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EnglishHaving in mind the importance of Value at Risk (VaR) as a risk measure for financial institutions and rating agencies, this study evaluated whether the ARLS model is more accurate in the calculation of the long term VaR than the traditional models, considering it is more appropriate for predicting the long-term volatility. Due to the fact that VaR s being used for market players as a measure of risk for the portfolio management, its proper measurement is important. Based on daily data from the stock markets and exchange of BRICS (Brazil, Russia, India, China and South Africa) future volatilities for 15 days, 1 month and 3 months ahead were calculated. Then the traditional measures of VaR accuracy were calculated. The results suggest the superiority of ARLS model for predicting the exchange rate volatility, being able to predict precisely the number of violations in 33% of cases, while traditional models did not perform well. Regarding the stock market, GARCH and ARLS models showed similar performance, with higher accuracy of the GARCH model considering the quadratic average loss function. These results have shown that the choice of ARLS model in VaR calculation to currency portfolios is better due to higher achieved accuracy, thus helping market participants to better manage the risk of their portfolios. In relation to the stock market, considering the similar performance of GARCH and ARLS models, the GARCH model is more suitable because of its greater simplicity and easy computational implementation. portuguesTendo em vista a importância do Value at Risk (VaR) como medida de risco para instituicoes financeiras e agencias de risco, o presente estudo avaliou se o modelo ARLS e mais preciso no calculo do VaR de longo prazo que os modelos tradicionais, dada sua maior adequacao para a previsao da volatilidade. Considerando a utilizacao do VaR pelos agentes de mercado como medida de risco para o gerenciamento de portfolios e importante sua adequada mensuracao. A partir de dados diarios dos mercados de acoes e cambial dos BRICS (Brasil, Russia, India, China e Africa do Sul) foram calculadas as volatilidades futuras para 15 dias, 1 mes e 3 meses. Em seguida, calculou-se as medidas tradicionais de avaliacao da precisao do VaR. Os resultados sugerem a superioridade do modelo ARLS para a previsao da volatilidade cambial, capaz de prever corretamente o numero de violacoes em 33% dos casos, enquanto os modelos tradicionais nao obtiveram um bom desempenho. Com relacao ao mercado acionario, os modelos GARCH e ARLS apresentaram desempenho similar. O modelo GARCH e superior considerando a perda media quadratica. Esses resultados apontam para a escolha do modelo ARLS no calculo do VaR de portfolios cambiais devido a maior precisao alcancada. Ajuda assim os agentes de mercado a melhor gerirem o risco de suas carteiras. Em relacao ao mercado acionario, em funcao do desempenho similar dos modelos GARCH e ARLS, o modelo GARCH e o mais indicado devido a sua maior simplicidade e facil implementacao computacional.

Modelo de Previsão de Value at Risk Utilizando Volatilidade de Longo Prazo