ARCH model

Most high-frequency asset returns exhibit seasonal volatility patterns. This article proposes a new class of models featuring periodicity in conditional heteroscedasticity explicitly designed to capture the repetitive seasonal time variation in the second-order moments. ...

The ARCH type of models is a notorious family of models proven to be suitable for predicting financial returns. Their notoriety flourished after Bollerslev (1986) developed the econometric Generalized ARCH model (GARCH). This paper provides a presentation of the main characteristics of the modeling of financial returns with the objective to calibrate an EGARCH (Exponential GARCH) model for the logarithmic

We consider a model $Y\_t=\sigma\_t\eta\_t$ in which $(\sigma\_t)$ is not independent of the noise process $(\eta\_t)$, but $\sigma\_t$ is independent of $\eta\_t$ for each $t$. We assume that $(\sigma\_t)$ is stationary and we propose an adaptive estimator of the density of $\ln(\sigma^2\_t)$ based on the observations $Y\_t$. Under various dependence structures, the rates of this nonparametric estimator coincide with the

This paper presents the R package AdMit which provides task of tuning a sam- pling algorithm. The relevance of the package is shown in two examples. The rst aims at illustrating in detail the use of the functions provided by the package in a bivariate bimodal distribution. The second shows the relevance of the adaptive mixture procedure through the Bayesian

Although volatility clustering has a long history as a salient empirical regularity characterizing high-frequency speculative prices, it was not until recently that applied researchers in finance have recognized the importance of explicitly modeling time-varying second-order moments. Instrumental in most of these empirical studies has been the Autoregressive Conditional Heteroskedasticity (ARCH) model introduced by Engle (1982). This paper contains an overview of some of the developments in the formulation of ARCH models and a survey of the numerous empirical applications using financial data. Several suggestions for future research, including the implementation and tests of competing asset pricing theories, market microstructure models, information transmission mechanisms, dynamic hedging strategies, and the pricing of derivative assets, are also discussed.

The uctuation of a bilateral exchange rate in a target zone is often chosen as part of oÆcial agreements between two or more countries (such as in the European Monetary System { EMS) or of informal unilateral monetary policy packages a country adopts for itself. The defendability of such a regime in the face of asymmetric shocks is always an issue. In this paper, we examine a long period in the life of the EMS and we argue that the increase in volatility in the interest rates could help identifying periods of possible impending crisis for the exchange rates. Our framework provides a way to put to test the quality of the reaction by monetary authorities and to relate perceived weakness to subsequent episodes of realignment in the central parity. We examine ten years of Italian Lira one month Eurodeposit daily between 1983 and 1993 addressing three empirical questions: 1. Is interest rate volatility a measure of the perceived degree of vulnerability of the institutional agreements and...

As it is possible to model both linear and nonlinear structures in time series by using Artificial Neural Network (ANN), it is suitable to apply this method to the chaotic series having nonlinear component. Therefore, in this study, we propose to employ ANN method for high volatility ...