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Estimating Relative Risk Aversion, Risk-Neutral and Real-World Densities using Brazilian Real Currency Options

Ornelas, Jose Renato Haas; Barbachan, José Fajardo; Farias, Aquiles Rocha de
Fonte: Fundação Getúlio Vargas Publicador: Fundação Getúlio Vargas
Tipo: Artigo de Revista Científica
EN_US
Relevância na Pesquisa
35.75%
Building Risk-Neutral Densities (RND) from options data can provide market-implied expectations about the future behavior of a financial variable. And market expectations on financial variables may influence macroeconomic policy decisions. It can be useful also for corporate and financial institutions decision making. This paper uses the Liu et all (2007) approach to estimate the option-implied Risk-neutral densities from the Brazilian Real/US Dollar exchange rate distribution. We then compare the RND with actual exchange rates, on a monthly basis, in order to estimate the relative risk-aversion of investors and also obtain a Real-world density for the exchange rate. We are the first to calculate relative risk-aversion and the option-implied Real World Density for an emerging market currency. Our empirical application uses a sample of Brazilian Real/US Dollar options traded at BM&F-Bovespa from 1999 to 2011. The RND is estimated using a Mixture of Two Log-Normals distribution and then the real-world density is obtained by means of the Liu et al. (2007) parametric risktransformations. The relative risk aversion is calculated for the full sample. Our estimated value of the relative risk aversion parameter is around 2.7, which is in line with other articles that have estimated this parameter for the Brazilian Economy...

Variáveis macroeconômicas e retorno real do Ibovespa : uma avaliação linear e não-linear

Ramos, Pedro Lutz
Fonte: Universidade Federal do Rio Grande do Sul Publicador: Universidade Federal do Rio Grande do Sul
Tipo: Dissertação Formato: application/pdf
POR
Relevância na Pesquisa
45.61%
A relação entre Variáveis Macroeconômicas e o Retorno de Ações é de alta importância para pesquisas econômicas e financeiras, já que, quando descoberto, um mecanismo de conhecer ou prever o impacto dessas variáveis oportuniza uma melhor performance de investidores no mercado acionário. Nesse sentido, nosso trabalho testa nove variáveis macroeconômicas (Preço de Commodities, Taxa de Desemprego, Inflação, Agregados Monetários, Taxas de juros, Relative Money Market Rate (RMM), Produção Industrial, Hiato do Produto (GAP) e Taxa de juros dos EUA) contra o retorno real do Ibovespa, empregando regressões lineares, como tradicional na literatura, e modelos de mudança de regime markoviana (MSM), para avaliar melhor o impacto e poder de previsão do retorno sob uma economia tão perturbada por planos econômicos e crises financeiras. Além disso, realizamos uma rigorosa avaliação do poder preditivo através de testes dentro e fora da amostra, incluindo avaliações dos coeficientes estimados defasados, critérios de Informação de AIC e BIC, Razões de Erro Quadrático Médio e o Erro Absoluto Médio e testes de encompassing de Diebold e Mariano (1995), de Clark e Mccracken (2001) e de Mccracken (2007), combinados aos novos valores assintóticos de Clark e Mccracken (2001...

Predicting GDP growth in the Euro Area

Campos, Claúdia Cristina Marinho
Fonte: NSBE - UNL Publicador: NSBE - UNL
Tipo: Dissertação de Mestrado
Publicado em /01/2013 ENG
Relevância na Pesquisa
35.49%
A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics; Predicting GDP growth is a concern of several economic agents. The right way to model such variable is far from consensual. This paper’s goal is to compare different models for GDP growth forecasting in the euro area. For comparative purposes, an autoregressive model (which is used as benchmark) and two Autoregressive Distributed Models (ADL), which contain financial and non-financial variables, chosen based on the literature, are used. The main conclusion is that the ADL(2,1,1) considered has superior forecast performance in- and out-of-sample, although in this last case depending on the evaluation metric.

Modelación, pronóstico y evaluación de la volatilidad de índices que representan diversos activos de renta fija y renta variable que listan en el mercado de capitales colombiano

Posada Villada, Jorge Andrés
Fonte: Pontifícia Universidade Javeriana Publicador: Pontifícia Universidade Javeriana
Tipo: masterThesis; Tesis de Grado Maestría Formato: Pdf
Relevância na Pesquisa
55.5%
Este trabajo tiene como objetivo principal evaluar la capacidad predictiva relativa fuera de muestra de diversos modelos pertenecientes a la familia GARCH, incluyendo tres modelos asimétricos: TARCH, EGARCH y PARCH. Para caracterizar el mercado de renta variable se va a utilizar el Índice General de la Bolsa de Colombia-IGBC. El mercado de renta fija se va a caracterizar utilizando el índice representativo del mercado de deuda pública interna-IDXTES. También se incluye en el estudio la tasa de cambio COP/USD. Todos los modelos se comparan frente a un modelo base GARCH (1,1), utilizando la metodología desarrollada por Diebold y Mariano (DyM) (1995). Los resultados se resumen de la siguiente manera: Para pronósticos de uno hasta veinte días adelante, los modelos asimétricos entregan mejores pronósticos que el modelo GARCH (1,1), en especial el modelo EGARCH, según los valores del estadístico de DyM. Estos muestran que las diferencias son estadísticamente significativas para todos los períodos de predicción estudiados.; In this paper the main purpose is to examine the relative out of sample predictive ability of various models of the GARCH family, including asymmetric models, such as the TARCH, EGARCH and PARCH. The IGBC stock index is used to characterize the Colombian Stock Market. The IDXTES is used to characterize the Colombian Bond market and the COP/USD exchange rate is also included in the study. All the models were compared against a GARCH (1...

Choice of Sample Split in Out-of-Sample Forecast Evaluation

HANSEN, Peter Reinhard; TIMMERMANN, Allan
Fonte: Instituto Universitário Europeu Publicador: Instituto Universitário Europeu
Tipo: Trabalho em Andamento Formato: application/pdf; digital
EN
Relevância na Pesquisa
155.94%
Out-of-sample tests of forecast performance depend on how a given data set is split into estimation and evaluation periods, yet no guidance exists on how to choose the split point. Empirical forecast evaluation results can therefore be di cult to interpret, particularly when several values of the split point might have been considered. When the sample split is viewed as a choice variable, rather than being fixed ex ante, we show that very large size distortions can occur for conventional tests of predictive accuracy. Spurious rejections are most likely to occur with a short evaluation sample, while conversely the power of forecast evaluation tests is strongest with long out-of-sample periods. To deal with size distortions, we propose a test statistic that is robust to the effect of considering multiple sample split points. Empirical applications to predictability of stock returns and inflation demonstrate that out-of-sample forecast evaluation results can critically depend on how the sample split is determined.

General to specific modelling of exchange rate volatility : a forecast evaluation

Bauwens, Luc; Sucarrat, Genaro
Fonte: Universidade Carlos III de Madrid Publicador: Universidade Carlos III de Madrid
Tipo: info:eu-repo/semantics/workingPaper; info:eu-repo/semantics/workingPaper Formato: application/pdf
Publicado em 29/04/2008 ENG; ENG
Relevância na Pesquisa
75.65%
The general-to-specific (GETS) methodology is widely employed in the modelling of economic series, but less so in financial volatility modelling due to computational complexity when many explanatory variables are involved. This study proposes a simple way of avoiding this problem when the conditional mean can appropriately be restricted to zero, and undertakes an out-of-sample forecast evaluation of the methodology applied to the modelling of weekly exchange rate volatility. Our findings suggest that GETS specifications perform comparatively well in both ex post and ex ante forecasting as long as sufficient care is taken with respect to functional form and with respect to how the conditioning information is used. Also, our forecast comparison provides an example of a discrete time explanatory model being more accurate than realised volatility ex post in 1 step forecasting.

¿Qué tan buenos son los patrones del IGBC para predecir su comportamiento?: una aplicación con datos de alta frecuencia. Financial market and its patterns: a forecast evaluation with high frequency data

Alonso Cifuentes, Julio César; García, Juan Carlos
Fonte: Universidad Icesi; Facultad de Ciencias Administrativas y Económicas Publicador: Universidad Icesi; Facultad de Ciencias Administrativas y Económicas
Tipo: article; Artículo Formato: PDF; p.1-30; Electrónico
SPA
Relevância na Pesquisa
65.57%
Using 18 different specifications of the GARCH-M model and high frequency data for the Colombian exchange market index (IGBC), we evaluate the out-of-sample performance of the models. The models considered take in account the leverage effect, the day-of-the-week effect, and the hour-of-the-day effect. We evaluate 1000 one-step-ahead rolling forecasts for each of the 18 models. Using different descriptive statistics and the Granger and Newbold (1976) test and the Diebold and Mariano (1995) test, we found that the best model would be the GARCH-M without the leverage effect, the day-of-the-week effect, and the hour-of-the-day effect.

Finite sample forecasting with estimated temporally aggregated linear processes

Grigoryeva, Lyudmila; Ortega, Juan-Pablo
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 19/09/2012
Relevância na Pesquisa
25.56%
We propose a finite sample based predictor for estimated linear one dimensional time series models and compute the associated total forecasting error. The expression for the error that we present takes into account the estimation error. Unlike existing solutions in the literature, our formulas require neither assumptions on the second order stationarity of the sample nor Monte Carlo simulations for their evaluation. This result is used to prove the pertinence of a new hybrid scheme that we put forward for the forecast of linear temporal aggregates. This novel strategy consists of carrying out the parameter estimation based on disaggregated data and the prediction based on the corresponding aggregated model and data. We show that in some instances this scheme has a better performance than the "all-disaggregated" approach presented as optimal in the literature.

Modelling and forecasting stochastic volatility

Lopes Moreira da Veiga, Maria Helena
Fonte: Bellaterra : Universitat Autònoma de Bellaterra, Publicador: Bellaterra : Universitat Autònoma de Bellaterra,
Tipo: Tesis i dissertacions electròniques; info:eu-repo/semantics/doctoralThesis Formato: application/pdf
Publicado em //2004 ENG; ENG
Relevância na Pesquisa
35.59%
Consultable des del TDX; Títol obtingut de la portada digitalitzada; El objetivo de esta tesis es modelar y predecir la volatilidad de las series financieras con modelos de volatilidad en tiempo discreto y continuo. En mi primer capítulo, intento modelar las principales características de las series financieras, como a persistencia y curtosis. Los modelos de volatilidad estocástica estimados son extensiones directas de los modelos de Gallant y Tauchen (2001), donde incluyo un elemento de retro-alimentación. Este elemento es de extrema importancia porque permite captar el hecho de que períodos de alta volatilidad están, en general, seguidos de periodos de gran volatilidad y viceversa. En este capítulo, como en toda la tesis, uso el método de estimación eficiente de momentos de Gallant y Tauchen (1996). De la estimación surgen dos modelos posibles de describir los datos, el modelo logarítmico con factor de volatilidad y retroalimentación y el modelo logarítmico con dos factores de volatilidad. Como no es posible elegir entre ellos basados en los tests efectuados en la fase de la estimación, tendremos que usar el método de reprogección para obtener mas herramientas de comparación. El modelo con un factor de volatilidad se comporta muy bien y es capaz de captar la «quiebra» de los mercados financieros de 1987. En el segundo capítulo...

Evaluation and combination of conditional quantile forecasts

Giacomini, Raffaella; Komunjer, Ivana
Fonte: Instituto de Tecnologia da Califórnia Publicador: Instituto de Tecnologia da Califórnia
Tipo: Article; PeerReviewed Formato: application/pdf
Publicado em /10/2005
Relevância na Pesquisa
45.61%
We propose an encompassing test for comparing conditional quantile forecasts in an out-of-sample framework. Our test provides a basis for forecast combination when encompassing is rejected. Its central features are (1) use of the "tick" loss function, (2) a conditional approach to out-of-sample evaluation, and (3) derivation in an environment with asymptotically nonvanishing estimation uncertainty. Our approach is valid under general conditions; the forecasts can be based on nested or nonnested models and can be obtained by general estimation procedures. We illustrate the test properties in a Monte Carlo experiment and apply it to evaluate and compare four popular value-at-risk models.

Diagnostic checking and intra-daily effects in time series models

Koopman, Siem Jan
Fonte: London School of Economics and Political Science Thesis Publicador: London School of Economics and Political Science Thesis
Tipo: Thesis; NonPeerReviewed Formato: application/pdf
Publicado em //1992 EN
Relevância na Pesquisa
25.53%
A variety of topics on the statistical analysis of time series are addressed in this thesis. The main emphasis is on the state space methodology and, in particular, on structural time series (STS) models. There are now many applications of STS models in the literature and they have proved to be very successful. The keywords of this thesis vary from - Kalman filter, smoothing and diagnostic checking - to - time-varying cubic splines and intra-daily effects -. Five separate studies are carried out for this research project and they are reflected in the chapters 2 to 6. All studies concern time series models which are placed in the state space form (SSF) so that the Kalman filter (KF) can be applied for estimation. The SSF and the KF play a central role in time series analysis that can be compared with the important role of the regression model and the method of least squares estimation in econometrics. Chapter 2 gives an overview of the latest developments in the state space methodology including diffuse likelihood evaluation, stable calculations, etc. Smoothing algorithms evaluate the full sample estimates of unobserved components in time series models. New smoothing algorithms are developed for the state and the disturbance vector of the SSF which are computationally efficient and outperform existing methods. Chapter 3 discusses the existing and the new smoothing algorithms with an emphasis on theory...