Analysing nancial data using Polya treesBy
نویسنده
چکیده
We present a new approach to generalised autoregressive conditional heteroscedasitic (GARCH) modelling for asset returns. Instead of attempting to choose a speciic distribution for the errors, as in the usual GARCH model formulation, we use a nonparametric distribution to estimate these errors. This takes into account the common problems encountered in nan-cial time series, for example, asymmetricity and excessive kurtosis, whilst maintaining the simple, and highly interpretable, GARCH model.
منابع مشابه
Analysing Financial Data Using Polya Trees
We present a new approach to generalised autoregressive conditional het-eroscedasitic (GARCH) modelling for asset returns. Instead of attempting to choose a speciic distribution for the errors, as in the usual GARCH model formulation, we use a nonparametric distribution to estimate these errors. This takes into account the common problems encountered in nancial time series, for example, asymmet...
متن کاملBudding yeast telomerase RNA transcription termination is dictated by the Nrd1/Nab3 non-coding RNA termination pathway
The RNA component of budding yeast telomerase (Tlc1) occurs in two forms, a non-polyadenylated form found in functional telomerase and a rare polyadenylated version with unknown function. Previous work suggested that the functional Tlc1 polyA- RNA is processed from the polyA+ form, but the mechanisms regulating its transcription termination and 3'-end formation remained unclear. Here we examine...
متن کاملBrain-specific polyA- transcripts are detected in polyA+ RNA: do complex polyA- brain RNAs really exist?
Transcripts encoded by 2 different rat genomic clones, rg13 and rg100, appear to be typical brain-specific polyA- RNAs, as defined by previous criteria (rare, polysomal, and postnatally expressed from single-copy genes). However, we have found by using a sensitive nuclease protection assay that low levels of these transcripts (10% and 3%, respectively) are detected in polyA+ RNA. To determine i...
متن کاملBayesian paradigm for analysing count data in longitudina studies using Poisson-generalized log-gamma model
In analyzing longitudinal data with counted responses, normal distribution is usually used for distribution of the random efffects. However, in some applications random effects may not be normally distributed. Misspecification of this distribution may cause reduction of efficiency of estimators. In this paper, a generalized log-gamma distribution is used for the random effects which includes th...
متن کاملDynamic Discrete Choice Models with Lagged Social Interactions: with an Application to a Signaling Game Experiment
This article generalizes Heckmans (1981) dynamic discrete choice panel data models by introducing lagged social interactions, so that the models can accommodate interrelationships of decisions across cross-sectional units. The likelihood function for a general model with dynamic social interactions is derived and simulation methods based on the unbiased GHK simulator are proposed to implement ...
متن کامل