Um estudo dos supermercados no Brasil: uma investigação sobre a demanda de mercado, a fatia de mercado e a área de influência

Esse trabalho dá continuidade a estudos anteriores e visa contribuir para o avanço da ainda embrionária teoria varejista. Conseguimos desenvolver e operacionalizar os conceitos de área de influência, demanda de mercado e fatia de mercado, e analisar os resultados desses indicadores para os 27 supermercados de São Paulo, que participaram de nossa extensa pesquisa empírica. Um processo de modelagem econométrica foi conduzido, resultando em um modelo de regressão múltipla que satisfatoriamente explica e prevê área de influência como função de três variáveis: tamanho da loja, densidade populacional e disponibilidade de transporte coletivo. Apoiado em rigorosa metodologia de previsão de mercado, o estudo também revela estimativas de mercado que substancialmente diferem dos valores que vem sendo publicados na mídia especializada do setor. Nossa estimativa da demanda de mercado para o setor 'supermercados' no Brasil, em 2002, chega a superar R$ 100 bilhões, enquanto que nossa projeção da concentração das 5 maiores empresas no setor é de apenas 25%.

Automatic model selection for forecasting brazilian stock returns

This study aims to contribute on the forecasting literature in stock return for emerging markets. We use Autometrics to select relevant predictors among macroeconomic, microeconomic and technical variables. We develop predictive models for the Brazilian market premium, measured as the excess return over Selic interest rate, Itaú SA, Itaú-Unibanco and Bradesco stock returns. We nd that for the market premium, an ADL with error correction is able to outperform the benchmarks in terms of economic performance. For individual stock returns, there is a trade o between statistical properties and out-of-sample performance of the model.

Automatic model selection for forecasting Brazilian stock returns

This study aims to contribute on the forecasting literature in stock return for emerging markets. We use Autometrics to select relevant predictors among macroeconomic, microeconomic and technical variables. We develop predictive models for the Brazilian market premium, measured as the excess return over Selic interest rate, Itaú SA, Itaú-Unibanco and Bradesco stock returns. We find that for the market premium, an ADL with error correction is able to outperform the benchmarks in terms of economic performance. For individual stock returns, there is a trade o between statistical properties and out-of-sample performance of the model.

Forecasting Brazilian inflation by its aggregate and disaggregated data: a test of predictive power by forecast horizon

This work aims to compare the forecast efficiency of different types of methodologies applied to Brazilian Consumer inflation (IPCA). We will compare forecasting models using disaggregated and aggregated data over twelve months ahead. The disaggregated models were estimated by SARIMA and will have different levels of disaggregation. Aggregated models will be estimated by time series techniques such as SARIMA, state-space structural models and Markov-switching. The forecasting accuracy comparison will be made by the selection model procedure known as Model Confidence Set and by Diebold-Mariano procedure. We were able to find evidence of forecast accuracy gains in models using more disaggregated data