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Title:Essays in asset prices and macroeconomics
Author(s):Nivin Valdiviezo, Rafael J.
Director of Research:Villamil, Anne
Doctoral Committee Chair(s):Villamil, Anne
Doctoral Committee Member(s):Krasa, Stefan; Parente, Stephen; Yannelis, Nicholas C.
Department / Program:Economics
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Recursive preferences
Housing supply
Risk neutral density
Smoothing splines
Abstract:This dissertation is composed by two chapters relating asset prices and macroeconomic dynamics, the first one explores this relationship from a theoretical point of view while the second chapter is focused on a more empirical approach to use information from asset prices. The first chapter contributes with the macro- finance literature of asset pricing in a general equilibrium framework. A Dynamic Stochastic General Equilibrium Model is developed aiming to replicate simultaneously the historical regularities for both macroeconomic and financial variables for the US economy. In a framework that includes households with recursive preferences for consumption goods and housing services in a two sector production economy that includes long run technological shocks, the model delivers several regularities about asset pricing behavior consistent with the US historical data and also some regularities about macroeconomic variables. In particular, the model deliver a high equity premium, high volatility of equity returns and a low autocorrelation of equity returns. Moreover, by including an endogenously determination of housing supply, in combination with consumer's preference for housing services, the model also delivers a series of regularities about housing variables (risk premium, volatility and auto-correlation). In addition to, the model generates a more significant welfare cost of the business cycle in comparison with standard DSGE models, which is an important feature when trying to replicate asset pricing behavior in a general equilibrium framework. The second chapter reviews the main methodologies that have been using in recent years to extract market expectations implicit in derivative prices. Through recovering the density functions of the price of the underlying asset on the maturity date of options negotiated on the market (called implied risk-neutral probability density functions or RNDs) it is possible to track how market expectations over a particular financial asset evolve over time, providing a useful tool to assess the risk of financial assets. This chapter highlights the main difficulties that need to be faced when trying to estimate RNDs. A Monte Carlo analysis is implemented to check the robustness of the estimation method used here to obtain the RNDs from option price data, smoothing splines. An application for the Brazilian exchange rate is implemented to show the usefulness of this methodology, especially to identify changes on market expectations for emerging market's exchange rates in the wake of the US "taper tantrum".
Issue Date:2018-04-12
Rights Information:Copyright 2018 Rafael J. Nivin Valdiviezo.
Date Available in IDEALS:2018-09-04
Date Deposited:2018-05

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