Carlos Maquieira

Nonlinearities And Garch Inadequacy For Modeling Stock Market Returns: Empirical Evidence From Latin America

In this paper, we analyze the adequacy of using GARCH as the data-generating process to model conditional volatility of stock market index rates-of-return series. Using the Hinich portmanteau bicorrelation test, we find that a GARCH formulation or any of its variants fail to provide an adequate characterization for the underlying process of the main Latin American stock market indices. Policymakers need to be careful when using autoregressive models for policy analysis and forecast because the inadequacy of GARCH models has strong implications for the pricing of stock index options, portfolio selection, and risk management. In particular, measures of spillover effects and output volatility may not be correct when GARCH-type models are used to evaluate economic policy.

Adoption of IFRS in an emerging market: the Chilean case

Purpose The purpose of this paper is to analyze the impact triggered by adopting International Financial Reporting Standards (IFRS) in South America. In order to do this, the case of Chile is considered, as it was the first country in the region to adopt IFRS in full form from 2009. Design/methodology/approach The authors analyze a sample of 43 Chilean companies. The analysis has two stages. First, the authors analyze if the adoption of IFRS in Chile produced a statistically significant change in the main financial indicators. Then, the authors analyze the market reaction to the announcement of the adoption and implementation of IFRS, by doing an event study. Findings The authors found that adopting IFRS in Chile produced a statistically significant change in the main financial indicators, except for in leverage and Price-Earnings Ratios. As for the main accounts of the financial statements, the authors found significant differences, with the exception of inventories and current assets. However, after ass...

Nonlinear behaviour in EMBI series from Eastern Europe: evidence of 'window size effect'

The main objective of this article is to explore how the number of observations included in a window may impact the rejection rate of linear windows. We employ two methodologies proposed in the literature in order to study the linear and nonlinear behaviour. We use daily Emerging Markets Bond Index (EMBI) index spreads from six of the most important Eastern European countries (Bulgaria, Hungry, Poland, Russia, Serbia and Ukraine). The empirical results show what we call ‘window size effect’ because when we include more than 50 observations in each window, the rejection rate increases using the two different methodologies. Therefore, our findings support the idea that, even in this well informed and sophisticated market, the weak-form of the efficient market hypothesis cannot be confirmed.