The study provides evidence in favor of the price range as a proxy estimator of volatility in financial time series, in the cases that either intra-day datasets are unavailable or they are available at a low sampling frequency.

Various forms of instability can be observed in macroeconomic and financial data including changes in variance, changes in cycle properties, or both. Traditional tests do not allow to distinguish between these different cases. This paper proposes and compares two alternative approaches. The...

In this paper, we assess the size and power properties of Inclan and Tiao's (1994) Iterated Cumulative Sum of Squares (IT ICSS) algorithm for detecting sudden changes in volatility. We make use of the variance estimator that utilizes high, low and closing prices proposed by Rogers and Satchell...

Intraday data of 26 German stocks are used to investigate whether the information contained in trading volume and number of trades as well as in various specifications of overnight returns can improve one-step-ahead volatility forecasts. For this purpose, a HAR model of the realized range...

Owing to the vague fluctuation of energy prices from time to time, a new energy model, which considers both the mean-reverting behavior and the long memory property, is proposed in this paper. Since the problem of estimating parameters, in discrete time for this model, plays a central role in...

I consider a bivariate stationary fractional cointegration system and I propose a quasi-maximum likelihood estimator based on the Whittle analysis of the joint spectral density of the regressor and errors. This allows to estimate jointly all parameters of interest of the model. I lead a Monte...

In this paper we discuss the calibration issues of power models built on mean-reverting processes combined with long memory. The unknown parameters of fractional mean-reversion processes are estimated by a hybrid estimation method, which is built upon the marriage of the quadratic variation and...

Standard VAR and Bayesian VAR models are proven to be reliable tools for modeling and forecasting, yet they are still linear and they do not consider time-variation in parameters. VAR modeling is subject to the Lucas critique and fails to take into account the inherent nonlinearities of the...

We propose to produce accurate point and interval forecasts of exchange rates by combining a number of well known fundamental based panel models. Combination of each model utilizes a set of weights computed using a linear mixture of experts's framework, where weights are determined by log scores...

The paper examines Granger-causality between the producers' and the consumers' price using Australian data within the frequency domain framework. For long run relation, the Johansen and Juselius (1990) maximum likelihood approach to cointegration was utilized. The test is also supplemented by...