Semester 1 and Semester 2.

Electromagnetic Waves:   PH1031 - Waves, Particles and Quanta Module or equivalent   PH1012 – Mathematics Module     Modelling Complex Systems:   None.     Business Finance:   Accounting 1 or equivalent

Electromagnetic Waves:   To provide competence in basic electromagnetic theory and problem solving. Solution problems involving magnetic circuits.  To establish the four integral Maxwell's equations which are of fundamental importance in physics. Combine these to investigate electromagnetic wave propagation.     Modelling Complex Systems:   To characterize complex systems in nature and man-made systems. To introduce the student to the basic concepts behind neural networks, genetic algorithms, stochastic techniques and game theory.  To highlight the range of application of these techniques in finance and in the physical sciences.  To communicate scientific ideas orally.     Business Finance:   This module aims to give the student an understanding of the principles governing financial management of a business.  It will equip the student as a manager with the techniques for evaluating the financial needs of a business, identifying possible sources of finance, the most effective course of action to obtain that finance, and utilizing such finance in the attractive opportunity.  It will also provide an appreciation of the role of the finance function in the commercial life of the business.     To pass this component the student will demonstrate a familiarity of business finance (corporate finance and investment management).  The student should display some understanding of relevant issues and some familiarity with the relevant literature and techniques.

Electromagnetic Waves:   Students should be able to tackle problems involving magnetic circuits, understand and apply Maxwell’s equations, derive electromagnetic wave equation and apply to TEM waves.     Modelling Complex Systems:   At the end of the component, students should   -          be able to identify the general characteristics of a complex system.   -          be able to describe the general structure of neural networks, explain the workings of a three-layer, feed-forward, fully connected network in detail and describe how neural networks can be trained   -          be able to explain the use of the genetic algorithm for optimization problems   -          understand how pseudo-random numbers are generated by a computer and how different distributions may be generated, explain the Metropolis algorithm and the principles of importance sampling   -          be able to qualitatively explain game theory, its relationship to group interaction and company behaviour   -          be able to précis research papers and present the results orally.     Business Finance:   On successful completion of this component the students will be able to:   1.                  Appreciate the role and scope of corporate finance in the financial planning process of any firm.   2.                  Understand the time value of money and its implication in interpreting cash flows occuring in different time horizon in accounting statements.   3.                  Perform valuation of different assets based on the DCF method and appreciate the factors effecting such valuation.   4.                  Evaluate potential investment opportunities with its cost and risk factors, and select suitable ones in case of multiple alternatives, budgetary constraints and capital rationing   5.                  Identify the different sources of financing with their relative implications i.e. advantages and disadvantages.   6.                  Understand and appreciate the theories behind use of debt financing as leverage and the optimal capital structure for any firm.   7.                  Understand how companies determine their dividend payout policies and the signal that sends to the market.   8.                  Understand the success and the failure of mergers and acqusitions.

Electromagnetic Waves:   The investigates further the topics of magnetism and electromagnetic waves.     Diamagnets, Paramagnets, Ferromagnetics, Magnetisation M, Magnetisation current, Magnetic intensity H, Magnetic permeability, Magnetic susceptibility, Magnetic circuits, Reluctance, Hysteresis, Permanent magnets, Boundary conditions for B and H.     Displacement current, fourth Maxwell equation, review of vector analysis, Electromagnetic Waves, Speed, Refractive index, Attenuation, Skin depth, Uniform Plane waves, Linear Polarisation, Energy density and Power of Waves, Waves at Boundaries - reflection & refraction.     Fresnel's equations, Brewster angle, Total Internal reflection.     Modelling Complex Systems:   This module provides an introduction to some computational techniques widely used in management, finance and in the physical sciences.     Module Content:   -          Properties of complex systems; emergent behaviour, scale-invariance.   -          Artificial Neural Networks (ANN): general concepts, focus on the three-layer, feed-forward, fully connected ANN.  Training an ANN by back propagation.   -          Genetic algorithms (GA): reproduction, cross-over and mutation.  Linking GAs to ANNs.   -          Stochastic simulation and Monte Carlo methods: pseudo-random numbers, manipulating of stochastic variables, simple Monte Carlo including importance sampling and the Metropolis algorithm.   -          Game theory: non-cooperative game theory, the Prisoner’s dilemma.     Business Finance:   1.                  Working Capital Management   2.                  Time Value of Money   3.                  Asset Valuation   4.                  Capital Investment Appraisal   5.                  Risk and Return   6.                  Portfolio Theory & CAPM   7.                  Sources of Finance (Capital and Money Markets)   8.                  Cost of Capital   9.                  Capital Structure   10.              Dividend Policy   11.              Mergers and Acquisitions

Electromagnetic Waves:   12 hours of lectures and tutorial periods.     Modelling Complex Systems:   The course is presented using uLearn, the university's e-learning system.  12 hours are scheduled for lecturer-assisted session.     Business Finance:   The teaching and learning strategy is designed to allow a student to come to grips with what is essentially a subject of mixed theory and practice:   1.             Weekly one two-hour lecture incorporating class-room participation for better understanding.   2.             Fortnightly tutorial sessions for solving problems to understand the contents lectures. The tutorials cover worked examples which are an integral part of the course.  Will provide the necessary support during these sessions for deeper understanding using MCQ, short and long problem solutions.   3.             ULearn discussion forums to address any issues related to the constant, learning teaching environment, and delivery of the course and/or specific topics.   4.             ULearn will be used for delivering optional mock MCQ and short question examination, giving the participants an opportunity to get formative feedback.   5.             Utilizing ULearn as the main pool of resources including lecture handouts, tutorial problems, mock exercise, and discussions. Besides using ULearn as the main means of communication to establish resource efficiency and communicational effectiveness.   6.             Weekly office hours provided by lecturers.   7.             Support of lecture material by directed reading in selected textbooks and journal articles.

Electromagnetic Waves:   i.                Grant & Philips, Electromagnetism, Wiley.   ii.              Halliday, Resnick and Walker , Fundamentals of Physics, [Extended Fifth Edition], Wiley.     Modelling Complex Systems:   No single text covers all the material contained in this component, although many texts in the library explain the principles of one technique.  The following are suggested.   i.                Beltratti, Margarita and Terns, Neural networks for Economic and Financial Modelling, Thomson Computer Press. [for neural networks and genetic algorithms].   ii.              Frenkel and Smit, Understanding Molecular Simulation, Academic Press [for Monte Carlo Modelling].   iii.             Beale and Jackson, Neural Computing: an introduction, Institute of Physics Press   iv.            [for Neural Networks].   v.              Goldberg, Genetic Algorithms in Search, Optimisation and Machine Learning,   vi.            Addison-Wesley [for Genetic Algorithms].   vii.           Each month, the journal Physica A publishes articles using the techniques explored in this course.  Most do not require knowledge beyond an undergraduate level to be understood.   viii.         Lui Lam, Nonlinear Physics for beginners, World Scientific [for overview of typical Complex Systems and methods of their description].   ix.            Challet, Minority Games, Oxford University Press [for Game Theory].     Business Finance:   Essential Reading: 1.         Pike, R. and Neale B. (2009) Corporate Finance and Investment: Decisions & Strategies,             FT Prentice Hall Recommended Reading : 1.         Ryan, B. (2007) Corporate Finance & Valuation, Thomson Learning EMEA 2.         Peirson, G. Brown, R. Easton, S. Howard, P. Pinder, S (2006) Business Finance, 9th ed.,             McGraw-Hill Irwin 3.         Van Horne, J. Wachowicz Jr., J (2005) Fundamentaals of Financial Management, 12th ed.,             FT Prentice Hall 4.         Watson, D and Head, A (2004) Corporate Finance: Principles & Practice, 3rd ed., FT             Prentice Hall 5.         Keown, A et al (2006) Foundation of Finance, 5th ed., Pearson Background Reading: 1.         McLaney, E (2006) Business Finance: Theory & Practice, 7th ed. FT Prenctice Hall 2.         Atrill, P. (2006) Financial Management for decision makers, 4th ed. FT Prentice Hall

August 2010.