We present an efficient technique for the study of quasi-periodic oscillations in noisy, non-stationary signals, which allows the assessment of system dynamics despite phase resetting and noise. It is based on the definition of anchor points in the signal (in the simplest case increases or...

There are over 3 billion searches globally on Google every day. This report examines whether Google search queries can be used to predict the present and the near future unemployment rate in Finland. Predicting the present and the near future is of interest, as the official records of the state...

In this study we examine the time-dependent nature of volatility and cross-correlation of Australian equity returns data. Volatility and correlation estimates are calculated using methods that allow for non-stationary behaviour. By averaging the estimates across the entire data set we show that...

This paper examines the magnitude of error associated with linear approximations of nonlinear variables based on Taylor's Series. Little attention has been given to the error term in previous empirical studies. This paper presents the mathematical technique for the single-variable and...

One of the major problems of contemporary Poland is its increasingly difficult and complicated demographic situation. This makes the identification of demographic trends of the recent years an important research task. The article presents an assessment of Poland's demographic situation after...

We use a dynamic multipath general-to-specific algorithm to capture structural instability in the link between euro area sovereign bond yield spreads against Germany and their underlying determinants over the period January 1999 – August 2011. We offer new evidence suggesting a significant...

Financial markets witness high levels of activity at certain times but remain calm at others. This makes the flow of physical time discontinuous. Therefore, to use physical time scales for studying financial time series runs the risk of missing important activities. An alternative approach is to...

In practice, complex systems often change over time, and the temporal characteristics of a complex network make their behavior difficult to predict. Traditional link prediction methods based on structural similarity are good for mining underlying information from static networks, but do not...

This paper analyses the pure time-series properties of doctors’ fees in Ireland to assess whether a structural change in the series is observed at the time of the change in reimbursement in 1989. Such a break would be consistent with doctors responding to the reimbursement change in a manner...

The use of price promotions to stimulate brand and firm performance is increasing. We discuss how (i) the availability of longer scanner data time series, and (ii) persistence modeling, have lead to greater insights into the dynamic effects of price promotions, as one can now quantify their...