Abstract This publication presents the results of the comparative analysis of economic growth in the United States and Poland using Harver Analytics. It takes into account factors such as GDP, industrial output, consumption expenditure, investment, exports and consumption expenditure of the government. The aim of the publication is presentation of differences between economic growth in Poland and USA.

Abstract This research, under Engle-Granger Co-integration framework, examines the hedging efficiency of Indian rubber future markets during the period 2004-2017. The essence of this study is to seek evidence for the effects of global financial crisis of 2008 on the efficiency of rubber futures in hedging  price risks of spot rubber in India. The study proved the hedging efficiency of rubber futures during both pre and post recession periods. However, increased price volatility of Indian rubber after recession heightened risk exposure to market participants that eventually lead to unexpected changes in the hedging efficiency of rubber futures.  The research concludes with a suggestion that writing of rubber futures in India allows traders to hedge risk exposures in spot market along with the potentials of arbitrage gains. 

Abstract Background: Breast cancer patients experience a variety of psychological symptoms such as anxiety, depression that affect their quality of life. The present study probed whether the socioeconomic status had any significance on psychological distress and quality of life of breast cancer patients in India. Method: This was a cross-sectional and observational study, conducted over 111 breast cancer patients in a tertiary cancer hospital, Kolkata. Subjects were eligible to participate and they were of over 23rd years of age and had a histologically confirmed diagnosis of breast cancer had no history of recurrence or metastasis, and had no previous psychological problems. Age, marital status, residence, education, occupation and family income were assesses for patients’ socio economic status. Psychological symptoms and quality of life were assessed by using validated tools. Means and standard deviations of each outcome were compared by socioeconomic status and multivariate linear regression models for evaluating the association between socioeconomic status, psychological distress and quality of life Results: The patient group was categorized into three groups based on their income level as follows: ≤500=27.9%), 500-1000=51.4% and high income = ≥1000=20.7%. A total of 111 breast cancer patients participated in the study; the mean age of participants was 49.7 (SE=1.31).After using multivariate logistic regression with fully adjusted models, the patients who were living alone had significantly higher level of depression and poor quality of life compared to those who are employed. Higher education and family income both positively associated with quality of life after adjusting for age, marital status and occupation. Conclusion: The findings revealed that the family income have a significant impact on the psychological distress of the cancer patients.  

Abstract This paper presents a bootstrap resampling scheme to build prediction intervals for future values in fractionally autoregressive moving average (ARFIMA) models. Standard techniques to calculate forecast intervals rely on the assumption of normality of the data and do not take into account the uncertainty associated with parameter estimation. Bootstrap procedures, as nonparametric methods, can overcome these diculties. In this paper, we test two bootstrap prediction intervals based on the nonparametric bootstrap in the residuals of the ARFIMA model. In this paper, two bootstrap prediction intervals are proposed based on the nonparametric bootstrap in the residuals of the ARFIMA model. The rst one is the well known percentile bootstrap, (Thombs and Schucany, 1990; Pascual et al ., 2004), never used for ARFIMA models to the knowledge of the authors. For the second approach, the intervals are calculated using the quantiles of the empirical distribution of the bootstrap prediction errors (Masarotto, 1990; Bisaglia e Grigoletto, 2001). The intervals are compared, through a Monte Carlo experiment, to the asymptotic interval, under Gaussian and non-Gaussian error distributions. The results show that the bootstrap intervals present coverage rates closer to the nominal level assumed, when compared to the asymptotic standard method. An application to real data of temperature in New York city is also presented to illustrate the procedures.

Abstract While there has been a significant amount of research covering the causes of merger waves, few papers have rank ordered merger waves based on the causes nor sought to determine which rationale leads to higher bidder payouts.  This paper seeks to fill this gap by examining a cross section of large mergers across most industries occurring over a 17 year period.  I find that merger waves over this period are caused foremost by changing economic and regulatory conditions.  It is the behavioral rationale of mispricing, however, that more often leads to higher bidder payouts or merger premiums among acquirers in merger waves.