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Available. Open Access. Open Access
Article
Publication date: 31 October 2024

Michael O'Neill and Gulasekaran Rajaguru

The authors analyse the nature of nonlinear long-run causal dynamics between VIX futures and exchange-traded products (ETPs).

102

Abstract

Purpose

The authors analyse the nature of nonlinear long-run causal dynamics between VIX futures and exchange-traded products (ETPs).

Design/methodology/approach

Nonlinear long-run causal relations between daily price movements in ETPs and futures are established through a Markov switching vector error correction model (MS-VECM).

Findings

The authors observe time variation in causality with the volatility of volatility. In particular, demand pressures for VIX ETNs and futures can change in different regimes. The authors observe two regimes where regime 1 is classified as low-mean low-volatility, while regime 2 is classified as high-mean high-volatility. The convergence to the long-run equilibrium in the low-mean low-volatility regime is faster than the high-mean high-volatility regime. The nature of the time varying lead lag relations demonstrates the opportunities for arbitrage.

Originality/value

The linear causal relations between VXX and VIX futures are well established, with leads and lags generally found to be short-lived with arbitrage relations holding. The authors go further to capture the time-varying causal relationships through a Markovian process. The authors establish the nonlinear causal relations between inverse and leveraged products where causal relations are not yet documented.

Details

Journal of Accounting Literature, vol. 47 no. 5
Type: Research Article
ISSN: 0737-4607

Keywords

Available. Open Access. Open Access
Article
Publication date: 9 January 2025

Gulasekaran Rajaguru, Sheryl Lim and Michael O'Neill

This review investigates the effects of temporal aggregation and systematic sampling on time-series analysis, focusing on their influence on data accuracy, interpretability and…

118

Abstract

Purpose

This review investigates the effects of temporal aggregation and systematic sampling on time-series analysis, focusing on their influence on data accuracy, interpretability and statistical properties. The purpose of the study is to synthesise existing literature on the topic and offer insights into the trade-offs between these data reduction techniques.

Design/methodology/approach

The research methodology is based on an extensive review of theoretical and empirical studies covering univariate and multivariate time series models, focusing on unit roots, ARIMA, GARCH, cointegration properties and Granger Causality.

Findings

The key findings reveal that while temporal aggregation simplifies data by emphasising long-term trends, it can obscure short-term fluctuations, potentially leading to biases in analysis. Similarly, systematic sampling enhances computational efficiency but risks information loss, especially in non-stationary data, and may result in biased samples if sampling intervals coincide with data periodicity. The review highlights the complexities and trade-offs involved in applying these methods, particularly in fields like economic forecasting, climate modelling and financial analysis.

Originality/value

The originality and value of this study lie in its comprehensive synthesis of the impacts of these techniques across various time series properties. It underscores the importance of context-specific applications to preserve data integrity, offering recommendations for best practices in the use of temporal aggregation and systematic sampling in time-series analysis.

Details

Journal of Accounting Literature, vol. 47 no. 5
Type: Research Article
ISSN: 0737-4607

Keywords

Available. Content available
Book part
Publication date: 11 March 2025

Eva Tutchell and John Edmonds

Abstract

Details

The Stalled Revolution: Is Equality for Women an Impossible Dream?
Type: Book
ISBN: 978-1-83549-193-5

Available. Open Access. Open Access
Article
Publication date: 13 February 2024

Amer Jazairy, Emil Persson, Mazen Brho, Robin von Haartman and Per Hilletofth

This study presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into…

4898

Abstract

Purpose

This study presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into the logistics management field.

Design/methodology/approach

Rooting their analytical categories in the LMD literature, the authors performed a deductive, theory refinement SLR on 307 interdisciplinary journal articles published during 2015–2022 to integrate this emergent phenomenon into the field.

Findings

The authors derived the potentials, challenges and solutions of drone deliveries in relation to 12 LMD criteria dispersed across four stakeholder groups: senders, receivers, regulators and societies. Relationships between these criteria were also identified.

Research limitations/implications

This review contributes to logistics management by offering a current, nuanced and multifaceted discussion of drones' potential to improve the LMD process together with the challenges and solutions involved.

Practical implications

The authors provide logistics managers with a holistic roadmap to help them make informed decisions about adopting drones in their delivery systems. Regulators and society members also gain insights into the prospects, requirements and repercussions of drone deliveries.

Originality/value

This is one of the first SLRs on drone applications in LMD from a logistics management perspective.

Details

The International Journal of Logistics Management, vol. 36 no. 7
Type: Research Article
ISSN: 0957-4093

Keywords

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