From Digital Overload to Trading Zen

Author:

Bhatnagar Mukul1,Kumar Pawan1ORCID,Taneja Sanjay2ORCID,Sood Kiran3ORCID,Grima Simon4ORCID

Affiliation:

1. Chandigarh University, India

2. Graphic Era University, India

3. Chitkara Business School, Chitkara University, India & Research Fellow at the Women Researchers Council (WRC), Azerbaijan State University of Economics (UNEC), Azerbaijan

4. Department of Insurance, Faculty of Economics Management and Accountancy, University of Malta, Msida, Malta & Faculty of Business, Management and Economics, University of Latvia, Riga, Latvia

Abstract

Because of the urgency and high stakes involved in their trades, intraday traders are especially vulnerable to the perils of information overload in today's digital world. This chapter explores the potential benefits of digital detox programmes for intraday traders. The research uses the statistical programme SMart PLS to do a route analysis using primary data gathered via questionnaire. The results show that taking a break from technology may dramatically lower stress levels, which in turn boosts business efficiency. This correlation is moderated by traders' levels of expertise, however, indicating that newcomers to the market might gain the most from digital detox programmes. The last section of the study emphasises the chapter's central thesis, arguing for the inclusion of digital detox measures in training programmes and workplace rules in order to address the chapter's identified practical ramifications for traders, trading businesses, and regulatory agencies.

Publisher

IGI Global

Reference87 articles.

1. Interventions to reduce stress and prevent burnout in healthcare professionals supported by digital applications: a scoping review

2. World Trading System under Stress: Scenarios for the Future

3. MobileDNA: Relating Physiological Stress Measurements to Smartphone Usage to Assess the Effect of a Digital Detox

4. Multiple STL decomposition in discovering a multi-seasonality of intraday trading volume

5. Azzini, A., Dragoni, M., & Tettamanzi, A. G. B. (2013). Short-term market forecasting for intraday trading with neuro-evolutionary modeling. In Recent Advances in Computational Finance. Nova Science Publishers, Inc. https://www.scopus.com/inward/record.uri?eid=2-s2.0-84896237644&partnerID=40&md5=4e585a82d4e81a029451948ea0e6545f

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