30 December 2013

Peer reviewed paper published: A new generalisation of Sam-Solats multivariate hyperbolic secant distribution

December 30, 2013
Peer reviewed paper published: A new generalisation of Sam-Solats multivariate hyperbolic secant distribution

Download here full paper: Researchgate


Paper published in MATHEMATICAL SCIENCES RESEARCH JOURNAL ISSN 1537-5978


This paper proposed a new generalization of family of Sarmanov type Continuous multivariate symmetric probability distributions. More specifically the authors visualize a new generalization of Sam-Solai’s Multivariate Hyperbolic secant distribution from it’s univariate case. Further, we find its Cumulation, Marginal, Conditional distributions, Generating functions and also discussed its special case. The special cases include the transformation of Sam-solai’s Multivariate Hyperbolic secant distribution into Multivariate log- Hyperbolic secant. It is found that the conditional variance of Sam-Solai’s Multivariate conditional hyperbolic distribution is heteroskedastic and the correlation co-efficient among the random variables are similar to Pearson’s population product moment correlation. Finally,area values of the Bi-variate Hyperbolic secant distribution are extracted and bi-variate probability surfaces are also visualized. 

30 November 2013

Peer reviewed paper published: Modelling the Selection of Returns Distribution of G7 Countries

November 30, 2013
Peer reviewed paper published: Modelling the Selection of Returns Distribution of G7 Countries

Paper published in Research Journal of Management Sciences

Download here full paper: Researchgate


The purpose of the study is to identify the statistical distribution that is followed by the Indices returns of G7 countries.Canada is one of the members of the G7 countries but the data is insufficient and so it is not considered for the study. The closing values of indices were collected for selected countries from July 2003 to February 2013. The general assumption is that the stock returns are normally distributed. Using a statistical software 11 unbounded distributions was fitted for all the selected indices. The results show the returns follow different distributions that vary between countries.

30 October 2013

Peer reviewed paper published: Stress Symptoms : Structural Equation Modelling

October 30, 2013
Peer reviewed paper published: Stress Symptoms : Structural Equation Modelling

Download here full paper: Researchgate

Paper published in SCMS Journal of Indian Management ISSN: 0973-3167


The purpose of this study is to throw light on different types of stress factors, stress symptom and their impact of stress on college students from three different major disciplines namely Arts, Engineering and Management in Tiruchirapalli district, Tamil Nadu.Transition of students from school environment to College environment could cause a psychological, academic and social shock to them, since the educational system has huge differences: the student will face new methods of teaching, new academic requirements, new type of relations between students and faculties and even new relations among students themselves. Due to these changes, students can potentially experience different types of stress that can affect their mental health, social health and their academic achievements. Stress is one of the main aspects of our modern life, resulted from the rapid changes in human life, so this age is called the age of stress, students suffer from academic stress resulted from testing, home works and other college requirements which may exceed their abilities, sometimes the same person suffers from different types of stress at a same time.

30 September 2013

Peer reviewed paper published:Testing the Weak Form Efficiency of Indian Stock Market with Special Reference to NSE

September 30, 2013
Peer reviewed paper published:Testing the Weak Form Efficiency of Indian Stock Market with Special Reference to NSE

Download here full paper: Researchgate

Paper published in Advances In Management 

This study examines the random walk hypothesis to determine the validity of weak-form efficiency of the second major stock markets in India, NSE. The study uses daily observation over the span from 3rd July 2007 to 31st December 2011, comprising a total of 1116 observations. The random walk hypothesis is examined using auto correlation function, unit root tests (Augmented Dickey-Fuller test) and the runs test. The ADF and unit root tests clearly reveal that the null hypothesis of unit root is convincingly rejected in the case of stock market returns of indices, viz. S&P CNX NIFTY and the industry indexes. This suggests that the Indian stock markets do not show characteristics of random walk and as such are not efficient in the weak form implying that stock prices remain predictable.

The ACF and Unit root test do not show characteristics of random walk and as such are not efficient in the weak form for only some industries indexes such as the banking industry. This implies that the Indian stock markets are not weak form efficient signifying that there is systematic way to exploit trading opportunities and acquire excess profits. This provides an opportunity to the traders for predicting the future prices and earning abnormal profits on the banking industry. The implication of rejection of weak form efficiency for investors is that they can better predict the stock price movements by holding a well-diversified portfolio while investing in the Indian stock markets.

30 May 2013

Peer reviewed paper published: A New Generalisation of Sam-Solai’s Multivariate Additive Chi-Square Distribution

May 30, 2013
Peer reviewed paper published: A New Generalisation of Sam-Solai’s Multivariate Additive Chi-Square Distribution

Download here full paper: Researchgate

MATHEMATICAL SCIENCES RESEARCH JOURNAL ISSN 1537-5978

This paper proposed a new generalization of Sam-Solai's Multivariate additive chi-square distribution from the univariate case. Further, we find its Marginal, Multivariate Conditional distributions, Multivariate Generating functions, Multivariate survival, hazard functions and also discussed its special cases. The special cases includes the transformation of Sam-Solai's Multivariate additive chi-square distribution into Multivariate additive Chi-square distribution with n d.f,Multivariate Inverse chi-square distribution, Multivariate log chi-square distribution. Multivariate chi-distribution and Multivariate Extreme value chi-square distribution. Moreover, it is found that the bivariate correlation between two chi-square variables purely depends on the d.f and we simulated and established selected standard bivariate chi-square correlation bounds from 2500 different combination of d.f. The simulation results shows, the correlation between any two chi-square variables bounded from -1 to +1 for certain combination of fractional d.f.

02 March 2013

Peer reviewed paper published: A New Generalisation of Sam-Solai’s Multivariate Additive Gamma Distribution

March 02, 2013
Peer reviewed paper published: A New Generalisation of Sam-Solai’s Multivariate Additive Gamma Distribution

Download here full paper: Researchgate

MATHEMATICAL SCIENCES RESEARCH JOURNAL ISSN 1537-5978

This paper proposed a new generalization of bounded Continuous multivariate symmetric probability distributions. In this paper, we visualize a new generalization of Sam-Solai’s Multivariate additive Gammadistribution from the uni-variate two parameters Gamma distribution. Further, we find its Marginal, Multivariate Conditional distributions, Multivariate Generating functions, Multivariate survival, hazard functions and also discussed it’s special cases. The special cases includes the transformation of Sam-Solai’s Multivariate additive Gamma distribution into Multivariate Chi-square distribution, Multivariate Erlang distribution, Two parameter Multivariate Gamma distribution, Multivariate Inverse Gamma distribution, Multivariate log Gamma distribution and Multivariate Nagakami-m distribution. Moreover, it is found that the bivariate correlation between two Gamma random variables purely depends on the shape parameter and we simulated and established selected standard bivariate gamma correlation bounds from 900 different combinations of values for shape parameter.