Articles | Author |
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. |
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. |
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. |
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. |
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. |
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. |
Reetika Jain |