Simarjeet Singh, Nidhi Walia, Stelios Bekiros, Arushi Gupta, Jigyasu Kumar and Amar Kumar Mishra
This research study aims to design a novel risk-managed time-series momentum approach. The present study also examines the time-series momentum effect in the Indian equity market…
Abstract
Purpose
This research study aims to design a novel risk-managed time-series momentum approach. The present study also examines the time-series momentum effect in the Indian equity market. Apart from this, the study also proposes a novel risk-managed time-series momentum approach.
Design/methodology/approach
The study considers the adjusted monthly closing prices of the stocks listed on the Bombay Stock Exchange from January 1996 to December 2020 to formulate long-short portfolios. Newey–West t statistics were used to test the significance of momentum returns. The present research has considered standard risk factors, i.e. market, size and value, to evaluate the risk-adjusted performance of time-series momentum portfolios.
Findings
The present research reports a substantial absolute momentum effect in the Indian equity market. However, absolute momentum strategies are exposed to occasional severe losses. The proposed time-series momentum approach not only yields 2.5 times higher return than the standard time-series momentum approach but also causes substantial enhancement in downside risks and higher-order moments.
Practical implications
The study's outcomes offer valuable insights for professional investors, capital market regulators and asset management companies.
Originality/value
This study is one of the pioneers attempting to test the time-series momentum effect in emerging economies. Besides, current research contributes to the escalating literature on risk-managed momentum by suggesting a novel revised time-series momentum approach.
Details
Keywords
Simarjeet Singh, Nidhi Walia, Sivagandhi Saravanan, Preeti Jain, Avtar Singh and Jinesh jain
This study aims to recognize the current dynamics, prolific contributors and salient trends and propose future research directions in the area of alternative momentum investing.
Abstract
Purpose
This study aims to recognize the current dynamics, prolific contributors and salient trends and propose future research directions in the area of alternative momentum investing.
Design/methodology/approach
The study uses a blend of electronic database and forward reference searching to ensure the incorporation of all the significant studies. With the help of the Scopus database, the present study retrieves 122 research papers published from 1999 to 2020.
Findings
The results reveal that alternative momentum investing is an emerging area in the field of momentum investing. However, this area has witnessed an exponential growth in last ten years. The study also finds that North American, West European and East Asian countries dominate in total research publications. Through network citation analysis, the study identifies five major clusters: industrial momentum, earnings momentum, 52-week high momentum, time-series momentum and risk-managed momentum.
Research limitations/implications
The present review will serve as a guide for financial researchers who intend to work on alternative momentum approaches. The study proposes several unexplored research themes in alternative momentum investing on which future studies can focus.
Originality/value
The study embellishes the existing literature on momentum investing by contributing the first bibliometric review on alternative momentum approaches.
Details
Keywords
Jinesh Jain, Nidhi Walia, Manpreet Kaur and Simarjeet Singh
The advocates of behavioural finance have denounced the existing literature on investors’ rationality in the decision-making process and questioned the existence of efficient…
Abstract
Purpose
The advocates of behavioural finance have denounced the existing literature on investors’ rationality in the decision-making process and questioned the existence of efficient markets and rational investors. Although diversified research has been conducted in the area of behavioural finance, yet there is a need of further explorations into the field as the available knowledge base is confined to one or a few behavioural biases confronted by investors while making investment decisions. Hence, this study aims to develop a comprehensive, reliable and valid scale to measure the behavioural biases affecting investors’ decision-making process.
Design/methodology/approach
To develop a comprehensive, reliable and valid scale for measuring the behavioural biases affecting investors’ decision-making process, rigorous multi-stage scale development methodology has been followed. Stage one started with an extensive review of the literature followed by interviews from experienced stockbrokers to clarify construct and getting novel insights about dimensions of behavioural biases. In stage two, 52 items measuring the dimensions of behavioural biases were generated and got evaluated from panel of judges. Pilot testing was done in the third stage which gave a set of 39 items. Finally, in fourth stage, data were collected from 332 individual equity investors on a 7-point Likert scale using the snowball sampling technique.
Findings
The results of the study highlighted that behavioural biases is a multidimensional phenomenon that significantly affects investors’ decisions and has different dimensions, namely, Availability Bias, Representativeness Bias, Overconfidence Bias, Market Factors, Herding, Anchoring, Mental Accounting, Regret Aversion, Gamblers’ Fallacy and Loss Aversion. The present research has developed a comprehensive, reliable and valid scale for measuring behavioural biases affecting equity investors’ decision-making process.
Originality/value
Behavioural finance is an emerging area in the field of research particularly in the Indian context which needs further exploration. The present research concentrates on rendering an empirically tested scale to the researchers for measuring the behavioural biases and its impact on investor’s decision-making. Such an instrument can contribute to making progress in the area of behavioural finance and other research studies may also find it useful to achieve their goals.
Details
Keywords
Jinesh Jain, Nidhi Walia and Sanjay Gupta
Research in the area of behavioral finance has demonstrated that investors exhibit irrational behavior while making investment decisions. Investor behavior usually deviates from…
Abstract
Purpose
Research in the area of behavioral finance has demonstrated that investors exhibit irrational behavior while making investment decisions. Investor behavior usually deviates from logic and reason, and consequently, investors exhibit various behavioral biases which impact their investment decisions. The purpose of this paper is to rank the behavioral biases influencing the investment decision making of individual equity investors from the state of Punjab, India. This research would provide valuable insight into the different behavioral biases to investors and other participants of the capital market and help them in improving investment decisions.
Design/methodology/approach
The research is conducted on the individual equity investors of Punjab, India. Fuzzy analytic hierarchy process was applied to rank the factors influencing the decision making of individual equity investors of Punjab. The primary factors considered for the study are overconfidence bias, representative bias, anchoring bias, availability bias, regret aversion bias, loss aversion bias, mental accounting bias and herding bias.
Findings
The three most influential criteria were herding bias, loss aversion bias and overconfidence bias. The five most influential sub-criteria were “I readily sell shares that have increased in value (C61),” “News about the company (Newspapers, TV and magazines) affects my investment decision (C84),” “I invest each element of my investment portfolio separately (C71)” and “I usually hold loosing stock for long time, expecting trend reversal (C52).”
Research limitations/implications
Although sample survey conducted in the present study was based on a limited sample selected from a particular area that truly represented the total population, it is considered as the limitation of this study.
Practical implications
The outcome of this research provides investors with a better understanding of behavioral biases that influence their decision making. This study provides them a guideline on different behavioral biases that they should consider while making investment decisions.
Originality/value
The research model is based on the available literature on behavioral finance and the research results and findings would add value to the existing knowledge base.
Details
Keywords
Anchal Arora, Sanjay Gupta, Chandrika Devi and Nidhi Walia
The financial technology (FinTech) era has brought a revolutionary change in the financial sector’s customer experiences at the national and global levels. The importance of…
Abstract
Purpose
The financial technology (FinTech) era has brought a revolutionary change in the financial sector’s customer experiences at the national and global levels. The importance of artificial intelligence (AI) in the context of FinTech services for enriching customer experiences has become a new norm in this modern era of technological advancement. So, it becomes crucial to understand the customer’s perspective. The current research ranks the factors and sub-factors influencing customers’ perceptions of AI-based FinTech services.
Design/methodology/approach
The sample size for this study was decided to be 970 respondents from four Indian cities: Mumbai, Delhi, Kolkata and Chennai. The Fuzzy-AHP technique was used to identify the primary factors and sub-factors influencing customers’ experiences with AI-enabled finance services. The factors considered in the study were service quality, trust commitment, personalization, perceived convenience, relationship commitment, perceived sacrifice, subjective norms, perceived usefulness, attitude and vulnerability. The current research is both empirical and descriptive.
Findings
The study’s three top factors are service quality, perceived usefulness and perceived convenience, all of which have a significant impact on customers’ experience with AI-enabled FinTech services discussing sub-criteria three primary criteria for customers’ experience for FinTech services include: “Using FinTech would increase my effectiveness in managing a portfolio (A2)”, “My peer groups and friends have an impact on using FinTech services (SN3)” and “Using FinTech would increase my efficacy in administering portfolio (PU2)”.
Research limitations/implications
The current study is limited to four Indian cities, with 10 factors to understand customers’ preferences in FinTech. Further research can focus on other dimensions like perceived ease of use, familiarity, etc. Future studies can have a broader view of different geographical locations and consider new tech to understand customer perceptions better.
Practical implications
The study’s findings will significantly assist businesses in determining the primary aspects influencing customers’ experiences with AI-enabled financial services. As a result, they will develop strategies and policies to entice clients to use AI-powered FinTech services.
Originality/value
Existing AI research investigated several vital topics in the context of FinTech services. On the other hand, the current study ranked the criteria in understanding customer experiences. The research will substantially assist marketers, business houses, academicians and practitioners in understanding essential facets influencing customer experience and contribute significantly to the literature.
Details
Keywords
Sanjay Gupta, Nidhi Walia, Simarjeet Singh and Swati Gupta
This comprehensive study aims to take a punctilious approach intended to present qualitative and quantitative knowledge on the emerging concept of noise trading and identify the…
Abstract
Purpose
This comprehensive study aims to take a punctilious approach intended to present qualitative and quantitative knowledge on the emerging concept of noise trading and identify the emerging themes associated with noise trading.
Design/methodology/approach
This study combines bibliometric and content analysis to review 350 publications from top-ranked journals published from 1986 to 2020.
Findings
The bibliometric and content analysis identified three major themes: the impact of noise traders on the functioning of the stock market, traits of noise traders and different proxies used to measure the impact of noise trading.
Research limitations/implications
This study undertakes research papers related to the field of finance, published in peer-reviewed journals and that too in the English language.
Practical implications
This study shall accommodate rational traders, portfolio consultants and other investors to gain deeper insights into the functioning of noise traders. This will further help them to formulate their trading/investment strategies accordingly.
Originality/value
The successful combination of the bibliometric and content analysis revealed major gaps in the literature and provided future research directions.
Details
Keywords
Pooja Goel, Simarjeet Singh and Nidhi Walia
Purpose: The purpose of the present study is to synthesize and organize existing literature on contagious diseases and tourism. This systematic mapping of the literature helps to…
Abstract
Purpose: The purpose of the present study is to synthesize and organize existing literature on contagious diseases and tourism. This systematic mapping of the literature helps to identify various mature and emerging themes around the research domain in the literature.
Design/Methodology/Approach: The study uses systematic methodology along with bibliometric and content analysis. Using a combination of electronic database searching and forward and backward references searching, the study identifies 160 suitable published studies.
Findings: Initial bibliometric analysis reveals that Tourism Geographies and Tourism Management are most influential journals and Law and Lee are most influential authors working on this field. The Hong Kong Polytechnic University and Universiti Sains Malaysia are among the top contributing educational and research organizations. Further, the content analysis reveals that literature on contagious diseases and tourism industry revolves around three prominent themes namely SARS and other contagious diseases, crisis management and tourism forecasting.
Research Limitations/Implications: The study does not consider ‘grey literature’ and conference proceedings.
Originality and Value: Present study is one of the early attempts that analyzes the literature on contagious diseases and tourism using bibliometric analysis and contributes to the literature by identifying various mature and emerging on contagious diseases and tourism literature. These insights provide a robust map for future investigation in this field and also offer implications for practitioners.
Details
Keywords
Gagandeep Singh, Jasdeep Singh Walia and Avtar Singh
The businesses at the global level are surfacing precipitously, and its ecosystem is illustrated by the factors of volatility, uncertainty, complexity and ambiguity. The rapidly…
Abstract
The businesses at the global level are surfacing precipitously, and its ecosystem is illustrated by the factors of volatility, uncertainty, complexity and ambiguity. The rapidly changing business landscape calls for incorporating virtual exertion and the adoption of various digital tools. The process of virtual onboarding which has gained prominence at the global level at the onset of the pandemic necessitates encompassing recruits using virtual podiums and remote processes. The current chapter insinuates a holistic model for a suitable virtual onboarding programme, delineating a comprehensive methodology that incorporates a range of onboarding process elements and syndicates business best exercises from several theoretical backgrounds. It intends to offer a robust framework that suitably guides business organisations in developing and implementing effective virtual onboarding programmes. The Virtual Onboarding Model outlined in the present study elucidates the five integral phases, each serving a specific purpose and strategically integrating them from the outcomes derived from various theoretical underpinnings. The outcomes of this chapter provide detailed assistance for businesses operating in the volatility, uncertainty, complexity and ambiguity (VUCA) world to establish comprehensive remote onboarding programmes. It aims to endow human resource (HR) managers with the indispensable intuitions to create and execute virtual onboarding programmes that support successful learning, cultural integration and employee engagement, ultimately benefiting both the recruits and the businesses in contemporary HR practices.