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شیخو شریف اوکاڑہ سے فیصل آباد جانے والی سڑک پر بنگلہ گوگیرہ سے 8کلو میٹر شمال مشرق میں اوکاڑہ شہر سے تقریباً 30کلو میٹر کے فاصلہ پر واقع ہے۔ رینالہ خورد سے براستہ ستگھرہ بھی تقریباًاتنا ہی سفر بنتا ہے۔یہ علاقہ کبھی ضلع ساہیوال میں شامل تھا جو ادب کے لحاظ سے مردم خیز سر زمین شمار کی جاتی ہے۔ مجید امجد، منیر نیازی، جعفر شیرازی، گوہر ہوشیار پوری، ظفر اقبال اور حاجی بشیر احمد بشیرجیسے نامور شعرا کے اس شہر کی بنیاد اس وقت رکھی گئی جب 1864میں ریلوے لائن بچھ جانے کے بعد گوگیرہ سے ضلعی ہیڈ کوارٹر منتقل کرتے ہوئے گورنر پنجاب سر رابرٹ منٹگمری کے نام سے نیا ضلع بنانے کا اعلان کیا گیااور لاہور ملتان ریلوے لائن پر واقع ساہیوال کو منٹگمری کا نام دیا گیا۔1915تک مختلف انتظامی تبدیلیوں کے بعد یہ ضلع تحصیل پاکپتن، تحصیل اوکاڑہ، تحصیل دیپالپور اور تحصیل منٹگمری کی شکل میں آچکا تھا۔ قیام پاکستان کے بعد اس ضلع کے انتظامی ڈھانچے میں تو کوئی تبدیلی نہ ہوئی البتہ عوام کے پر زور اور دیرینہ مطالبہ پر 14نومبر 1966کو ضلع منٹگمری کا نام دوبارہ ساہیوال رکھ دیا گیا۔(۱) یکم جولائی 1982کو جب ضلع اوکاڑہ کا قیام عمل میں لایا گیا تو شیخوشریف کا علاقہ ضلع اوکاڑہ میں آگیا۔
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شیخو شریف سے جنوب مشرق میں 8کلومیٹر کے فاصلہ پر ستگھرہ کا تاریخی قصبہ واقع ہے۔ ستگھرہ کو بعض جگہ صد گھرہ بھی لکھا گیا ہے۔ ستگھرہ اور صد گھرہ میں فرق صرف ’’س‘‘ اور ’’ص‘‘ کا ہے۔
مولانا نور احمد فریدی، قصرِ ادب ملتان والے ایک سن رسیدہ عالم اور جہاں...
Dengue fever is a vector borne disease and is caused by DEN Virus. This virus has four different serotypes. The vectors are two mosquitoes known as Aedesaegypti (the yellow fever mosquito) and Aedesalbopictus(the Asian tiger mosquito). First case of dengue fever was reported back in 1994 in Karachi. A complete outbreak of this epidemic shook the whole nation in 2012. Uptill now, Lahore a city full of culture, witnessed about 16,580 confirmed cases and 257 deaths. About 5000 confirmed cases with 60 deaths were reported from the rest of the provinces. Under guidelines of WHO, Government has made efforts to combat this epidemic. Although the overall efforts have minimized the outbreak on controllable levels but dengue fever is a continuous threat. Since no permanent cure is available, the transmission of DEN virus is controlled indirectly. So the prime focus is to control mosquito population and decrease the possible hot spots i.e. Mosquito breeding sites in human habitations. Every year, the country witnesses monsoon season which brings vast areas full of clear standing waters providing breeding sites for mosquitoes which ultimately leads to increased number of patients suffering from dengue fever. Efforts have been made to fight against dengue including formation of dengue wards in hospitals, vector surveillance, community education, reactive vector control etc. A study has shown prevalence of four mosquito genera in Pakistan including Aedes, Culex, Armigeresand Anopheles. All of the above mentioned genera are associated with disease transmissions as they are the vectors of different viruses and parasites. It is the need of hour to do a collaborative effort stressing the community mobilization and management in war against dengue.
This study investigates the relative performance of linear versus nonlinear methods to predict volatility and return in equity markets. The study is performed on the EAGLEs and NEST markets, including China, India, Indonesia Pakistan, Bangladesh and Malaysia by using daily data of equity markets from the period January 4, 2000 to December 30, 2010. Nonlinear and asymmetric ARCH effects have been test by Lagrange Multiplier test. A range of models from random walk model to multifaceted ARCH class models are used to predict volatility. The results reveal that MA (1) model ranks first with use of RMSE criterion in linear models. With regards to nonlinear models for predicating stock return volatility, the ARCH, GARCH-in-Mean (1, 1) model and EGARCH (1, 1) model perform well. GARCH-in- Mean model outperforms on the basis of AIC, SIC and Log Likelihood method. It is concluded that GARCH specification is best in performance to capture the volatility. GARCH in mean model is extended with the macroeconomic variables in the variance equation for SS, BSE, JCI, KSE, KLSE and DSE. The macroeconomic variables include CPI, Term Structure of interest rate, industrial production and oil prices.Data for Macroeconomic variable is on monthly basis for the period Jan 2000 to Dec 2010.For SS, BSE, JCI, DSE, KLSE and KSE markets the conditional mean is significant and models the persistency in long run scenario and suggests for an integrated process. The model indicates that oil price have positive impact on volatility for SS. For BSE change in industrial production index and interest rate change have negative coefficients which indicate that industrial growth and increase in interest rate change has negative relationship with the volatility for this economy. For JCI the model indicates that change in growth in industrial production has positive impact on volatility. For KSE, ARCH and GARCH terms are not significant but growth rate in real sector and oil price has significant impact on volatility. However DSE has no significant results. For KSE the model indicates that inflation has positive impact on volatility but change in oil price has negative effect on volatility.Bullish market effect is quite significant in explaining the volatility capturing ability for all the equity markets. The TGARCH(1,1) model isestimated for SS, BSE, JCI, DSE KLSE and KSE returns series and results indicate that asymmetric effect exists for all the equity markets which indicates the presence of leverage effect. Study concludes that TGARCH (1,1) model is a potential envoy of the asymmetric conditional volatility procedure for the daily frequency of the data regarding to equity markets of SS, BSE, JCI, DSE, KLSE, and KLSE. Further GARCH-in-mean model is extended with value at risk that indicates the variables for variance equation are statistically significant and the VaR have significant impact on all equity markets in explaining the conditional volatility. In Last GARCH-in-Mean Model is extended with the semi-variance and results indicate that the downside risk causes rise in the volatility. It has ability to capture the asymmetric behavior of equity returns and reports the fat tails of the returns. It is concluded that volatility plays a significant role in asset price determination. Keywords: Conditional volatility, linear, nonlinear, Asymmetric effect, Macroeconomic Variables, Bullish, Value at Risk, Semi-Variance.