In this study, we conduct a comparative analysis of the nonlinear dynamics of time series data for green and conventional bond indices spanning the period from 2014 to 2023. Our research builds upon the existing limited studies conducted in this domain. To examine the inherent characteristics of...

This study endeavors to unravel the structured and sequential intricacies underlying the empirical da-ta-generating process (DGP) and the captivating evolutionary dynamism of Islamic fixed income securi-ties. To achieve this goal, we delve into the realm of nonlinear dynamics governing the Dow...

The wavelet transform is used to identify a biannual and an annual seasonality in the Phelix Day Peak and to separate the long-term trend from its short-term motion. The short-term/long-term model for commodity prices of Schwartz & Smith (2000) is applied but generalised to account for weekly...

This study provides an overview of the model evolution and research trends in the field of financial and risk modelling by applying a bibliometric approach from 2008–2019 and an overall citation network analysis. We present a content analysis of contributing authors, countries, journals, main...

In this study, we present a combinatory chaos analysis of daily wavelet-filtered (denoised) S&P 500 returns (2000–2020) compared with respective surrogate datasets, Brownian motion returns and a Lorenz system realisation. We show that the dynamics of the S&P 500 return series consist of an...

In discussions and critiques on the validity of the Efficient Market Hypothesis, there are two important research focuses: statistical analyses showing that the basic assumption of statistical independence in price series is violated and empirical findings that show that significant market...

Paper Length: 24 PagesSuplementary Material: 88 Pages (mostly graphics)This paper applies rolling windows to generate time-varying data series of selected chaos measures (i.e. Hurst exponent, maximum Lyapunov exponent, Lyapunov sum and sample entropy). The generated series are analysed to...

In this study, we apply a rolling window approach to wavelet-filtered (denoised) S&P500 returns (2000–2020) to obtain time varying Hurst exponents. We analyse the dynamics of the Hurst exponents by applying statistical tests (e.g., for stationarity, Gaussianity and self-similarity), a...