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Emma M. Iglesias

Bio: Emma M. Iglesias is an academic researcher from University of A Coruña. The author has contributed to research in topics: Estimator & Autoregressive conditional heteroskedasticity. The author has an hindex of 12, co-authored 59 publications receiving 534 citations. Previous affiliations of Emma M. Iglesias include Cardiff University & Michigan State University.


Papers
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TL;DR: In this paper, the spatial Probit models for cross-sectional dependent data in a binary choice context are analyzed and partial maximum likelihood estimators are introduced and they are shown to be consistent and asymptotically normal under some regularity conditions.

77 citations

Journal ArticleDOI
TL;DR: In this article, a block bootstrap procedure based on resampling of the likelihood function has been proposed for estimating GARCH models, and sufficient conditions for higher order refinements for equally tailed and symmetric test statistics.

44 citations

Posted Content
TL;DR: In this paper, a new semiparametric estimator for an empirical asset pricing model with general nonparametric risk-return tradeoff and a GARCH process for the underlying volatility is introduced.
Abstract: A new semiparametric estimator for an empirical asset pricing model with general nonparametric risk-return tradeoff and a GARCH process for the underlying volatility is introduced. The estimator does not rely on any initial parametric estimator of the conditional mean function, and this feature facilitates the derivation of asymptotic theory under possible nonlinearity of unspecified form of the risk-return tradeoff. Besides the nonlinear GARCH-in-mean effect, our specification accommodates exogenous regressors that are typically used as conditioning variables entering linearly in the mean equation, such as the dividend yield. Using the profile likelihood approach, we show that our estimator under stated conditions is consistent, asymptotically normal, and efficient, i.e. it achieves the semiparametric lower bound. A sampling experiment provides evidence on finite sample properties as well as comparisons with the fully parametric approach and the iterative semiparametric approach using a parametric initial estimate proposed by Conrad and Mammen (2008). An empirical application to the daily S&P 500 stock market returns suggests that the linear relation between conditional expected return and conditional variance of returns from the literature is misspecified, and this could be the reason for the disagreement on the sign of the relation.

40 citations

Journal ArticleDOI
TL;DR: In this paper, a new semiparametric estimator for an empirical asset pricing model with general nonparametric risk-return tradeoff and GARCH-type underlying volatility is introduced.

37 citations

Journal ArticleDOI
TL;DR: In this article, the authors analyse the impact of interest rate volatility on interest rates and the monetary transmission mechanism in the countries of the CSME 2 using the asymmetric TAR and MTAR cointegration models by Enders and Siklos (2001) and the EC-EGARCH(1, 1)-M model by Wang and Lee (2009), who examined the same issue for the US and nine Asian countries.

25 citations


Cited by
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TL;DR: In this article, a computer program for modelling financial time series is presented, based on the Random Walk Hypothesis, which is used to forecast trends in prices in futures markets.
Abstract: Features of Financial Returns Modelling Price Volatility Forecasting Standard Deviations The Accuracy of Autocorrelation Estimates Testing the Random Walk Hypothesis Forecasting Trends in Prices Evidence Against the Efficiency of Futures Markets Valuing Options Appendix: A Computer Program for Modelling Financial Time Series.

1,115 citations

Posted Content
TL;DR: In this article, the authors generalise l'estimateur bien connu de Hill de lindice d a fonction de reparatition avec queue de variation reguliere a une estimation de l'indice of a loi de valeurs extremes.
Abstract: On generalise l'estimateur bien connu de Hill de l'indice d'une fonction de reparatition avec queue de variation reguliere a une estimation de l'indice d'une loi de valeurs extremes. On demontre la convergence et la normalite asymptotique. On utilise l'estimateur pour certaines estimations comme celle d'une quantile elevee et d'un point d'extremite

655 citations

Posted Content
TL;DR: In this article, the expectation and covariance matrix of the Wishart distribution are derived, where the expectation is derived from the expectation matrix of a square matrix containing only zeros and ones.
Abstract: The commutation matrix $K$ is defined as a square matrix containing only zeroes and ones. Its main properties are that it transforms vecA into vecA', and that it reverses the order of a Kronecker product. An analytic expression for $K$ is given and many further properties are derived. Subsequently, these properties are applied to some problems connected with the normal distribution. The expectation is derived of $\varepsilon' A\varepsilon\cdot\varepsilon' B\varepsilon\cdot\varepsilon'C\varepsilon$, where $\varepsilon \sim N(0, V)$, and $A, B, C$ are symmetric. Further, the expectation and covariance matrix of $x \otimes y$ are found, where $x$ and $y$ are normally distributed dependent variables. Finally, the variance matrix of the (noncentral) Wishart distribution is derived.

443 citations

Journal ArticleDOI
TL;DR: In this paper, a new measure of risk based entirely on downward moves measured using high frequency data is proposed, based on the theory of probability theory, drawing on some new results from probability theory.
Abstract: We propose a new measure of risk, based entirely on downward moves measured using high frequency data. Realised semivariances are shown to have important predictive qualities for future market volatility. The theory of these new measures is spelt out, drawing on some new results from probability theory.

287 citations

01 Jan 2001
TL;DR: In this article, the authors investigated the dynamic causal linkages among nine major international stock price indexes and found significant interdependencies between the established OECD and the Asian markets, and also the leadership of the US and UK markets over the short and long run.
Abstract: This paper investigates the dynamic causal linkages amongst nine major international stock price indexes. In order to gauge the causal transmission patterns we employ very recent methods of: (i) vector error-correction modeling and (ii) level VAR modeling with possibly integrated and cointegrated processes, advocated by: (i) Toda and Phillips (Econometrica, 61 (1993) 1367) and (ii) Toda and Yamamoto (J. Econometrics, 66 (1995) 225), respectively. The paper illustrates how such methods may be appropriately augmented in a compatible fashion to unearth previously unfounded linkage properties inherent amongst a system of stock price indexes. In particular, we demonstrate that previous research, by using ordinary difference VARs, ignored an important component of linkages displayed purely over the long run. This untapped evidence essentially provides robust and very useful information to international financial analysts and investors. At a substantive level, results of this study tend to support the contention offered by several studies in the literature of significant interdependencies between the established OECD and the Asian markets, and also the leadership of the US and UK markets over the short and long run. The levels VAR, however, illustrate the Japanese market's influence as an additional long run leader. Findings seem to be plausible given that these three markets (US, UK and Japan) have consistently contributed over 75% of global stock market capitalization over the major part of the sample under consideration. At a methodological level, this analysis also provides a primer for the wealth of applied financial econometric research focusing on dynamic causal inference which involve systems containing possibly integrated and cointegrated processes.

269 citations