of physical and human resources, low information flows, slowness, etc. The VSM presented an organizational diagnosis indicating effective solutions that do integrate its five systems.

Financial leverage and tangibility of assets of Brazilian companies of agribusiness in the post-real plan period

This paper aims to study the relationship between the debt level and the asset structure of Brazilian companies of the agribusiness sector, since it is considered a current and relevant discussion: to evaluate the mechanisms for fund-raising and guarantees. The methodology of Granger`s Causality test and Autoregressive Vectors was used to conduct a comparative analysis, applied to a financial database of companies with open capital of Brazilian agribusiness, in particular the agricultural sector and Fisheries and Food and Beverages in a period of 10 years (1997-2007) from quarterly series available in the database of Economatica(R). The results demonstrated that changes in leverage generate variations in the tangibility of the companies, a fact that can be explained by the large search of funding secured by fiduciary transfer of fixed assets, which facilitates access to credit by business of the Agribusiness sector, increasing the payment time and lowering interest rates.

Microscopic origin of non-Gaussian distributions of financial returns

In this paper we study the possible microscopic origin of heavy-tailed probability density distributions for the price variation of financial instruments. We extend the standard log-normal process to include another random component in the so-called stochastic volatility models. We study these models under an assumption, akin to the Born-Oppenheimer approximation, in which the volatility has already relaxed to its equilibrium distribution and acts as a background to the evolution of the price process. In this approximation, we show that all models of stochastic volatility should exhibit a scaling relation in the time lag of zero-drift modified log-returns. We verify that the Dow-Jones Industrial Average index indeed follows this scaling. We then focus on two popular stochastic volatility models, the Heston and Hull-White models. In particular, we show that in the Hull-White model the resulting probability distribution of log-returns in this approximation corresponds to the Tsallis (t-Student) distribution. The Tsallis parameters are given in terms of the microscopic stochastic volatility model. Finally, we show that the log-returns for 30 years Dow Jones index data is well fitted by a Tsallis distribution, obtaining the relevant parameters. (c) 2007 Elsevier B.V. All rights reserved.