Submitted by Adriano Faria (afaria@fgvmail.br) on 2017-12-13T19:49:29Z No. of bitstreams: 1 Tese_deFaria.pdf: 3657553 bytes, checksum: 11ec67914c866ca46d83c67c1592e093 (MD5) / Approved for entry into archive by GILSON ROCHA MIRANDA (gilson.miranda@fgv.br) on 2017-12-21T11:41:13Z (GMT) No. of bitstreams: 1 Tese_deFaria.pdf: 3657553 bytes, checksum: 11ec67914c866ca46d83c67c1592e093 (MD5) / Made available in DSpace on 2017-12-27T12:18:22Z (GMT). No. of bitstreams: 1 Tese_deFaria.pdf: 3657553 bytes, checksum: 11ec67914c866ca46d83c67c1592e093 (MD5) Previous issue date: 2017-03-16 / This thesis is a collection of essays in empirical finance mainly focused on term structure models. In the first three chapters, we developed methods to extract the yield curve from government and corporate bonds. We measure the performance of such methods in pricing, Value at Risk and forecasting exercises. In its turn, the last chapter brings a discussion about the effects of different metrics of the optimal portfolio on the estimation of a CCAPM model.In the first chapter, we propose a segmented model to deal with the seasonalities appearing in real yield curves. In different markets, the short end of the real yield curve is influenced by seasonalities of the price index that imply a lack of smoothness in this segment. Borrowing from the flexibility of spline models, a B-spline function is used to fit the short end of the yield curve, while the medium and the long end are captured by a parsimonious parametric four-factor exponential model. We illustrate the benefits of the proposed term structure model by estimating real yield curves in one of the biggest government index-linked bond markets in the world. Our model is simultaneously able to fit the yield curve and to provide unbiased Value at Risk estimates for different portfolios of bonds negotiated in this market.Chapter 2 introduces a novel framework for the estimation of corporate bond spreads based on mixture models. The modeling methodology allows us to enhance the informational content used to estimate the firm level term structure by clustering firms together using observable firm characteristics. Our model builds on the previous literature linking firm level characteristics to credit spreads. Specifically, we show that by clustering firms using their observable variables, instead of the traditional matrix pricing (cluster by rating/sector), it is possible to achieve gains of several orders of magnitude in terms of bond pricing. Empirically, we construct a large panel of firm level explanatory variables based on results from a handful of previous research and evaluate their performance in explaining credit spread differences. Relying on panel data regressions we identify the most significant factors driving the credit spreads to include in our term structure model. Using this selected sample, we show that our methodology significantly improves in sample fitting as well as produces reliable out of sample price estimations when compared to the traditional models.Chapter 3 brings the paper “Forecasting the Brazilian Term Structure Using Macroeconomic Factors”, published in Brazilian Review of Econometrics (BRE). This paper studies the forecasting of the Brazilian interest rate term structure using common factors from a wide database of macroeconomic series, from the period of January 2000 to May 2012. Firstly the model proposed by Moench (2008) is implemented, in which the dynamic of the short term interest rate is modeled using a Factor Augmented VAR and the term structure is derived using the restrictions implied by no-arbitrage. Similarly to the original study, this model resulted in better predictive performance when compared to the usual benchmarks, but presented deterioration of the results with increased maturity. To avoid this problem, we proposed that the dynamic of each rate be modeled in conjunction with the macroeconomic factors, thus eliminating the no-arbitrage restrictions. This attempt produced superior forecasting results. Finally, the macro factors were inserted in a parsimonious parametric three-factor exponential model.The last chapter presents the paper “Empirical Selection of Optimal Portfolios and its Influence in the Estimation of Kreps-Porteus Utility Function Parameters”, also published in BRE. This paper investigates the effects on the estimation of parameters related to the elasticity of intertemporal substitution and risk aversion, of the selection of different portfolios to represent the optimal aggregate wealth endogenously derived in equilibrium models with Kreps-Porteus recursive utility. We argue that the usual stock market wide index is not a good portfolio to represent optimal wealth of the representative agent, and we propose as an alternative the portfolio from the Investment Fund Industry. Especially for Brazil, where that industry invests most of its resources in fixed income, the aforementioned substitution of the optimal proxy portfolio caused a significant increase in the risk aversion coefficient and the elasticity of the intertemporal substitution in consumption.