We provide a signal modality analysis to characterize and detect nonlinearity schemes in the US Industrial Production Index time series. The analysis is achieved by using the recently proposed "delay vector variance" (DVV) method, which examines local predictability of a signal in the phase...

A novel procedure to test for unit root in a nonlinear framework is proposed by first introducing a new model – the MT-STAR model – which has similar properties as the ESTAR model but reduces the effects of the identification problem and can also account for cases where the adjustment...

We propose a transparent way of establishing a turning point chronology for the Euro-zone business cycle. Our analysis is achieved by exploiting the concept of recurrence plots, in particular distance plots, to characterize and detect turning points of the business cycle. Firstly, we apply the...

We provide a signal modality analysis to characterize and detect nonlinearity schemes in the US Industrial Production Index time series. The analysis is achieved by using the recently proposed ‘delay vector variance’ (DVV) method, which examines local predictability of a signal in the phase...

With the emergence of the chaos theory and the method of surrogates data, nonlinear approaches employed in analysing time series typically suffer from high computational complexity and lack of straightforward explanation. Therefore, the need for methods capable of characterizing time series in...

Identification of financial bubbles and crisis is a topic of major concern since it is important to prevent collapses that can severely impact nations and economies. Our analysis deals with the use of the recently proposed "delay vector variance" (DVV) method, which examines local predictability...

In ESTAR models it is usually quite difficult to obtain parameter estimates, as it is discussed in the literature. The problem of properly distinguishing the transition function in relation to extreme parameter combinations often leads to getting strongly biased estimators. This paper proposes a...

In this paper, we aim at assessing Markov-switching and threshold models in their ability to identify turning points of economic cycles. By using vintage data that are updated on a monthly basis, we compare their ability to detect ex-post the occurrence of turning points of the classical...

Sharpe-like ratios have been traditionally used to measure the performances of portfolio managers. However, they are known to suffer major drawbacks. Among them, two are intricate : (1) they are relative to a peer's performance and (2) the best score is generally assumed to correspond to a...

The aim of this paper is to study the cross-sectional effects present in the market using a new framework based on graph theory. Within this framework, we represent the evolution of a dynamic portfolio, i.e. a portfolio whose weights vary over time, as a rank-based factorial model where the...