Tests of conditional asset pricing models in the brazilian stock market

In this paper, we test a version of the conditional CAPM with respect to a local market portfolio, proxied by the Brazilian stock index during the period 1976-1992. We also test a conditional APT modeI by using the difference between the 3-day rate (Cdb) and the overnight rate as a second factor in addition to the market portfolio in order to capture the large inflation risk present during this period. The conditional CAPM and APT models are estimated by the Generalized Method of Moments (GMM) and tested on a set of size portfolios created from individual securities exchanged on the Brazilian markets. The inclusion of this second factor proves to be important for the appropriate pricing of the portfolios.

A few more moments to finance theory: introducing higher moments in investment theory and econometrics

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The Capm and Fama-French models in Brazil: a comparative study

This paper confronts the Capital Asset Pricing Model - CAPM - and the 3-Factor Fama-French - FF - model using both Brazilian and US stock market data for the same Sample period (1999-2007). The US data will serve only as a benchmark for comparative purposes. We use two competing econometric methods, the Generalized Method of Moments (GMM) by (Hansen, 1982) and the Iterative Nonlinear Seemingly Unrelated Regression Estimation (ITNLSUR) by Burmeister and McElroy (1988). Both methods nest other options based on the procedure by Fama-MacBeth (1973). The estimations show that the FF model fits the Brazilian data better than CAPM, however it is imprecise compared with the US analog. We argue that this is a consequence of an absence of clear-cut anomalies in Brazilian data, specially those related to firm size. The tests on the efficiency of the models - nullity of intercepts and fitting of the cross-sectional regressions - presented mixed conclusions. The tests on intercept failed to rejected the CAPM when Brazilian value-premium-wise portfolios were used, contrasting with US data, a very well documented conclusion. The ITNLSUR has estimated an economically reasonable and statistically significant market risk premium for Brazil around 6.5% per year without resorting to any particular data set aggregation. However, we could not find the same for the US data during identical period or even using a larger data set. Este estudo procura contribuir com a literatura empírica brasileira de modelos de apreçamento de ativos. Dois dos principais modelos de apreçamento são Infrontados, os modelos Capital Asset Pricing Model (CAPM)e de 3 fatores de Fama-French. São aplicadas ferramentas econométricas pouco exploradas na literatura nacional na estimação de equações de apreçamento: os métodos de GMM e ITNLSUR. Comparam-se as estimativas com as obtidas de dados americanos para o mesmo período e conclui-se que no Brasil o sucesso do modelo de Fama e French é limitado. Como subproduto da análise, (i) testa-se a presença das chamadas anomalias nos retornos, e (ii) calcula-se o prêmio de risco implícito nos retornos das ações. Os dados revelam a presença de um prêmio de valor, porém não de um prêmio de tamanho. Utilizando o método de ITNLSUR, o prêmio de risco de mercado é positivo e significativo, ao redor de 6,5% ao ano.

Factors affecting the technical efficiency of production of the Brazilian banking system : a comparison of four statistical models in the context of data envelopment analysis

This paper uses an output oriented Data Envelopment Analysis (DEA) measure of technical efficiency to assess the technical efficiencies of the Brazilian banking system. Four approaches to estimation are compared in order to assess the significance of factors affecting inefficiency. These are nonparametric Analysis of Covariance, maximum likelihood using a family of exponential distributions, maximum likelihood using a family of truncated normal distributions, and the normal Tobit model. The sole focus of the paper is on a combined measure of output and the data analyzed refers to the year 2001. The factors of interest in the analysis and likely to affect efficiency are bank nature (multiple and commercial), bank type (credit, business, bursary and retail), bank size (large, medium, small and micro), bank control (private and public), bank origin (domestic and foreign), and non-performing loans. The latter is a measure of bank risk. All quantitative variables, including non-performing loans, are measured on a per employee basis. The best fits to the data are provided by the exponential family and the nonparametric Analysis of Covariance. The significance of a factor however varies according to the model fit although it can be said that there is some agreements between the best models. A highly significant association in all models fitted is observed only for nonperforming loans. The nonparametric Analysis of Covariance is more consistent with the inefficiency median responses observed for the qualitative factors. The findings of the analysis reinforce the significant association of the level of bank inefficiency, measured by DEA residuals, with the risk of bank failure.

Applying supply chain management models in the banking industry: a brazilian case analysis

The study presents the results and recommendations deriving from the application of two supply chain management analysis models as proposed by the Supply Chain Council (SCOR, version 10.0) and by Lambert (1997, Framework for Supply Chain Management) on the logistics of cash transfers in Brazil. Cash transfers consist of the transportation of notes to and from each node of the complex network formed by the bank branches, ATMs, armored transportation providers, the government custodian, Brazilian Central Bank and financial institutions. Although the logistic to sustain these operations is so wide-ranged (country-size), complex and subject to a lot of financial regulations and security procedures, it has been detected that it was probably not fully integrated. Through the use of a primary and a secondary data research and analysis, using the above mentioned models, the study ends up with propositions to strongly improve the operations efficiency