The main purpose of this article is to introduce the technique of panel data analysis in econometrics modeling. The elasticity of labour, capital and economic of scale for twenty two food manufacturing firms covering from 1989 to 1993 is estimated using the Cobb-Douglas model. The three main techniques of panel data analysis discussed are least square dummy variables (LSDV), analysis of covariance (ANCOVA) and generalized least square (GLS). Ordinary Least Square (OLS) method is included as the basis of comparison.
This study proposes a simple methodology to estimate the power-law tail index of the Malaysian stock exchange by using the maximum likelihood Hill’s estimator. Recursive procedures base on empirical distribution tests are use to determine the threshold number of observations in the tail estimation. The threshold extreme values can be selected bases on the desired level of p-value in the goodness-of-fit tests. Finally, these procedures are apply to three indices in the Malaysian stock exchange.
In this research we introduce an analyzing procedure using the Kullback-Leibler information criteria (KLIC) as a statistical tool to evaluate and compare the predictive abilities of possibly misspecified density forecast models. The main advantage of this statistical tool is that we use the censored likelihood functions to compute the tail minimum of the KLIC, to compare the performance of a density forecast models in the tails. Use of KLIC is practically attractive as well as convenient, given its equivalent of the widely used LR test. We include an illustrative simulation to compare a set of distributions, including symmetric and asymmetric distribution, and a family of GARCH volatility models. Our results on simulated data show that the choice of the conditional distribution appears to be a more dominant factor in determining the adequacy and accuracy (quality) of density forecasts than the choice of volatility model.
This paper analyzes the asymmetric long memory volatility dependency of the interday prices of Composite Index (CI) at Bursa Malaysia by using GARCH family models. The GARCH type models are used with the assumption that the innovations series follow either one of the following distributions: Gaussian, Student -t and skewed Student -t. The stock returns' long memory dependency is determined using the Hurst parameter. The long memory and asymmetric volatility are modelled by fractionally integrated GARCH models. It is found that the asymmetric and long memory GARCH models with skewed student-t distribution give better predictive ability on the volatility of the Kuala Lumpur Composite Index (KLCI).
The accuracy of financial time series forecasts often rely on the model precision and the availability of actual observations for forecast evaluations. This study aimed to tackle these issues in order to obtain a suitable asymmetric time-varying volatility model that outperformed in the forecast evaluations based on interday and intraday data. The model precision was examined based on the most appropriate time-varying volatility representation under the autoregressive conditional heteroscedascity framework. For forecast precision, the evaluations were conducted under three loss functions using the volatility proxies and realized volatility. The empirical studies were implemented on two major financial markets and the estimated results are applied in quantifying their market risks. Empirical results indicated that Zakoian model provided the best in-sample forecasts whereas DGE on the other hand indicated better out-of-sample forecasts. For the type of volatility proxy selection, the implementation of intraday data in the latent volatility indicated significant improvement in all the time horizon forecasts.
This study investigates the value-at-risk (VaR) using nonlinear time-varying volatility (ARCH model) and extreme-value-theory (EVT) methodologies. Similar VaR estimation and prediction are observes under the EVT and heavy-tailed long-memory ARCH approaches. The empirical results evidence the EVT-based VaR are more accurate but only at higher quantiles. It is also found that EVT approach is able to provide a convenient framework for asymmetric properties in both the lower and upper tails which implies that the risk and reward are not equally likely for the short- and long-trading positions in Malaysian stock market.
The main objective of this paper is to explore the varying volatility dynamic of inflation rate in Malaysia for the period from January 1980 to December 2004. The GARCH, GARCH-Mean, EGARCH and EGARCH-Mean models are used to capture the stochastic variation and asymmetries in the economic instruments. Results show that the EGARCH model gives better estimates of sub-periods volatility. Further analysis using Granger causality test show that there is sufficient empirical evidence that higher inflation rate level will result in higher future inflation uncertainty and higher level of inflation uncertainty will lead to lower future inflation rate.
This article study the influences of structural break to the fractionally integrated time-varying volatility model in Malaysian stock markets from year 1996 to 2006. A fractionally integrated autoregressive conditional heteroscedastic (FIGARCH) model combines with sudden changes of volatility is develops to study the possibility of structural change in Asian financial crisis and currency crisis. Our empirical results evidence substantially reduction in long memory clustering volatility after the inclusion of sudden changes in the volatility. Finally, the estimation, diagnostic and model selection evaluations indicate that the fractionally integrated model with structural change is out-performed compared to the standard model.
Expectation Maximization (EM) algorithm has experienced a significant increase in terms of usage in many fields of study. In this paper, the performance of the said algorithm in finding the Maximum Likelihood for the Gaussian Mixed Models (GMM), a probabilistic model normally used in fraud detection and recognizing a person’s voice in speech recognition field, is shown and discussed. At the end of the paper, some suggestions for future research works will also be given.