Past Issue : Volume-10 (2019-2020)


The Role of Precision Timing in Stock Market Price Discovery when Trading through Distributed Ledgers

This paper investigates the importance of “time of execution” and the relevance of “precision time” in order driven transactions done over distributed ledgers. We created a distributed marketplace using stock market price data from the Toronto Stock Exchange (TMX). We then proceeded to test and measure the impact of timing of orders at the nanosecond level. Whilst price discovery in order driven markets is done instantaneously, with distributed markets, it is necessary to know which order to process first to avoid “front- running”. We argue that a protocol for the time of order of receipt and execution should be subject to nanosecond stacking. Our approach incorporates both transitory and permanent price discovery components. It allows for the efficient processing of transactions and the order that are received by a market clearing distributed ledger.
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Daniel Broby, Devraj Basu and Ashwin Arulselvan

Information Content in International Equity Volatility on Yuan's Depreciation

We investigate whether depreciation of USD-CNY exchange rate causes direct or indirect effects on conditional variances in the international equity markets, especially of Japanese, ASEAN, Australian, and Indian markets. Employing APARCH and using MSCI indices we find a significant positive impact of Yuan’s depreciation on the conditional variances of Japanese, ASEAN and Australian equity markets. When USD-CNY exchange rate depreciates by 0.25 percent or more, volatility in the Chinese equity market causes a significant positive impact on the conditional volatility in the Japanese and Australian equity markets, though with some lag. USD-CNY exchange rate movements strongly influence the ASEAN equity markets across all time frames. The findings may enable investors to manage their portfolios of equity markets under consideration in the presence or absence of USD-CNY movements.
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Amanjot Singh and Harminder Singh

Structural Equation Modelling: A Powerful Antibiotic

This article is an attempt to scrutinize the applicability of the widely used statistical technique of Structural Equation Modelling (SEM). SEM is a comprehensive technique to test the model adequacy. SEM is considered as an important advancement in social science research as it combines measurement with substantive theories. It has been observed that many studies pay attention to statistical mechanisation of SEM rather than the assumptions on which it is based. The history of SEM can be traced to Regression Analysis, Path Analysis and Confirmatory Factor Analysis. SEM is popularly applied because of its use in estimating multiple dependence relationships. It is able to measure the unobserved variables, define the model representing the set of relationships and also corrects the measurement error. The technique is commonly applied in disciplines including sociology, psychology and other fields of behavioural science. The availability of various user-friendly software programmes like LISREL, AMOS, EQS, Mx, Mplus and PISTE is an added advantage. However, one should be careful while using SEM for causal inferences. In comparison to other common standard statistical techniques, SEM is based on several assumptions. The technique requires a priori knowledge of all the parameters to be estimated and a substantial amount of data pertaining to covariances, variances and path coefficients. It also requires relationships to be specified in the model. The model inherently assumes temporal precedence and is heavily dependent on researcher’s judgements about exogeneity and directionality. Normality is yet another important assumption of SEM. The mismatch between data characteristics and assumptions imperils inference and accuracy. Like antibiotics are a boon to mankind yet one needs to judiciously use them. Similarly, SEM is a powerful technique however, researchers are suggested to apply cautiously.
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H. K. Dangi, Ashmeet Kaur and Juhi Jham

Female Labour Force Participation in India: Understanding the Nature and Constraints

Rising education of women and falling fertility has not translated into greater participation of women in the labour force. Understanding the nature of and factors affecting women’s employment is pivotal to direct policy initiatives in addressing the issue. Using a nationally representative dataset, this study analyses various factors affecting women’s employment with specific focus on the presence of young children in the household. The paper also studies the nature of employment as a ‘work away from home’ and ‘full-year or not’ and effect of various factors on the same. The study finds that apart from other factors, presence of very young children in the household acts a major constraint to a woman’s participation in the labour market, ie., decreasing their likelihood to work. Moreover, even if a woman participates, presence of young children may affect the nature of work that she engages in. Whereas we find no effect of child-care responsibilities on the place of work of women, there is significant negative effect on women’s nature of work being full-year if there are young kids in the household.
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Divya Gupta

Role of Medical Representatives in Influencing Medicine Prescription Behaviour of Doctors

Medicine Prescription Behaviour (MPB) is a doctor’s decision for a specific drug/medicine of a pharmaceutical company. Doctors consider several factors in their evaluation process while selecting a particular drug. The transfer of information to doctors, especially through detailing by Medical Representatives (MRs), is a crucial element of pharmaceutical marketing. New drugs are introduced in the market very frequently because of rapid change in preferences and prescription patterns of doctors. Therefore, understanding shift in doctors’ desires regarding selection of a particular drug give opportunities to proactive pharmaceutical companies to increase their market share by timely anticipating doctors' preferences. This paper seeks to identify the influence of level of knowledge, kind of information, communication skills and frequent visit of MRs on three aspects of MPB; early prescription of new drugs, cost of drugs and habitual aspect. Testable hypotheses were developed with respect to MPB and a survey questionnaire was designed to capture data from 150 doctors practicing in Delhi. The hypotheses were tested using Multiple Regression and Analysis of Variance (ANOVA). The study concluded that the knowledge, kind of information, communication skills and professionalism factor of MRs influence doctors towards early prescription of new drugs and their habitual behaviour towards prescription of drugs. The study concluded that knowledge and the kind of information given by MRs are significant predictors of cost aspect of MPB of doctors.
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Kiran Bala and Kavita Sharma

Analysis of Indian Consumers’ Behaviour using Lifestyle Segmentation

Demographic profiling has been an important basis of segmenting consumers. But the demographic variables provide a compartmentalised view of consumer behaviour. Purchase and consumption behaviour are in fact the result of influence of many variables operating simultaneously in the background. In order, to provide a holistic view of the ‘why and how’ of consumers purchase decision, lifestyle analysis has been considered a superior basis of customer profiling in recent research. Lifestyle study focuses on activities, interests and opinions of consumers and their role in formulating consumers’ purchase decision. Past researches in India do provide an insight into the segmentation of Indian consumers on demographic and geographic basis. However, not much has been emphasised on the use of lifestyle for segmenting Indian consumers. The present research, therefore, tries to fill this void by providing the lifestyle profiling of the Indian consumers using factor analysis and cluster analysis. This study can help the marketers in segmenting their prospective and present customers using the suggested lifestyle dimensions.
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Reetika Jain