BSc in Financial Engineering (2018 onwards)
Transcript of BSc in Financial Engineering (2018 onwards)
BSc in Financial Engineering (2018 onwards)
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BACHELOR OF SCIENCE IN FINANCIAL ENGINEERING
CURRICULUM REVISION - DEGREE PROGRAM IN FINANCIAL ENGINEERING
Introduction
BSc in Financial Engineering (external) degree programme focuses on creating new financial
strategies and tools used to forecast financial trends, develop financial instruments / models
and establish new methods that are beneficial to businesses and organizations to make
strategic financial decisions. Students pursuing this degree will learn essential Mathematics,
Statistics, language and computer skills, Basic Economics and Accounting, Quantitative
techniques, quantitative finance, financial modeling, risk management, corporate finance,
Professional development and practices in finance.
Rationale
The drive toward financial market expansion and development suggests the need for people
who are able to identify, evaluate, forecast, disseminate and provide integrated solutions to
meet the needs of financial sector. “Financial Engineering” continues to be one of the fastest
growing areas within modern financing/banking. Together with the sophistication and
complexity of modern financial products, this exciting discipline continues to act as the
motivating factor for new mathematical models and the subsequent development of
associated computational schemes. Although relatively young, financial mathematics has
developed rapidly into a substantial body of knowledge and established part of mathematical
science. The proposed revision is designed to fulfill the demand for expertise in the drive
toward financial expansion and development.
The course is structured to support all part-time external students to engage with the
Lecturers in the course modules continuously. Learning Management system (LMS) is used
as a self-learning assessment and evaluation mechanism.
The intellectually exciting and practical Finance course will prepare students for a range of
careers in the financial analysis field within Sri Lanka and internationally. With a degree in
Financial Engineering students can harness skills necessary for economic analysis, financial
forecasting, and financial practice as well as for financial consultancy, advisory and financial
product development/analysis.
Indented Learning Outcomes of BSc in Financial Engineering
The end of the 3 years (SLQF Level 5) BSc in Financial Engineering Degree holders should
be able to:
1. demonstrate knowledge and proficiency in the terminologies, theories, concepts,
practices and skills specific to the field of finance and insurance financial product
development.
2. observe and interpret financial markets to uncover potential opportunities and
construct financial portfolios.
3. apply best practices in financial management to make plans, organize projects,
monitor outcomes and provide financial leadership.
4. apply the Standards of Practice and Codes of Conduct of Financial Practitioners to
address ethical challenges within the business environment and demonstrate
intellectual maturity in a global setting.
5. practice professionalism and uphold ethical standards and improve/update skills
required for employment and life-long learning.
6. effectively communicate & disseminate knowledge, information and ideas to
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specialist and a wider society
7. perform independently as well as interdependently
Specific Intended Learning Outcomes
Upon completion of the BSc Financial Engineering, the following criteria shall be fulfilled:
1. KNOWLEDGE
Upon completion of the BSc in Financial Engineering programme, the student should
possess knowledge and understanding of the following:
● Insight into some of the subjects fundamental to finance.
● Basic principles, theories and applications in the field of financial mathematics.
● Mathematical analysis common to most financial analysis disciplines, calculus,
linear algebra.
● Differential equations models for finance.
● Numerical methods and scientific computing to solve problems in calculus,
differential equations, and linear algebra.
● Basic probability theory and statistics including data analysis, error analysis,
hypothesis testing and linear regression.
● Basic understanding of financial programming in common languages and
spreadsheet applications.
● Basic principles of Economics and Accounting
2. SKILLS
Upon completion of the BSc in Financial Engineering programme, the student should have
gained the skills to:
2.1 Disciplinary skills
● Quantify and model the financial structure of projects and corporations and for
that purpose apply suitable techniques.
● Design mathematical models of the financial functions of organizations and solve
the formulated problems by a range of quantitative techniques, including
simulation and optimization techniques.
● Plan, manage and analyze financial and operational structures in projects, using
recognized financial techniques as well as other current best-practice methods.
● Apply the statistical methods in order to analyze and interpret data.
● Carry out risk assessment by disciplines of risk management and decision
analysis.
2.2 Personal Skills
● Apply financial methods to projects, i.e. have the ability to assess the financial
feasibility of the projects and identify the key factors in a given situation, and
develop an approach to a solution.
● Formulate and work on open-ended problems, including creative thinking.
● Apply research methodology, including the fundamentals of technical writing and
information finding, including literature search.
● Apply standard scientific principles to develop financial solutions to a range of
practical problems.
2.3 Interpersonal skills
● Develop strategic communication skills through industry based management case
studies.
● Communicate effectively and professionally and formulate sound arguments,
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both in writing and by means of presentations, using appropriate professional
techniques.
● Developing team analytical negotiation skills in providing a business proposal
and project plan.
● Be an effective team member and contribute to the management of team projects
by interpreting data analysis.
3. COMPETENCE (Attitudes, Values, Professionalism and Vision for life,
Lifelong Learning)
Upon completion of the BSc programme, the student should be able to utilize the knowledge
and skills he/she has acquired to:
● Apply analytical skills and modelling methodologies to recognize, analyze, synthesize
and implement operational solutions to Finance problems
● Apply standard quantitative scientific principles to develop finance solutions to a
range of practical problems in Finance
● Appreciate the importance of keeping up with evolving industry practice technologies
and technology and research, to meet expand professional competencies and industry
expectations.
● Undertake further studies towards a graduate level degrees and professional
qualifications.
Program Structure
B.Sc. in Financial Engineering will be completed in three years (90 Credits / SLQF Level 5)
and it consists of three levels.
LEVEL I: Diploma in Financial Engineering (30 Credits)
LEVEL II: Advanced Diploma in Financial Engineering (60 Credits)
LEVEL III: BSc in Financial Engineering (90 Credits)
LEVEL I
Semester Course
Code
Course Title Credit
/Hours
Core
/Elective
Semester I FE 1101 Economics I for Finance 30L 2C Core *
Semester I FE 1102 Mathematics for Finance 30L 2C Core *
Semester II FE 1103 Accounting I for Finance 30L 2C Core *
Semester I FE 1104 Statistics I for Finance 30L 2C Core
Semester I FE 1105 Applied Finance 30L 2C Core *
Semester I FE 1106 Computing for Finance 60P 2C Core *
Semester II FE 1107 Financial English 30L 2C Core *
Semester I FE 1108 Management Science I 30L 2C Core
Semester II FE1109 Economics II Finance 30L 2C Core *
Semester II FE 1110 Statistics II for Finance 30L 2C Core
Semester II FE 1111 Calculus for Finance 30L 2C Core *
Semester II FE 1112 Linear Algebra 30L 2C Core
Semester I FE 1113 Differential Equations I for
Finance
30L 2C Core
Semester I FE 1114 Financial Markets & Instruments 30L 2C Core *
Semester II FE 1115 Numerical Methods I for Finance 60P 2C Core *
*Compulsory course to eligible for Diploma in Financial Engineering
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LEVEL II
Semester I FE 2101 Accounting II for Finance 30L 2C Core *
Semester I FE 2102 Advanced Applications in
Spreadsheet
60P 2C Core
Semester II FE 2103 Financial risk Management I 30L 2C Core *
Semester I FE 2104 Investment Analysis I 30L 2C Core *
Semester I FE 2105 Management Science II 30L 2C Core
Semester I FE 2106 Financial Econometrics 30L 2C Core *
Semester I FE 2107 Insurance for Business 30L 2C Core *
Semester II FE 2108 Investment Analysis II 30L 2C Core *
Semester II FE 2109 Survival Models and Analysis 30L 2C Core *
Semester II FE 2110 Differential Equations II for
Finance
30L 2C Core
Semester II FE 2111 Life Insurance Models 30L 2C Core *
Semester II FE 2112 Fuzzy Modeling 60P 2C Core
Semester I FE 2113 Financial Statement Analysis 30L 2C Core *
Semester II FE 2114 Numerical Methods II for Finance 60P 2C Core *
Semester I FE 2115 Game Theory 30L 2C Core
*Compulsory course to eligible for Advance Diploma in Financial Engineering (together
with Level I *)
LEVEL III
Semester II FE 3101 Investment Analysis III 30L 2C Core
Semester II FE 3102 Financial Risk Management II 60P 2C Core
Semester I FE 3103 Computational Modeling 30L 2C Core
Semester I FE 3104 Management Science III 30L 2C Core
Semester I FE 3105 Stochastic Calculus for Finance 30L 2C Core
Semester I FE 3106 Banking and International Finance 30L 2C Core
Semester II FE 3107 Portfolio Management 30L 2C Core
Semester I FE 3108 E-Commerce 30L 2C Core
Semester II FE 3109
Professional Development in
Finance
60P 2C Core
Semester I FE 3110 Case Studies in Management 60P 2C Core
Semester II FE 3111 Professional Financial Practice 60P 2C Core
Semester I FE 3112 Project 180P 6C Core
Semester II FE 3113 Data Analysis 60P 2C Core
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Course Code &
Title
FE1101 Economics I for Finance
Credit Value &
Lecture Hours
30 L 2C
Prerequisite None
Objective To provide essential Economic knowledge to be applied with quantitative
Finance.
Learning
Outcomes
At the end of the course students will be able to;
● Interpret the essential principles of microeconomics.
● Apply economic theory to solve and interpret financial problems.
Course Content Introduction to Microeconomics, Demand and supply, Elasticities of Demand,
,The application of Market Laws and Elasticities ,Theory of Consumer Behavior
Theory of Production and Analysis of Cost, Labour markets, Theory of
Production and the Production of Two Variable Inputs, The Theory of Cost of
Production, The firm and its objectives , The market Structure, Price and output
determination, Market Failure and Public goods.
Methods of
Evaluation
● Final exam – 60%
● Take home assignment- 15%
● Midterm Test- 15%
● In class Assessment-10%
Recommended
Reading
● Lipsey, R. G. & Chrystal, K. A (2015). Principles of Economics (13th
ed.).
Oxford University Press.
● Dwivedi, D. N. (2009). Microeconomics: Theory & Applications. The
McGraw- Hill Companies.
Course Code &
Title
FE 1102 Mathematics for Finance
Credit Value &
Lecture Hours
30L 2C
Prerequisite None
Objective To provide basic mathematical concepts required in Finance.
Learning
Outcomes
The end of the course students are able to;
• Express and derive mathematical statements.
• Identify functions and their properties.
• Solve basic linear difference equations, describe their behavior and apply
them related to finance.
Course Content Introduction to Set Theory and Mathematical Reasoning: Propositional Logic,
Logical Operations, Truth Tables, Proofs and types of proofs, Quantifiers,
negation of statements with quantifiers and Types of Proofs, Relations, types of
functions such as one-to-one, onto, inverse, Inequalities, Linear Difference
Equations and their applications in Finance.
Methods of
Evaluation
● End Semester Exam – 60%
● Continuous Assessments – 40%
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Recommended Reading
● Eccles, P. J. (1997). An Introduction to Mathematical Reasoning:
Numbers, Sets and Functions. Cambridge University Press.
● Goldberg, S. (1958). Introduction to Difference Equations. Dover
Publications, Inc., New York.
Course Code &
Title
FE 1103 Accounting I for Finance
Credit Value &
Lecture Hours
30L 2C
Prerequisite None
Objective Provide the Fundamental concepts of Financial and Management Accounting
principles of a Business.
Learning
Outcomes
At the end of the course, students are able to;
● Identify the basic principles of Financial Accounting.
● Identify the basic principles of Management Accounting.
Course Content Introduction to Accounting and its environment, Financial Statements, Ledger
accounting, Profit and Loss Account, Balance Sheet, Trial balance, Trading and
Manufacturing Account, Bank reconciliation, Intangibles, Suspense accounts,
Control of cash and bank transactions, Inventories, Income and Expenditure
Account and Accounts for small business unit, Incomplete records, Cost
Accounting Cost classification, Materials and Stocks control, Labor cost
allocation and Overheads classification and analysis, Absorption and Marginal
costing, Financial Accounting packages.
Methods of
Evaluation
● Continuous Assessments – 40%
● End Semester Exam – 60%
Recommended
Reading
● Wijewardena, H. (2004). Financial Accounting in Sri Lanka.
● Wood, F. (1967). Business Accounting.
Course Code &
Title FE 1104 Statistics I for Finance
Credit Value &
Lecture Hours
30L 2C
Prerequisite FE 1006
Objective To provide basic statistics concepts within a financial context.
Learning
Outcomes
The end of the course students are able to;
● Identify and apply commonly used techniques for data collection and
analysis.
● Analyze statistical data using graphical methods, measures of central
tendency, dispersion and location.
● Identify some applications of statistical analysis in business practice.
● Use Excel to perform statistical analysis.
● Apply fundamental concepts of probability to solve problems in business
decision-making and interpret the outcomes.
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Course Content Introd Types of Variables, Descriptive Statistics, Data and Representation, Measures of
Central Tendency, Measures of Spread, Measures of Shape, sample space and
events, defining probability, basic elements of Probability, Mutually exclusive
events, Addition and Multiplication rules, conditional probability, Independence
of events, Combinatorial Probability, Bayes Theorem/Law of Probability, Excel
functions for basic statistics.
Methods of
Evaluation
● End Semester Exam – 70%
● Continuous Assessments – 20%
● Practical Exam (Excel) – 10%
Recommended
Reading
● Leekly, R. M. (2010), Applied Statistics for Business and Economics.
CRC Press.
● Wegner, T. (2013). Applied Business Statistics: Methods and Excel-
Based Applications (3rd ed.). Juta and Company Ltd.
Course Code &
Title
FE 1105 Applied Finance
Credit Value &
Lecture Hours
30L 2C
Prerequisite None
Objective To provide basic concepts of money valuation process.
Learning
Outcomes
The end of the course students are able to;
● Interpret and compute interest rates as required rate of return, rate of
discount, opportunity cost, effective annual rate of return, given the stated
annual rate of return, frequency of compounding.
● Compute and interpret the future value and present value of a single sum
of money, a series of regular payments (basic annuity), and varying
regular payments.
● Compute and apply the feasibility of small scale projects based on future
and present value concepts.
Course Content Interest rate, Simple and Compound interest rate, Time value of Money, Present
value, Future value, Discounting, Compounding, Effective rate of return (EAR),
Basic annuity valuation, Annuity immediate, Annuity due, Perpetuity,
Discounted cash flow analysis, NPV, Excel financial functions and their
applications.
Methods of
Evaluation
● End Semester Exam – 60%
● Mid Semester Exam – 20
● Continuous Assessments –20%
Recommended
Reading
● Kellison, S. G. (2009). The Theory of Interest (3rd ed.). McGraw-Hill
Irwin.
● Beaumont, P. H. (2004). Financial Engineering Principles: A Unified
Theory for Financial Product Analysis and Valuation. John Wiley &
Sons, Inc.
● Capinski, M. & Zastawniak, T. (2003). Mathematics for Finance: An
Introduction to Financial Engineering. Springer.
Course Code & FE 1106 Computing for Finance
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Title
Credit Value &
Lecture Hours
60P 2C
Prerequisite None
Objective To provide basic knowledge in spreadsheet and mathematical programming
languages.
Learning
Outcomes
The end of the course students are able to;
● Identify formulae in excel.
● Write simple excel programs to solve real world problems.
● Identify functions in MATLAB/Octave.
● Write simple programs using MATLAB/Octave to solve real world
problems.
Course Content Basics of worksheet, Worksheet formulas, Mathematical and statistical functions,
Dates, time and text functions, Financial functions, Lookup, reference and
information functions, Logical and conditional functions, Random functions and
data analyzing tools, Tables and pivot tables, Worksheet programming.
Getting started with MATLAB, Creating Arrays, Mathematical operations with
arrays, Curve plotting, MATLAB /Octave functions, programming in MATLAB
/Octave with common mathematics functions.
Methods of
Evaluation
Continuous Assessments – 100%
Recommended
Reading
● MacDonald, M. (2010). Excel 2010: Missing Manual (1st ed.). O’Reilly
Media, Inc.
● Walkenbach, J. (2010). Excel 2010 Bible (1st ed). John Wiley & Sons,
Inc.
● Gilat A. (2010), MATLAB: An Introduction with Application (4th ed.).
Wiley.
Course Code &
Title
FE 1107 Financial English
Credit Value &
Lecture Hours
30L 2C
Prerequisite None
Objective To introduce students to language elements required to navigate the world of
finance and economics effectively.
Learning
Outcomes
The end of the course students are able to;
● Comprehend and use vocabulary related to various contexts of finance.
● Implement conversational strategies in professional contexts.
● Analyze language structures found in professional context to discern their
functions.
● Produce written communications following the established norms.
Course Content Budgeting: Vocabulary for Budgeting, Asking the Right questions: Probing
Questions, Forming Yes/No Questions, Forming WH Questions
Forecasting: Vocabulary for Forecasting, Answering Questions Without
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Defensiveness, Chart Communication/Storytelling, Transition Phrases for Cause
and Effect; and Contrast and Additions
Negotiating: Vocabulary for Negotiating , Maintaining Integrity and Making
Concessions, Persuasive Language-Logic, Phrases for Concession and Counter
Arguments
Auditing: Vocabulary for Auditing, Types of Power and Speaking Tone ,
Writing Tone and Levels of Formality, Writing Emails and Letters
Economics: Vocabulary for Economics, Building Relationships and Networking
, Reading Strategies and Comprehension, Modifiers and Parallelism
Methods of
Evaluation
● End Semester Exam – 80%
● Continuous Assessments – 20%
Recommended
Reading
● Bovee, C., & Thill, J. (2014). Business communication essentials. Boston:
Pearson.
● Guffey, M. & Loewy, D. (2011). Business communication. Mason, Ohio:
Cengage Learning.
● Sweeney, S. (2014). English for Business communication. Cambridge:
Cambridge University Press.
Course Code &
Title
FE 1108 Management Science I
Credit Value &
Lecture Hours
30 L 2C
Prerequisite FE 1106
Objective To provide basic concepts of Operational Research modeling approach by
constructing and solving linear programming models related to management
science.
Learning
Outcomes
The end of the course students are able to;
● Develop fundamental skills of linear programming models.
● Develop a linear programming model from problem description.
● Apply the Graphical and Simplex methods for solving linear
programming problems.
● Express the dual of a LP problem and interpret the results and obtain
solutions to the primal problem from the solutions of the dual problem.
● Solve LP problems using Excel Solver.
Course Content Overview of Operations Research, Concept of a model, Important topics of
Operations Research and Scope of it, A tool for Decision support system,
Introduction to Linear programming, formulation of problems and their features,
Applications in financial and economics fields, Graphical method, Simplex
method, Two Phase Method, Special cases of Linear Programming, Dual
problem, Economical interpretation of models, Excel solvers for LP problems.
Methods of
Evaluation
Continuous Assessments - 100%
Recommended
Reading
● Hillier, F. S., & Lieberman G. L. (2010). Introduction to Operations
Research (9th ed.). McGraw-Hill, New York.
● Taha, H. A. (2009). Operations Research (8th ed.). Pearson Prentice
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Hall.
Course Code &
Title
FE1109 Economics II Finance
Credit Value &
Lecture Hours
30 L 2C
Prerequisite FE 1101
Objective To explore essential Macroeconomics theories to complement finance. .
Learning
Outcomes
At the end of the course students are able to;
● Interpret the essential principles of macroeconomics.
● Apply economic theory to solve and interpret financial problems.
Course Content Working of an economy by identifying macroeconomic objectives and policies,
Aggregate Demand and Aggregate Supply, Use of fiscal and monetary policies,
Money supply and money demand and the conduct of monetary policy by the
Central bank, Trade theories and the understanding of the balance of payments
and the exchange rates, Determinants of inflation and unemployment, Theories of
economic growth and its determinants, understanding of the phases of the
business cycles.
Methods of
Evaluation
● Final exam : 60%
● Case Study: 10%
● Midterm exam: 15%
● Midterm exam: 15%
Recommended
Reading
● Lipsey, R. G., & Chrystal K. A. (2015). Principles of Economics,13th ed.,
Oxford University Press.
Course Code &
Title
FE 1110 Statistics II for Finance
Credit Value &
Lecture Hours
30L 2C
Prerequisite FE 1104
Objective To provide advanced statistics and probability concepts within a financial
context.
Learning
Outcomes
The end of the course students are able to;
● Identify and apply commonly used probability distributions to model
financial problems.
● Use Excel to analysis and interpret the results.
Course Content Univariate probability Distributions: Probability functions and Probability
density functions, Cumulative distribution functions, Moments generating
functions, Binomial, Negative Binomial, Poisson, Uniform, Exponential,
Gamma, Normal distribution and Standard Normal distribution, Introduction to
the Chi-square distribution, Multivariate Probability Distributions: Joint
probability functions and probability density functions, Joint Cumulative
distribution functions, Central Limit Theorem, Conditional and Marginal
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Probability distributions, Covariance and Correlation coefficient,
Transformations and order statistics, Introduction to Estimation, Estimating the
Population mean, Sampling, Inference, Hypothesis Testing, P-value
Methods of
Evaluation
● End Semester Exam – 60%
● Continuous Assessments – 40%
Recommended
Reading
● Robert M. L. (2010). Applied Statistics for Business and Economics.
CRC Press.
Course Code &
Title
FE 1111 Calculus for Finance
Credit Value &
Lecture Hours
30L 2C
Prerequisite FE 1102
Objective To provide essential concepts in calculus required in Finance.
Learning
Outcomes
The end of the course students are able to;
● Identify the properties of functions derivatives, sequences and series.
● Compute and find limits, derivatives and integrals.
● Apply concepts in calculus to solve problems in finance.
Course Content The Concept of Limit, Continuity, Intermediate Value Theorem, Absolute Extrema
for Continuous Functions, Derivatives, Maxima and Minima of Differentiable
Functions of One and More Variables, Taylor Series and its various forms, Integral
Calculus: Riemann Integration, Mean value Theorem, Sequences and Series,
Concepts of Convergence and properties, Applications in Finance and Economics
fields.
Methods of
Evaluation
● End Semester Exam – 60%
● Continuous Assessments – 40%
Recommended
Reading
● Stewart, J. (2011). Calculus: Early Transcendentals,7th ed., Brooks
Cole.
Course Code &
Title
FE 1112 Linear Algebra
Credit Value &
Lecture Hours
30L 2C
Prerequisite None
Objective To provide essential concepts in linear algebra to solve problems in finance.
Learning
Outcomes
The end of the course students are able to;
● Perform operations in matrices.
● Interpret outcomes of the operations.
● Apply matrices to solve problems in finance.
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Course Content Matrices, Rank, Determinants, Non-singular matrices, Systems of Linear
Equations, Solutions to system of linear equations: Jacobi method, LU-
Decomposition, Vector Spaces subspaces, Null space, Basis and dimension,
Linear Transformations, Change of basis, Matrix representation of a linear
transformation, Inner Product Spaces, Eigenvalues and Eigenvectors, QR
factorization, Quadratic Forms, Linear Functional, Applications in Finance.
Methods of
Evaluation
● End Semester Exam – 60%
● Continuous Assessments – 40%
Recommended
Reading
● Strang, G. (2012). Introduction to Linear Algebra, Wellesley-
Cambridge Press, U.S.
● Liesen, J., & Mehrmann, V. (2015). Linear Algebra,1st ed,Springer.
Course Code &
Title
FE 1113 Differential Equations I for Finance
Credit Value &
Lecture Hours
30L 2C
Prerequisite FE 1111
Objective To provide essential concepts in ordinary differential equations to solve
problems in finance.
Learning
Outcomes
The end of the course students are able to;
● Solve first and second order ordinary differential equations and interpret
the outcomes.
● Model finance related problems using ordinary differential equations and
interpret the solutions in relation to finance and economics.
Course Content Introduction to Mathematical Modeling in Finance with ODEs, Ordinary
Derivatives of Functions: Physical interpretations and real life applications, First
order linear equations and their properties, Separable equations, Orthogonal
Trajectories, Exact Equations, Existence and Uniqueness Theorem without
proof, Applications of ODEs in Population dynamics, Radioactive decay,
models in finance and economics, Second order linear differential Equations,
Linear Equations with constant coefficients: Real roots, Complex roots,
Reduction of Order, Non-homogeneous equations and their applications.
Methods of
Evaluation
● End Semester Exam – 60%
● Continuous Assessments – 40%
Recommended
Reading
● Hermann, M., & Saravi, M. (2014). A First Course in Ordinary
Differential Equations. Springer.
● Tenebaum, M., & Pollard, H. (1985). Ordinary Differential Equations:
An elementary text book for students of Mathematics, Engineering,
and the Sciences. Dover Publications, New York.
● Ahsan, Z. (2004). Differential Equations and their Applications, 2nd
ed., Prentice Hall.
Course Code & FE 1114 Financial Markets & Instruments
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Title
Credit Value &
Lecture Hours
30L 2C
Prerequisite None
Objective To provide the basic knowledge on various financial markets, their assets and
trading mechanisms.
Learning
Outcomes
At the completion of this course students are able to;
● Explain the functions of different financial markets.
● Describe the various assets and instruments traded in these markets and
the roles of different market participants.
● Perform simple calculations with respect to financial assets and interpret
results.
Course Content Types of Financial markets and their characteristics, Equity market, Forex
market, Insurance market, Bonds, Introduction to T- bills, Options, Derivatives,
Mutual Funds, Financial indices and their characteristic, Example of Financial
indices (Sri-Lankan and Global context), Dynamics of World Markets,
Commodity Markets.
Methods of
Evaluation
Continuous Assessment
● Classroom test 1 - 20%
● Classroom test 2 - 20%
● Classroom Group Work - 10%
● End Semester classroom test – 30%
● End Semester online test – 20%
Recommended
Reading
● Valdez, S., & Molyneux, P. (2013). An Introduction to Global Financial
Markets (7th ed.). Palgrave Macmillan.
● Barucci, E. (2003). Financial Markets Theory: Equilibrium, Efficiency
and Information, Springer.
Course Code &
Title
FE 1115 Numerical Methods I for Finance
Credit Value &
Lecture Hours
60P 2C
Prerequisite FE 1106
Objective To provide computer programming competencies to solve numerical problems.
Learning
Outcomes
At the end of the course, students are able to;
● Identify the numerical algorithms for practical problems.
● Write and implement computer programs for numerical algorithms
● Apply numerical and programming tools to solve real world problems.
Course Content Introduction to Numerical methods, Needs of Numerical methods in Financial
Field, Taylor’s Theorem and its various forms, Orders of Convergence; Big O
and small O, Sources of Errors, Solutions for nonlinear equations; Bisection
Method, Newton Raphson Method and their convergence, Interpolation
Techniques, Numerical Integration, Numerical Methods for Linear Systems;
Direct Methods, Iterative Methods, Simple Iteration, Applications in Finance
and Economics fields, MATLAB/Octave codes for the described Numerical
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Methods.
Methods of
Evaluation
● Continuous Assessments – 50%
● Final Examination – 50%
Recommended
Reading
● Hamming, R. W. (1987). Numerical Methods for Scientists and
Engineers,2nd Revised ed., Dover Publications.
● Chapra, S. C. (2011). Applied Numerical Methods with MATLAB for
Engineers and Scientists,3rd ed.,McGraw-Hill Education.
Course Code &
Title
FE 2101 Accounting II for Finance
Credit Value &
Lecture Hours
30L 2C
Prerequisite FE 1103
Objective To provide the skills to analyze the Financial performance of Companies.
Learning
Outcomes
At the end of the course, students are able to;
● Apply the basic principles of Accounting to interpret the performance of
companies
● Analyze Financial Statements of organizations for strategic decision
making
Course Content Introduction to the Principles of Accounting and Ratio Analysis , Preparing
financial statements and interpreting the relationship between the financial
statements, Analysis and communication of accounting information to
stakeholders
Methods of
Evaluation
● Continuous Assessments – 40%
● End Semester Exam – 60%
Recommended
Reading
● Wijewardena, H. (2004). Financial Accounting in Sri Lanka.
Course Code &
Title
FE 2102 Advanced Applications in Spreadsheet
Credit Value &
Lecture Hours
60P 2C
Prerequisite FE 1106
Objective To provide hands on experience to utilize the power of worksheet application.
Learning
Outcomes
The end of the course students are able to;
● Identify and implement spreadsheet formulae and solvers for real
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problems.
● Apply and implement spreadsheet programs to solve real problems.
● Write a macro programs for real problems.
Course Content Macro programing, Random functions, Worksheet programming.
Methods of
Evaluation
● End Semester Assessments – 50%
● Continuous Assessments – 50%
Recommended
Reading
● MacDonald, M. (2010). Excel 2010: Missing Manual,1st ed., O’Reilly
Media, Inc
● Walkenbach, J. (2010). Excel 2010 Bible,1st ed., John Wiley & Sons, Inc.
● Winston, W. L. (2011). Data analysis and business modeling,1st ed.,
O’Reilly Media, Inc.
Course Code &
Title
FE 2103 Financial risk Management I
Credit Value &
Lecture Hours
30L 2C
Prerequisite FE 1114
Objective To provide basic knowledge in financial risk and tools in financial risk
management.
Learning
Outcomes
The end of the course students are able to;
● Describe various types of financial risk and risk management tools.
● Define and quantify risk measures.
● Compute, model the risk and implement in spreadsheets.
Course Content Defining Financial risks, Financial market participants and their roles, Types of
Risk; Market Risk, Interest Rate Risk, Credit Risk, Operational Risk, Fixed
Income Risk, Credit risk Models, Available Tools and Utilities, Quantification of
Risk/Risk Measures, Risk management concepts, Types of Risk management
tools and their limitations, Durations and interest rate volatility, Duration
Matching, Nonlinearity and convexity risk, Vega risk, Assets and Liabilities,
Value at Risk and Computations, Volatility estimation, Modes of computation;
parametric, historical, Spreadsheet computation.
Methods of
Evaluation
● Continuous Assessments – 40%
● Final Examination – 60%
Recommended
Reading
● Allen, S. L. (2012). Financial Risk Management: A Practitioner's
Guide to Managing Market and Credit Risk, 2nd ed., Wiley.
Course Code &
Title
FE 2104 Investment Analysis I
BSc in Financial Engineering (2018 onwards)
16
Credit Value &
Lecture Hours
30L 2C
Prerequisite FE 1105
Objective To provide basic concepts of financial instruments.
Learning
Outcomes
The end of the course students are able to;
● Interpret and identify the loan repayment methods, bonds and stocks as
investment instruments.
● Apply basic quantitative methods to price the bonds and stocks.
● Apply the valuation methods to identify feasibility of the given project.
Course Content Introduction to corporate finance and related applications, Corporate Securities as
contingent claims on total firm value, The corporate firms, Goals of the corporate
firm, Financial Markets, varying interest rate valuation, Annuity valuation,
Amortization and sinking fund, Internal rate of return and its applications, Bond
valuation and analysis, stock valuation, foreign currency rate.
Methods of
Evaluation
● End Semester Exam – 60%
● Mid Semester Exam – 20%
● Continuous Assessments – 10%
● Practical Exam (Excel) – 10%
Recommended
Reading
● Kellison, S. G. (2009). The Theory of Interest, 3rd ed., McGraw-Hill
Irwin.
● Beaumont, P. H. (2004). Financial Engineering Principles: A Unified
Theory for Financial Product Analysis and Valuation. John Wiley &
Sons, Inc.
● Capinski, M., & Zastawniak, T. (2003). Mathematics for Finance: An
Introduction to Financial Engineering, Springer.
● Ross, S., Westerfield, R., & Jaffe, J. (2005), Corporate Finance,
McGraw-
Hill, Irwin.
Course Code &
Title
FE 2105 Management Science II
Credit Value &
Lecture Hours
30L, 2C
Prerequisite FE 1108
Objective To provide basic concepts of optimization tools for real problems.
Learning
Outcomes
At the end of the course students able to;
● Apply dynamic programming methods to solve real world problems.
● Use excel solver to find the Shortest path.
● Apply the optimization method to find the optimum solutions.
Course Content Introduction to Dynamic Programming, Shortest path problem, Solution to Linear
Programming problem through Dynamic Programming, capital budgeting
problem, Reliability improvement problem, Excel (or equivalent software)
solvers for problems, Classical optimization techniques for Finance and
Economics problems (including Lagrange Multipliers), Sensitivity analysis of the
problems.
BSc in Financial Engineering (2018 onwards)
17
Methods of
Evaluation ● Continuous assessment - 40%
● End Semester Exam – 60%
Recommended
Reading
● Hillier, F.S. and Lieberman, G.J. (1995). Introduction to operations
research. New York, N.Y.: McGraw-Hill.
● G. Sirivasan. (2017). Operations Research: Principles and Applications,
3rd ed., Delhi,: PHI Learning Private Limited.
Course Code &
Title FE 2106 Financial Econometrics
Credit Value &
Lecture Hours
30L 2C
Prerequisite FE 1110
Objective To provide basic econometric techniques to model financial data.
Learning
Outcomes
The end of the course students are able to;
● Identify and describe essential econometrics tools to model financial data.
● Apply the tools and interpret the results.
Course Content Scatter plots and correlations, Simple linear regression, multiple linear
regression, Coefficient of Determination, ANOVA, T-distribution and T-test, F-
distribution and F-test, Hypothesis testing on regression, Non linear models,
dummy variables, EXCEL functions for regression, cross sectional and panel
data, time series and forecasting basics, smoothing techniques, auto correlations,
EXCEL functions for time series data.
Methods of
Evaluation
● End Semester Exam – 60%
● Continuous Assessments – 40%
Recommended
Reading
● Weisberg, S. (2005). Applied Linear Regression (3rd ed.). John Wiley &
Sons, Inc.
● Brockwell, P.J., & Davis, R.A. Introduction to time series and
forecasting.
● Enders, W. (2008). Applied Econometric Time Series (2nd ed.). Wiley
India Pvt. Limited.
Course Code &
Title
FE 2107 Insurance for Business
Credit Value &
Lecture Hours
30L 2C
Prerequisite None
Objective To give students a basic background of the modern insurance system and to
appreciate the role of insurance within the wider field of Financial Services.
BSc in Financial Engineering (2018 onwards)
18
Learning
Outcomes
The end of the course students are able to;
● Identify key social and economic drives that causes different risks.
● Identify and describe the fundamental principles and practices of
insurance.
● Identify and explain how various insurance products meet specific client
needs.
Course Content Evolution of Insurance-Historical and Futuristic Overview, Purpose and need for
Insurance, Environmental-Socio economic and technological transitions and their
impact on the Insurance Industry, Historical evolution, scope, underwriting and
claims management of selected classes of Insurance:- Life, Property, Liability,
Marine, Motor, Role of insurance in the development of economy , Concept of
Insurance and Principles of Insurance, Risk and Insurance, Risk assessment and
developing new products, Pricing mechanism in the open market, Appreciation of
Actuarial Aspects, Legal Aspects, Basic Principles of law of contract and its
application to insurance contract, obligations of parties, Consumer protection and
statutory regulations related to insurance business in Sri Lanka, Dispute
resolution, Practice of Reinsurance, Issues in reinsurance in international markets,
Insurance Market, role played by the intermediates-brokers, agents, Market
Cycles.
Methods of
Evaluation
● End Semester Exam – 60%
● Continuous Assessments – 40%
Recommended
Reading
● Thoyts, R. (2010). Insurance Theory and Practice Paperback. Routledge.
● Outreville, J.F. (1998). Theory and Practice of Insurance. Springer
Science & Business Media.
Course Code &
Title
FE 2108 Investment Analysis II
Credit Value &
Lecture Hours
30L 2C
Prerequisite FE 2104
Objective To provide basic concepts of financial decision making techniques.
Learning
Outcomes
The end of the course students are able to;
● Identify and compute the impact of interest variation.
● Compute the spot rates, forward rates and identify their meaning.
● Compute the duration and convexity of the investment projects (bond)
and interpret their economical meaning.
● Apply the valuation methods to identify feasibility of the given project.
Course Content Introduction to financial analysis, pricing a bond and sensitivity of it, zero
coupon bonds and their features, par yield, spot rates, forward rates, term
structure of interest rate, yield rate, duration and convexity of the bond, fund
analysis, time weighted and time weighted rates, holding rates, Excel
computation and solvers.
Methods of
Evaluation
● End Semester Exam – 60%
● Mid Semester Exam – 20%
● Continuous Assessments – 10%
BSc in Financial Engineering (2018 onwards)
19
● Practical Exam (Excel) – 10%
Recommended
Reading
● Kellison, S. G. (2009). The Theory of Interest,3rd ed., McGraw-Hill
Irwin.
● Beaumont, P. H. (2004). Financial Engineering Principles: A Unified
Theory for Financial Product Analysis and Valuation. John Wiley &
Sons, Inc.
● Capinski, M., & Zastawniak, T. (2003). Mathematics for Finance: An
Introduction to Financial Engineering, Springer.
● Ross, S., Westerfield, R., & Jaffe, J. (2005). Corporate Finance.
McGraw-Hill, Irwin.
Course Code &
Title
FE 2109 Survival Models and Analysis
Credit Value &
Lecture Hours
30L 2C
Prerequisite FE 1110
Objective To introduce some of the fundamental ideas and issues of lifetime and time-to-
event data analysis, as used in actuarial practice.
Learning
Outcomes
The end of the course students are able to;
● Identify and describe the key features of lifetime data.
● Model the warranty period.
● Model human mortality and interpret the life table in a variety of
contexts.
● Solve problems, and especially to apply ideas learned in one context to
other contexts.
Course Content Introduction to concepts of survival modeling; censoring; survival and hazard
functions, Estimating the survivor function, present value an actuarial present
value concepts, general survival models, Models for human mortality;
Comparison of models of mortality: Binomial, Poisson and multiple-state
models, Survival distributions and Life Tables: Probability for the age-at-death,
the survival function, Time-until-death for a person age x, Curtate-future-
lifetimes, Force of Mortality, Some analytical laws of mortality, Life
expectancy.
Methods of
Evaluation
● End Semester Exam – 60%
● Continuous Assessments – 40%
Recommended
Reading
● Gerber, H. (1997). Life Insurance Mathematics, 3rd ed.,Springer-Verlag,
New York.
● Dickson, D. C. M., Hardy, M. R., & Waters, H. R. (2013). Actuarial
Mathematics for Life Contingent Risk. Cambridge University Press.
Course Code &
Title
FE 2110 Differential Equations II for Finance
BSc in Financial Engineering (2018 onwards)
20
Credit Value &
Lecture Hours
30L 2C
Prerequisite FE 1113
Objective To provide essential concepts in partial differential equations to model and solve
problems in finance.
Learning
Outcomes
The end of the course students are able to;
● Solve partial differential equations using various techniques and interpret
the solutions.
● Model finance related problems using partial differential equations and
interpret the solutions in relation to finance and economics.
Course Content Introduction to Partial Differential Equations, Problem Formulation using PDEs,
Classifications of PDEs, Parabolic Equations, Linear Parabolic Equations,
Fundamental Solution of Parabolic Equations, Applications in Finance and
Economics, Heat equation and its applications, Analytical and numerical
methods to solve Heat equation, MATLAB programing for solving the heat
equation.
Methods of
Evaluation
● Continuous Assessments – 40%
● Final Exam Computer Based - 60%
Recommended
Reading
● Basov, S. (2007). Partial Differential Equations in Economics and
Finance. Nova Publishers.
● Stanoyevitch, A. (2005). Introduction to Numerical Ordinary and
Partial Differential Equations Using MATLAB®. John Wiley & Sons,
Inc.
Course Code &
Title
FE 2111 Life Insurance Models
Credit Value &
Lecture Hours
30L 2C
Prerequisite FE 2109
Objective To introduce basic life insurance models.
Learning
Outcomes
The end of the course students are able to;
● Model the future lifetime.
● Compute the net single premium and premium for the different life
policies.
● Compute the gross premiums and analyze the feasibility.
Course Content Review of concepts of survival mode and future lifetime, Survival distributions
and Life Tables, Actuarial present value, Valuing contingent payments
annuities, pure endowment, term, endowment, whole life policies and their
characteristics, Computing net single premium and premium, Fully discrete,
Semi-continuous, Fully continuous life models.
Methods of
Evaluation
● End Semester Exam – 60%
● Continuous Assessments – 40%
Recommended
Reading
● Gerber, H. (1997). Life Insurance Mathematics (3rd ed.).
Springer-Verlag, New York.
BSc in Financial Engineering (2018 onwards)
21
● Dickson, D. C. M., Hardy, M. R., & Waters, H. R. (2013). Actuarial
Mathematics for Life Contingent Risk. Cambridge University Press.
Course Code &
Title
FE 2112 Fuzzy Modeling
Credit Value &
Lecture Hours
60P 2C
Prerequisite None
Objective To introduce basic uncertainty modeling concepts and models
Learning
Outcomes
The end of the course students are able to;
● Identify uncertainty models.
● Apply fuzzy techniques to model uncertainty events.
● Compute decisions and evaluate feasibility.
Course Content Traditional logic vs Fuzzy logic, point vs interval estimation, fuzzy numbers,
fuzzy membership functions, fuzzy rules, fuzzy applications in real world
problems, fuzzy based techniques to solve real problems.
Methods of
Evaluation
● End Semester Exam – 60%
● Continuous Assessments – 40%
Recommended
Reading James J. Buckley, Leonard J. Jowers (2006), Simulating
Continuous Fuzzy Systems, Springer-Verlag Berlin Heidelberg
Course Code &
Title
FE 2113 Financial Statement Analysis
Credit Value &
Lecture Hours
30L 2C
Prerequisite FE 2101
Objective To provide basic knowledge on financial statements and their characteristics.
Learning
Outcomes
The end of the course students are able to;
● Identify financial ratios.
● Compute the financial ratios using statements.
● Interpret and use the financial ratios for decision making process.
Course Content Introduction to Financial Statements, Types of Financial statements, Financial
statements analysis, Horizontal Analysis, Vertical Analysis, Common-Size
Statements, Trend Percentages, Ratio Analysis, Types of Ratios, Liquidity
Ratios, Equity Ratios, Profitability Tests, Market Tests, Current Ratio, Acid-test
Ratio, Accounts receivable turnover, Inventory turnover, Total assets turnover,
Return on Operating assets, Profit Margin, Return on Average Common
stockholders’ equity, Cash flow margin, Working Capital, Net Income to Net
Sales.
Methods of
Evaluation
● End Semester Exam – 60%
● Continuous Assessments – 40%
BSc in Financial Engineering (2018 onwards)
22
Recommended
Reading
● Alvarez, F. & Fridson, M. Financial Statement Analysis: A
Practitioner's Guide.
Course Code &
Title
FE 2114 Numerical Methods II for Finance
Credit Value &
Lecture Hours
60P 2C
Prerequisite FE 1113 and FE 1115
Objective To provide computer programming competencies to solve differential equations
in numerically.
Learning
Outcomes
At the end of the course, students are able to;
● Identify the numerical algorithms for differential equations models.
● Write and implement computer programs for numerical algorithms.
● Apply numerical and programming tools to solve real world problems.
Course Content Numerical Methods for Linear Systems; Direct Methods (Gaussian, Jacobi,
Gauss-Seidel), Iterative Methods, Simple Iteration, Numerical Methods for
ODEs, Euler Method, Runge-Kutta Method, Linear Multi-step Methods and
their Convergence with Applications in Finance, Numerical methods for growth
models, MATLAB Codes for described Numerical Methods.
Methods of
Evaluation
● Continuous Assessments – 50%
● Final Exam Computer Based - 50%
Recommended
Reading
● Griffiths, D. F., & Highamm, D. J. (2005). Numerical Methods for
Ordinary Differential Equations: Initial Value Problems. Springer
Science & Business Media.
● Stanoyevitch, A. (2005). Introduction to Numerical Ordinary and
Partial Differential Equations Using MATLAB®. John Wiley & Sons,
Inc.
Course Code &
Title
FE 2115 Game Theory
Credit Value &
Lecture Hours
30L 2C
Prerequisite None
Objective To provide the knowledge on decision and behavior rules.
Learning
Outcomes
The end of the course students are able to;
● Identify the characteristics of different decision models.
● Describe and compute optimality situations.
● Apply game theory models to solve finance and economic problems.
Course Content Generalized the Financial Decision Problems, Introduction to Game Theory and
its applications in Finance, Economics and other Disciplines, Various Classical
Games (Zero Sum, Battle of Sexes, Prisoner’s Dilemma) and their applications,
Types of game: Perfect/Imperfect information, Simultaneous/Sequential,
Dynamic/Stochastic, Repeat Games, Nash Equilibrium, Pareto equilibrium, Pure
and mixed Strategy, Bargaining, Sealed bid Auction, Duopoly Problem, Cournot
BSc in Financial Engineering (2018 onwards)
23
and Bertrand competition, Financial Simulation and Game Theory, Prisoners’
Dilemma game its direct applications to Economics and Finance, Entry
deterrence.
Methods of
Evaluation
● End Semester Exam – 60%
● Continuous Assessments – 40%
Recommended
Reading
● Pastine, I. & Pastine, T. (2017). Introducing Game Theory: A Graphic
Guide, Icon Books Ltd.
● Funke, C. (2007). Applying Game Theory in Finance. GRIN Verlag.
Course Code &
Title
FE 3101 Investment Analysis III
Credit Value &
Lecture Hours
30L 2C
Prerequisite FE 2108
Objective To provide advance concepts of investment analysis techniques.
Learning
Outcomes
The end of the course students are able to;
● Identify and interpret the project evaluation tools.
● Apply such methods and identify the feasibility of the given projects.
● Develop and analyze decision models to rank the projects.
Course Content Introduction to discounted cash flow analysis, NPV, IRR, Payback Period,
Discounted Payback Period, and Related Investment decision Criteria,
Incremental cash flows, Inflation and Capital Budgeting, Capital Market theory,
Returns, Risk Statistics, Cost of Capital and Capital Budgeting, Maximizing
firm value versus Maximizing Stockholder interests, Taxes, Adjusted present
value approach, Capital budgeting with estimated rate of discount, Economic
life of an asset, Determination of Economic life of an asset, Replacement and
maintenance analysis, Excel computation.
Methods of
Evaluation
● End Semester Exam – 60%
● Mid Semester Exam – 20%
● Continuous Assessments – 10%
● Practical Exam (Excel) – 10%
Recommended
Reading
● Kellison, S. G. (2009). The Theory of Interest,3rd ed., McGraw-Hill
Irwin.
● Beaumont, P. H. (2004). Financial Engineering Principles: A Unified
Theory for Financial Product Analysis and Valuation. John Wiley &
Sons, Inc.
● Capinski, M., & Zastawniak, T. (2003). Mathematics for Finance: An
Introduction to Financial Engineering, Springer.
● Ross, S., Westerfield, R., & Jaffe, J. (2005). Corporate Finance.
McGraw-Hill, Irwin.
BSc in Financial Engineering (2018 onwards)
24
Course Code &
Title
FE 3102 Financial Risk Management II
Credit Value &
Lecture Hours
30L 2C
Prerequisite FE 2103
Objective To provide advanced concepts of financial risk management.
Learning
Outcomes
The end of the course students are able to;
● Identify suitable financial instruments for risk management and their
valuation.
● Compute the risk and develop hedging strategies using instruments.
● Solve risk management problems using spreadsheets.
Course Content Types of Financial instruments and their valuations, Forwards and Futures,
Options, Risk Modeling of Financial Instruments, Stress testing and simulation,
Black Scholes Pricing, Option Greeks, Measuring credit risk and the probability
of default, Short Selling, Operational risk, Developing a hedging strategy and its
applications, Financial crises, Bubbles, Extreme Volatility, Financial Market
behavior during extreme events, Applications using spreadsheets.
Methods of
Evaluation
● Continuous Assessments – 40%
● Final Examination) – 60%
Recommended
Reading
● Allen, S. L. (2012). Financial Risk Management: A Practitioner's
Guide to Managing Market and Credit Risk (2nd ed.). Wiley.
● Overdahl, J. A., & Kolb, R. W. (2009). Financial Derivatives:
Pricing and Risk Management,1st ed., Wiley.
Course Code &
Title
FE 3103 Computational Modeling
Credit Value &
Lecture Hours
60 P 2C
Prerequisite FE 2114
Objective To provide theoretical and practical knowledge, on building and using
computational models based on soft programming techniques.
Learning
Outcomes
At the end of this course students are able to;
● Compare hard computing methods with soft computing methods and
choose the appropriate method for solving a given problem.
● Describe how Artificial Neural Network (ANN) functions. Implement
an ANN to solve classification and prediction problems using
programming languages.
● Describe how Genetic Algorithms (GA) functions. Implement a GA to
solve optimization problems using programming languages.
● Design and implement GA/ ANN hybrid systems.
● Use Monte-Carlo simulations to solve appropriate problems.
BSc in Financial Engineering (2018 onwards)
25
Course Content Introduction to Artificial Neural Networks (ANN), Single Layer Networks,
Multilayer Networks. Different learning rules. Advantages and limitations of
ANN. Preprocessing and post processing of data. Using ANN to solve real
world problems.
Introduction to Genetic Algorithms (GA) with advantages, disadvantages and
limitations. Encoding data to genes. Cross overs, mutations and other
generation creation techniques. Different selection methods. Solving TSP and
knapsack problems. Using ML to implement GA to solve problems.
Different hybrid mechanism. Implement a GA ANN hybrid. Advantages of a
hybrid.
Introduction to Monte Carlo simulations (MC), its applications. Using ML to
implement a MC to model real world problems.
Methods of
Evaluation
● End Examination - 50 %
● Continuous Assignments - 50 %
Recommended
Reading
● Priddy, K. L., & Keller, P. E. (2005). Artificial Neural Networks: An
Introduction. SPIE Publications.
● Michalewicz, Z. (1996). Genetic Algorithms + Data Structures =
Evolution Programs,3rd ed.,Springer-Verlag Berlin Heidelberg.
● Haupt, R. L., & Haupt, S. E. (2004). Practical Genetic Algorithms,
2nd ed., Wiley-Interscience.
● Thomopoulos, N. T. (2013). Essentials of Monte Carlo Simulation.
Springer-Verlag, New York.
Course Code &
Title
FE 3104 – Management Science III
Credit Value &
Lecture Hours
30 L 2C
Prerequisite FE 2105
Objectives To provide basic concepts of Queuing Theory and Quadratic Programming.
Learning
Outcomes
The end of the course students are able to;
● Develop a queuing model for real problem and compute steady-state
measures of performance of single and multi-server models.
● Develop a quadratic programming model for real problems.
● Apply the KKT methods for solving quadratic programming problems.
Course Content Operational techniques for Finance and Economics, Queuing theory and its
applications to Finance and Banking sectors, Introduction to Quadratic
Programming, Applications of Quadratic Programming in Finance and
Economics, Problem formulation, Constrained quadratic programming
problems, Equality constrained quadratic programming, KKT matrix and
reduced Hessian, Global minimizer, Direct solution of the KKT system and
various methods to solve KKT system.
Methods of
Evaluation
● Continuous Assessments – 40%
● End Semester Exam – 60%
Recommended
Reading
● Hillier, F. S., & Lieberman, G. L. (2009). Introduction to Operations
Research,9th ed., McGraw-Hill, New York.
● Taha, H. A. (2009). Operations Research, 8th ed., Pearson Prentice
Hall.
BSc in Financial Engineering (2018 onwards)
26
Course Code &
Title
FE 3105 Stochastic Calculus for Finance
Credit Value &
Lecture Hours
30L 2C
Prerequisite FE 1110
Objective To provide essential concepts in stochastic calculus for option pricing and
related problems in finance.
Learning
Outcomes
End of the course students able to;
● Calculate option prices based on Binomial tree and other techniques in
stochastic calculus.
● Simulate the stock prices using Brownian motion and interpret outcomes.
Course Content Introduction to Stochastic Processes and their applications, Binomial Tree,
Normal and Lognormal random variables, Discrete and Continuous Time
Martingales, Brownian Motion, Model of Fair Game, Introduction to Stochastic
Differential Equations and their application in Finance, Introduction to Wiener
Process and its applications in Finance.
Methods of
Evaluation
● Continuous assessment - 30%
● Practical test - 20 %
● End of semester written examination - 50%
Recommended
Reading
● Hull, J. C. (2005). Futures and other Derivatives, 6th ed., Prentice Hall.
Course Code &
Title
FE 3106 Banking and International Finance
Credit Value &
Lecture Hours
30L 2C
Prerequisite None
Objective To provide practical experiences in banking industry.
Learning
Outcomes
End of the course students able to;
● Identify the banking systems and main operations.
● Describe the banking operations.
● Use banking operations for financial activities.
Course Content Introduction to Banking systems, Bank Liquidity management, Bank Asset and
Liability Management, Banking history, Banking regulations, The Savings and
Loan Crisis, The Supply of Money; Multiple Deposit Creation, Determination of
the Money Supply, Depositor and Bank behavior, Monetary base, Exchange
Rates, Foreign Exchange Markets, International Finance, Transactions motive,
Speculative motive, How does Money affect the Economy.
Methods of
Evaluation
● Continuous assessment - 60%
● End of semester written examination - 40%
BSc in Financial Engineering (2018 onwards)
27
Recommended
Reading
● Szulczyk, K. R. (2013). Money, Banking, and International Finance, 2nd
ed., CreateSpace Independent Publishing Platform.
● Sercu, P. (2009). International Finance: Theory into Practice. Princeton
University Press.
Course Code &
Title
FE 3107 Portfolio Management
Credit Value &
Lecture Hours
30L, 2C
Prerequisite FE 3102
Objective To provide the essential concepts and knowledge on financial portfolios to
construct and optimize a simple portfolio.
Learning
Outcomes
At the end of this course a student should be able to;
● Describe the concept of return and risk and to compute return related
ratios and interpret the outcomes.
● Compute portfolio return and volatility.
● Use programing language to construct an optimal portfolio with respect
to constraints and interpret the outcomes.
Course Content Introduction to Financial Portfolio, Holding Period of Return and Yield,
Investment Policy Statement: construction and management, Portfolio Returns
and Risk Measures, Sharp Ratio, Information Ratio and other Extended Risk
Measures, Minimum variance frontier and its applications, changes with
respect to utility, Portfolio proportion in two dimensions, Modeling Returns,
Criterion for Portfolio Construction and Asset Allocation, Portfolio
Construction and Optimization using programing languages with constraints.
Methods of
Evaluation
Continuous Assessment
● Classroom test - 20%
● Group Case Study - 10%
● Computer Based Classroom Test (MATLAB) – 20%
● End Semester classroom test – 20%
● End Semester online test – 30%
Recommended
Reading
● Reilly, F. K., & Brown, K. C. (2002). Investment Analysis and Portfolio
Management, 7th ed., Cengage Learning.
● Kim, D., & Chincarini, L. B. (2010). Quantitative Equity Portfolio
Management: An Active Approach to Portfolio Construction and
Management, 1st ed., McGraw-Hill Education.
BSc in Financial Engineering (2018 onwards)
28
Course Code &
Title
FE 3108 E-Commerce
Credit Value &
Lecture Hours
30L 2C
Prerequisite None
Objective To provide a fundamental competency of the different types and key components
on business models in the New Economy.
Learning
Outcomes
At the end of this course a student should be able to;
● Explain the components and roles of the Electronic Commerce
environment.
● Describe E-Commerce payment systems.
● Explain the client/server infrastructure that supports electronic commerce
and to explain basic electronic commerce functions.
Course Content Defining E-commerce, The Development of E-commerce, E-commerce
Marketing, E-commerce Security Issues, E-commerce Security Requirements, E-
commerce Legal Considerations, International Legal Considerations in E-
commerce, E-commerce Implementation Costs, Online Auctions Including EBay
and other Electronic Payment Systems, Global, Social, and Other Issues in e-
Commerce.
Methods of
Evaluation
● Continuous Assessment - 40%
● Final Examination - 60%
Recommended
Reading
● Reynolds, J. (2004). The complete e-commerce book, 2nd ed., CRC
Press.
● Traver, C. G., & Laudon, K. C. (2009). E-commerce: Business,
Technology, Society, 5th ed., Prentice Hall.
● Phillips, J. (2016). Ecommerce Analytics: Analyze and Improve the
Impact of Your Digital Strategy, 1st ed., Pearson FT Press.
Course Code &
Title
FE 3109 Professional Development in Finance
Credit Value &
Lecture Hours
60P 2C
Prerequisite None
Objective Provide writing, oral, and collaborative skills necessary for future business,
professional and academic positions.
Learning
Outcomes
The end of the course students are able to;
● Deliver effective skills in presentations that may require oral
presentations in Finance.
● Participate effectively in groups emphasizing critical and reflective
thinking.
● Write an academic and professional research report.
Course Content Research Reports and proposals: Develop accuracy (in grammar) and style (so
that messages are effective, efficient, and ethical), Academic writing,
Referencing, Paraphrasing and Summarizing, Interpersonal skills: listening,
questioning and feedback, Oral communication (To deliver oral presentations),
Public communication, Intercultural Communication, Organizational
BSc in Financial Engineering (2018 onwards)
29
communication, Team communication and Communicating in meetings.
Methods of
Evaluation
● Participation 10%
● Written Communication 10%
● Oral communication- Individual Presentation 20%
● A three page long business research report or proposal 20%
● Oral Communication (plus email evaluation) 20%
● A group/individual presentation 20%
Recommended
Reading
● Eunson, B. (2012). Communication in the 21st Century, 3rd ed., Milton,
Old, John Wiley and Sons Australia, ISBN 9780730302636.
Course Code &
Title
FE 3110 Case Studies in Management
Credit Value &
Lecture Hours
60P 2C
Prerequisite None
Objective Analyzing Management case studies
Learning
Outcomes
The end of the course students are able to;
● Describe Management theories for organizational problems.
● Analyze organizational problems and interpret solutions.
Course Content Introduction to the case study method, Case study applications for
organizational & managerial issues, Introduction to Human resource
management, job analysis, selection process, performance evaluation, training &
development process, Case studies in Human Resource Management,
Introduction to change management process, forces of change, Barriers in
change management, Case studies in Change management, Introduction to
Marketing management. Marketing environment, Segmentation, Marketing mix.
Case studies in Marketing Management. Introduction to Leadership. Leadership
theories, Communication model, Motivation theories. Case studies in
Leadership Management.
Methods of
Evaluation
Continuous assessment: 100%
Recommended
Reading
● Natarajan, B., & Nagarajan, S. K. (2007). Developing Analytical Skills:
Case Studies in Management. Shroff Publishers and Distributors Pvt.
Ltd.
● Ellet, W. (2007). The case Study Handbook: How to Read, Discuss and
write persuasively about cases. Harvard business school press.
● Kulkarni, J. A., Pachpande, A., & Pachpande, S. (2011). Case studies in
Management. Dorling Kindersley
BSc in Financial Engineering (2018 onwards)
30
Course Code &
Title
FE 3111 Professional Financial Practice
Credit Value &
Lecture Hours
60P 2C
Prerequisite FE 3110 and FE 3109
O Objective To provide applied analytical financial thinking skills by finance case studies.
Learning
Outcomes
The end of the course students are able to;
● Apply analytical methods to interpret the solutions for various
stakeholders.
● Develop team building and interpersonal communication through
challenging finance practice.
● Apply and strategize different tasks to achieve investment goals.
Course Content Application of knowledge learnt in Capital budgeting (NPV, IRR), Financial
Statement Analysis (Income statements, Balance sheet and Cash flow
statements) and Ratio Analysis, Industry Analysis (SWOT and PESTAL
Analysis).
Method of
Evaluation
C Continuous Assessment – 100%
Course Code &
Title
FE 3112 Project
Credit Value &
Lecture Hours
180P, 6C
Prerequisite None
Objective Provide an opportunity to utilize learnt competencies
Learning
Outcomes
Identify and model real world problems and interpret the result
Communicate their findings and interpret through the learnt concepts and
theories
Course Content Students are assigned problems and they are expected to work independently
for 6 month duration and present their work based on: Proposal, Literature
review, Methodology, Basic results and final results. At the end of the 6
months the students are expected to submit the report. Students will be
evaluated through a VIVA.
Methods of
Evaluation
Continuous progress 40%
Report : 30%
VIVA : 30%
Course Code & FE 3113 Data Analysis
BSc in Financial Engineering (2018 onwards)
31
Title
Credit Value &
Lecture Hours
60P 2C
Prerequisite FE 2106
Objective Provide an opportunity to use data analytics to create actionable
recommendations.
Learning
Outcomes
The end of the course students are able to :
● Demonstrate data analysis functions and reporting.
● Analyze and adapt data to feed business decisions.
Course Content Organizing and summarizing data, Summarizing relationship between
variables, Simple linear Regression and Correlation analysis, Multiple
Regression Analysis, Analysis of variance, Analysis of categorical Data, Time
series models and forecasting, case studies in finance and economics
Methods of
Evaluation
● Group Assignment- 50%
● Individual Assignment- 50%
Recommended
Reading
● Kitchens, L. J. (2003). Basic Statistics and Data Analysis. Duxbury
Press.
● Peck, R., Olsen, C., & Devore, J. L. (2016). Introduction to Statistics
and Data Analysis, Cengage Learning; Brooks Cole, Cengag.
● MacFarland, T. W. (2014), Introduction to Data Analysis and
Graphical Presentation in Biostatistics with R. Springer.