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.
پنڈت ہردے ناتھ کنزرو یہ سطریں لکھی جارہی تھیں کہ پنڈت ہردنے ناتھ کنزرد کی وفات کی خبر ملی، انھوں نے بڑی لمبی عمر پائی، نوے سال کے تھے، وہ ایک جلیل القدر، مرنجان مرنج، بامروت، وضعدار شخصیت، پارلیمانی دستور کے بڑے ماہر ہندو مسلمان کی ملی جلی تہذیب کے عمدہ نمونہ اور اردو زبان کے بڑے محسن کی حیثیت سے برابر یاد کئے جائیں گے، وہ اپنی ترشی ہوئی بھلمنساہت کی وجہ سے ہندوستان کی سیاست کی جذباتی ہم آہنگی کے قابل تقلید نمونہ بن سکتے ہیں، بشرطیکہ موجودہ قومی دھارے کے بنانے والے ان کو ایسا ہی سمجھیں۔ (’صباح الدین عبدالرحمن، اپریل ۱۹۷۸ء)
In Islamic legislation Ijtihad plays an important role and has central position in the whole process. Demands of life change day by day thus it become necessary to take on the structural review of Islamic laws keeping in mind the spirit and discipline of Islamic. Ijtihad thus play as a perfect tool for legislation. Regarding fatawas the jurists followed the methodologies of companions, tabieen, and taba Tabaeen. In cases in which they did not find any legal opinion of their teachers related to a specific problem they themselves tried to find out the solution for that problem from the relevant Texts and formulate their own fatawa. In Pakistan the Judiciary that performs the task of interpretation for law-making, Majlis-e-Shura and various Ulama are exercising the job of Ifta. The Council of Islamic Ideology is the official legislative body of fatawa. Taqleed is also an acceptable mode of legislation whose proofs are evident from Quran and Sunnah. It has been used as a source of legislation in Pakistan as well. In constitution of Pakistan article 189 and 201 are related to Taqlid. Article 189 and 201 makes the decisions of Supreme Court binding on all courts and the High court judgments binding on all subordinate courts. Thus the legislative process in Islam employs the methods of Ijtihad, Ifta and Taqlid as a perfect tool of legislation.
Modelling and simulation of molecular systems helps in understanding the behavioural mechanism of biological regulation. Time delays in production and degradation of expressions are important parameters in biological regulation. Constraints on time delays provide insight into the dynamical behaviour of a Biological Regulatory Network (BRN). A recently introduced Process Hitting (PH) Framework has been found efficient in static analysis of large BRNs, however, it lacks the inference of time delays and thus determination of the constraints associated with the evolution of expression levels of biological entities of BRN is not possible. In this thesis, we propose a Hybrid Process Hitting scheme for introducing time delays in Process Hitting Framework for dynamical modelling and analysis of Large Biological Regulatory Networks. It will provide valuable insights into the time delays corresponding to the changes in the expression levels of biological entities thus possibly helping in identification of therapeutic targets. The proposed framework is applied to a well-known BRNs of Bacteriophage λ and ERBB Receptor-regulated G1/S transition involved in the breast cancer to demonstrate the viability of our approach. Using the proposed approach, it was possible to perform goal-oriented reduction of the BRN and also determine the constraints on time delays characterizing the evolution (dynamics) of the reduced BRN. The proposed Hybrid Process Hitting methodology is applied to a considerably large BRN of Apoptosis Pathway comprising of 90 entities for obtaining the dynamical properties of this pathway. The determination of constraints on time delays corresponding to the evolution of entities for the reduced BRN (entities involving feedbacks) was successfully computed using the new methodology. The chemical reactions as well as the biological interactions are all stochastic in nature and could, therefore, assume any rate of change within the range of delays determined through Hybrid Modeling. The same has thus been extended to Stochastic Modeling using Stochastic Petri Nets (SPNs) in which the random delay in firing of the transitions aptly captures the stochastic behaviour of changes in expression levels of genes. The proposed scheme was found to be more efficient than existing methodology and less computationally intensive. It was applied to the mucus production in Pseudomonas Aeruginosa BRN and results obtained from Stochastic Petri Nets are in agreement with the Hybrid Modeling results which establishes the accuracy of this approach as well as provide more insight in the dynamical behaviour of BRNs through simulation.