Search results for "Conditional variance"
showing 10 items of 10 documents
Asymmetric covariance in spot-futures markets
2003
This article studies how the spot-futures conditional covariance matrix responds to positive and negative innovations. The main results of the article are achieved by obtaining the Volatility Impulse Response Function (VIRF) for asymmetric multivariate GARCH structures, extending Lin (1997) findings for symmetric GARCH models. This theoretical result is general and can be applied to analyze covariance dynamics in any financial system. After testing how multivariate GARCH models clean up volatility asymmetries, the Asymmetric VIRF is computed for the Spanish stock index IBEX-35 and its futures contract. The empirical results indicate that the spot-futures variance system is more sensitive to…
Some extensions of multivariate sliced inverse regression
2007
Multivariate sliced inverse regression (SIR) is a method for achieving dimension reduction in regression problems when the outcome variable y and the regressor x are both assumed to be multidimensional. In this paper, we extend the existing approaches, based on the usual SIR I which only uses the inverse regression curve, to methods using properties of the inverse conditional variance. Contrary to the existing ones, these new methods are not blind for symmetric dependencies and rely on the SIR II or SIRα. We also propose their corresponding pooled slicing versions. We illustrate the usefulness of these approaches on simulation studies.
Has the Introduction of Bitcoin Futures on Regulated Exchanges Decreased Price Volatility?
2019
Master's thesis Business Administration BE501 - University of Agder 2019 Bitcoin is a tremendously debated phenomenon in the world of finance and in recent the scientific literature on the topic has expanded. In this thesis,the bitcoin to US dollar exchange rate is examined through various conditional variance models to describe its highly volatile nature. We examine whether the introduction of bitcoin futurescontractsin late 2017 has had a decreasing impact on price volatility by estimatingthe unconditional variance. The log-return of the bitcoin exchange rate is analysed,and there is evidence of volatility clustering and time-varying volatility. Consequently, the variance is modelled thro…
Response models for mixed binary and quantitative variables
1992
SUMMARY A number of special representations are considered for the joint distribution of qualitative, mostly binary, and quantitative variables. In addition to the conditional Gaussian models and to conditional Gaussian regression chain models some emphasis is placed on models derived from an underlying multivariate normal distribution and on models in which discrete probabilities are specified linearly in terms of unknown parameters. The possibilities for choosing between the models empirically are examined, as well as the testing of independence and conditional independence and the estimation of parameters. Often the testing of independence is exactly or nearly the same for a number of di…
Nonlinear GARCH models for highly persistent volatility
2005
In this paper we study new nonlinear GARCH models mainly designed for time series with highly persistent volatility. For such series, conventional GARCH models have often proved unsatisfactory because they tend to exaggerate volatility persistence and exhibit poor forecasting ability. Our main emphasis is on models that are similar to previously introduced smooth transition GARCH models except for the novel feature that a lagged value of conditional variance is used as the transition variable. This choice of the transition variable corresponds to the idea that high persistence in conditional variance is related to relatively infrequent changes in regime. U sing the theory of Markov chains w…
Parameter orthogonality and conditional profile likelihood: the exponential power function case
1999
Orthogonality, according to Fisher’s metrics, between the parameters of a probability density function, as well as giving rise to a series of statistical implications, makes it possible to express a function of conditional profile likelihood with better properties than the ordinary profile likelihood function. In the present paper the parameters of exponential power function are made orthogonal and the conditional profile likelihood of the shape parameter p is determined in order to study its properties with reference to p estimation. Moreover, by means of a simulation plan, a comparison is made between the estimates of p obtained from the conditional profile log-likelihood and those obtain…
Modeling Conditional Skewness in Stock Returns
2007
Abstract In this paper, we propose a new GARCH-in-Mean (GARCH-M) model allowing for conditional skewness. The model is based on the so-called z distribution capable of modeling skewness and kurtosis of the size typically encountered in stock return series. The need to allow for skewness can also be readily tested. The model is consistent with the volatility feedback effect in that conditional skewness is dependent on conditional variance. Compared to previously presented GARCH models allowing for conditional skewness, the model is analytically tractable, parsimonious and facilitates straightforward interpretation.Our empirical results indicate the presence of conditional skewness in the mon…
Decomposing changes in the conditional variance of GDP over time
2017
A well established fact in the growth empirics literature is the increasing (unconditional) variation in output per capita across countries. We propose a nonparametric decomposition of the conditional variation of output per capita across countries to capture different channels over which the variation might be increasing. We find that OECD countries have experienced diminishing conditional variation while other regions have experienced increasing conditional variation. Our decomposition suggests that most of these changes in the conditional variance of output are due to unobserved factors not accounted for by the traditional growth determinants. In addition to this we show that these facto…
No linealidad y asimetría en el proceso generador del Índice Ibex35
2013
This paper analyzes the behavior of Ibex35 from January 1999 to December 2001, in order to check if it follows a different process from random walk so its return is not a white noise and it can be predictable, against the efficient market hypothesis. For that, a nonlinear generating process of return will be considered and a STAR-APARCH model will be specified. This model allows a nonlinear behavior in the conditional mean and in the conditional variance. The empirical results show that the Ibex35 follows a nonlinear and asymmetric process, both in the conditional mean as in the conditional variance, so the weak-version of efficient market hypothesis is rejected. El trabajo analiza el compo…
Exponential inequalities and estimation of conditional probabilities
2006
This paper deals with the problems of typicality and conditional typicality of “empirical probabilities” for stochastic process and the estimation of potential functions for Gibbs measures and dynamical systems. The questions of typicality have been studied in [FKT88] for independent sequences, in [BRY98, Ris89] for Markov chains. In order to prove the consistency of estimators of transition probability for Markov chains of unknown order, results on typicality and conditional typicality for some (Ψ)-mixing process where obtained in [CsS, Csi02]. Unfortunately, lots of natural mixing process do not satisfy this Ψ -mixing condition (see [DP05]). We consider a class of mixing process inspired …