ڈاکٹر عبدالبصیرخان
قاہرہ سے واپسی پردوسری اندوہناک خبر اپنے عزیز دوست ڈاکٹر عبدالبصیر خان کی وفات حسرت آیات کی سُنی جوپہلی خبرسے کم دلدوز نہیں تھی۔ موصوف اپنے مضمون (ZOOLOGY) میں بین الاقوامی شہرت کے مالک تھے۔ مسلم یونیورسٹی علی گڑھ میں اپنے شعبہ کے صدر اور پروفیسر تھے،پراکٹر بھی رہ چکے تھے۔ طبعاً نہایت شریف ،سچّے اور خدا ترس انسان تھے۔ مرنا ہرایک کوہے لیکن اُن کی وفات جن حالات میں ہوئی ہے وہ حددرجہ صبرآزماتھے،اس لیے ہمیں اس میں ذرا شبہ نہیں کہ اُن کی موت صرف موت نہیں بلکہ شہادت ہے۔ اﷲ تعالیٰ انھیں صدیقین وشہداء کامقامِ جلیل عطا فرمائے اور ان کی نوجوان بیوہ اور دو کمسن بچّوں کاحافظ وناصر اور نگہبان ہو،آمین۔ [نومبر ۱۹۶۶ء]
Multiparity is a matter of great concern regarding the health of women as well as child. At the same time it has different determinants and socioeconomic backgrounds. Objective: To determine the determinants of lack of family planning in grand multiparous women. Methods: It is a descriptive cross sectional study including 271 GMP patients from DHQ Hospital Okara city. Mean age was 35 ± 10 years. Data was collected with the help of questionnaire and evaluated and analyzed using SPSS version 24. Mean and standard deviation was calculated for quantitative data and frequency and percentages for qualitative data. To measure the determinants of lack of family planning, chi square test was used. P values less than and equal to 0.05 were taken as significant. Results: Most of women belong to rural area 172(63.47%) and areMuslims 259(95.5%). Most of the families lie under upper lower 149 (54.8%) and lower middle group of income 71(26.1%). The reason of last pregnancy was desire for baby boy 66(24.4%), then husband’s wish 45(16.6%)and so on. There is a good association of socioeconomic status and residence of head of family as p < 0.05, (Results are 325.272a, df = 10, p=0.000). There is an association of Gravida and socioeconomic status of head of family as p<0.05. (27.294, df= 20, p=.05). There is a good association between reasons of last pregnancy and gravida as p<0.05, (41.920, df = 24, p=0.001). Conclusions: The grand multiparty is still very common in Okara Pakistan district, considering the easy availability of modern contraceptive methods but very few women are aware of it. The most popular explanation given for present pregnancy by grand multiparous women was an urge for baby boy followed by husband wish. Most of women are Muslims. Rural Women are more socio-economically down and they have grandermultiparty.
The main focus of the present study is to investigate the model that is most superior to estimate, forecast and analyze and further examine the spillover effects of portfolio returns volatility of the stocks traded in Karachi Stock Exchange (KSE) of Pakistan for the time period of July 1998 to June 2011on daily basis. From 100 stocks, 10 portfolio returns (10 stocks each) are constructed sorted on high/low betas to estimate portfolio volatility. Due to autoregressiveness and heteroskedasticity characteristic of stock returns ARCH models are used to estimate the volatilities of portfolio returns. For analysis one symmetric GARCH-M model and three asymmetric TGARCH-M, EGARCH-M and PGARCH-M are used where conditional mean equation follows ARMA specification. The GARCH-M Models are employed because they allow to estimate the reward for facing the volatility risk by the investor. Based on the specification criteria of minimum Akaike Information Criterion (AIC) and the higher R2, the ARMA (1, 0)-EGARCH (1, 1)-M is found to be the better specification to estimate portfolio returns volatility for all 10 portfolios. To arrive at the best model to estimate volatility for 10 portfolios returns the specific to general approach is adopted based on EGARCH-M specification. The specific models are extended by including first portfolios volume, then business cycle variables(market return, oil prices, gold prices, foreign exchange, foreign cash reserves), then deterministic shocks and finally stochastic shocks. The in-sample and out-sample forecasting performance evaluation suggests that general model is most superior to estimate and forecast portfolio returns volatility for all ten portfolios. The ARMA(1,0)-EGARCH(1,1)-M in general form is used further for examining the volatility spillover effect between the high risky and low risky portfolio returns volatilities and also among high risk, low risky portfolio volatility and business cycle variables. The results reveal that the high/low beta portfolios returns are more volatile and that the risk premium for facing volatility risk by almost all of the high-beta portfolios returns is highly significant compared to the low-beta portfolios returns. This indicates that the low-beta portfolios are less volatile and hence slowly respond to the new/surprises. The forecasting performance of the low-beta portfolios returns volatilities is high relative to the high-beta portfolios returns volatilities because of the strong predictability power of the less risky stocks relative to the high volatile stocks. Also, the empirical results reveal the existence of the volatility spillover effect between the high beta portfolio returns and the low beta portfolio returns as well as between the high/low portfolio returns and the business cycle variables respectively. The present study tend to be a comprehensive study that engulfs in itself all of the major and potential factors that may influence the portfolios returns volatilities and the predictability of the high-to-low beta portfolios returns volatilities as well as the volatility spillover effect. This analysis could be helpful for the academicians, researchers, financial analysts, local and foreign investors, portfolio managers, macro-economic policy makers and the Securities and Exchange Commission of Pakistan to forecast volatility, analyze spillover effects on one hand. On the other hand, the present study uses this analysis for understanding linkage between stock market volatility and financial and business cycle variables, development of modern corporate sector and efficient capital market to foster investment and economic growth in Pakistan.