The impact of rare disasters on equity premium and term premium in a New Keynesian DSGE model is explored in the thesis. Andreasen's (2012) model with Epstein-Zin preferences, bonds and a rare disaster shock in total factor productivity process is extended by a variable capital stock and an equity-type asset. We find that the variable capital significantly changes behavior of the model, capital depreciation must be substantially increased to counter the effect of variable capital and stochastic mean of inflation increases. The model calibrated to the US economy and a high risk aversion generates 10-year term premium of 90 basis points, rare disasters increase the premium only by 3 basis points. The equity premium is 163 basis points and rare disasters increase it also only by 3 basis points. The model with a low coefficient of relative risk aversion of 5.5 generates negative risk premia. Rare disasters increase the risk premia by mere 4 basis points in comparison to a model with i.i.d. shocks. Powered by TCPDF (www.tcpdf.org)

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This paper estimates the zero coupon yield curve for the Peruvian government bond market. We employ two methods of estimation proposed by Nelson y Siegel (1987) and Svensson (1994). Model performance is evaluated based on criteria of goodness of fit, flexibility and parameter stability, by using alternative objective functions for parameter estimation. The Svensson model shows on average a better adjustment; however, parameter estimates are more unstable when data availability is limited —for example when there is a small number of transactions in the secondary market— in which case is better to use the Nelson y Siegel estimates. At the end of the paper, yield curve estimates are used to derive market expectations of future short term interest rates, that are valuable sources of information for central bank’s monetary policy. / En el presente documento se estiman dos modelos para la curva de rendimiento en soles para el Perú, el modelo de Nelson y Siegel (1987) y el modelo de Svensson (1994). Se compara el desempeño de ambos modelos en términos de ajuste, flexibilidad y estabilidad de sus parámetros, y se evalúan funciones objetivo de estimación alternativas. El modelo de Svensson tiene el mejor ajuste, sin embargo, es más inestable cuando no se dispone de datos suficientes para los diferentes plazos de la curva de rendimiento —por la ausencia de emisiones o de precios cuando la negociación en el mercado secundario es incipiente— en cuyo caso es preferible el uso del modelo de Nelson y Siegel. En la parte final se muestra el uso de las curvas de rendimiento cupón cero estimadas como fuente de información de los bancos centrales sobre las expectativas del mercado para la evolución futura de la tasa interbancaria.

[pt] O presente trabalho traz 6 diferentes técnicas de previsão para a variação mensal do Índice da Produção Industrial americana em 3 ambientes diferentes totalizando 18 modelos. No primeiro ambiente foram usados como variáveis explicativas a própria defasagem da variação mensal do Índice da produção industrial e outras 55 variáveis de mercado e de expectativa tais quais retornos setoriais, prêmio de risco de mercado, volatilidade implícita, prêmio de taxa de juros (corporate e longo prazo), sentimento do consumidor e índice de incerteza. No segundo ambiente foi usado à data base do FRED com 130 variáveis econômicas como variáveis explicativas. No terceiro ambiente foram usadas as variáveis mais relevantes do ambiente 1 e do ambiente 2. Observa-se no trabalho uma melhora em prever o IP contra um modelo AR e algumas interpretações a respeito do comportamento da economia americana nos últimos 45 anos (importância de setores econômicos, períodos de incerteza, mudanças na resposta a prêmio de risco, volatilidade e taxa de juros). / [en] This thesis presents 6 different forecasting techniques for the monthly variation of the American Industrial Production Index in 3 different environments, totaling 18 models. In the first environment, the lags of the monthly variation of the industrial production index and other 55 market and expectation variables such as sector returns, market risk premium, implied volatility, and interest rate risk premiums (corporate premium and long term premium), consumer sentiment and uncertainty index. In the second environment was used the FRED data base with 130 economic variables as explanatory variables. In the third environment, the most relevant variables of environment 1 and environment 2 were used. It was observed an improvement in predicting IP against an AR model and some interpretations regarding the behavior of the American economy in the last 45 years (importance of sectors, uncertainty periods, and changes in response to risk premium, volatility and interest rate).