Development of College of Industrial Technology FM Broadcast Trainer

An FM Broadcast Trainer was developed to expose the students to the basic equipment needed in radio broadcasting. The cost of Portable FM Broadcast Trainer is much lower than the cost of the traditional commercial equipment because of the materials used. The FM Broadcast Trainer is laboratory equipment that can be used by schools offering academic programs in Industrial Courses specifically Electronics Communication courses. At present there is no portable FM broadcast station available in the local market. Some schools are reluctant to by new FM station equipment since these are quite costly. To resolve this problem, the researchers deemed it necessary to design and develop a portable FM Broadcast Trainer that is simple and affordable to fulfil the basic curricular requirements for offering courses in Electronics Communication Technicians. This is a requirement for our graduates to qualify to take the Radio Telephone Operator examination given by the National Telecommunication Commission the telecommunication body in the Philippines counterpart of Federal Communication Commission in the US. Aside from this, the station will be a venue for Mass Communications students and a vehicle for channelling important announcement from the School.

Impact of Technical Analysis on Karachi Stock Exchange of Pakistan

This thesis examines the impact of Technical Analysis on Karachi Stock Exchange by investigating the tools used for Technical Analysis for the sample period of 1997 to 2014. The KSE-100 index was examined to represent the market over the sample period for the following three aspects. First the results indicate that KSE-100 index do not follow random walk model by applying the Wright„s rank and sign variance ratio test. Secondly the study compared a variety of extremely popular technical trading rules based on simple moving averages, exponential moving averages, relative strength index and stochastic RSI to find the predictive ability of these indicators. The thesis also employed generalized regression neural network (GRNN) for stock prediction. The results show that these trading rules have predictive power over future price behavior. It is also evidenced that the inclusion of oscillators like RSI and RSIStochastic increase the performance in generating above average return. The combination of GRNN with simple moving averages also produced significant return. Based on these trading rules, the study proposed two trading strategy in order to know that whether investor beat buy-and- hold strategy. The results indicate that strategy based onthese rules have the ability to outperform the buy-andhold strategy. The results are significant even after considering the transactional cost. Technical Analysis is very effective for the investors in creating excess return for the sample period.