Expected shortfall (ES) is a popular risk measure and plays an important role in risk and portfolio management. Recently, change-point detection of risk measures has been attracting much attention in finance. Based on the self-normalized CUSUM statistic in Fan, Glynn and Pelger (2018) and the...

We present in this paper an alternative approach to determining and predicting the fluctuations in the daily prices and stock returns of a first-generation bank in the Nigerian Stock Market (NSM). The approach uses a three-state Markov to estimate the expected duration of the asset returns in...

We provide empirical evidence of volatility forecasting in relation to asymmetries present in the dynamics of both return and volatility processes. Using recently-developed methodologies to detect jumps from high frequency price data, we estimate the size of positive and negative jumps and...

The objective of this research is to introduce in literature new measures of accuracy for point forecasts (radical of order n of the mean of squared errors, mean for the difference between each predicted value and the mean of the effective values, ratio of radicals of sum of squared errors...

The proper forecasting of listed companies' earnings is crucial for their appropriate pricing. This paper compares forecast errors of different univariate time-series models applied for the earnings per share (EPS) data for Polish companies from the period between the last financial crisis of...

To capture location shifts in the context of model selection, we propose selecting significant step indicators from a saturating set added to the union of all of the candidate variables. The null retention frequency and approximate non-centrality of a selection test are derived using a...

This paper shows how to decompose weakly stationary time series into the sum, across time scales, of uncorrelated components associated with different degrees of persistence. In particular, we provide an Extended Wold Decomposition based on an isometric scaling operator that makes averages of...

In this study, a vector autoregression (VAR) model with time-varying parameters (TVP) to predict the daily Indian rupee (INR)/US dollar (USD) exchange rates for the Indian economy is developed. The method is based on characterization of the TVP as an optimal control problem. The methodology is a...

In this study, we treat the seasonal variation in monthly time series in the context of the Western-European tourism demand for Tunisia, by presenting different techniques of detection of seasonality and the parametric and non-parametric approaches of seasonal adjustment. Then, we compare the...