This programme integrates mathematics, statistics, finance, and economics to prepare students for careers in risk assessment and financial modelling. It equips learners with quantitative and analytical skills for valuing uncertain future events in insurance, pensions, and investment contexts. Graduates are well-positioned for professional actuarial certification and employment in insurance companies, banks, consultancies, and government agencies. The programme fosters innovation and practical skills aligned with global actuarial standards and local industry needs.

Duration:	4 years
Minimum Credit Load:	480
Maximum Credit Load: Actual Credit Load:	540 516
Maximum MBKS Credit Load:	412
ZNQF Level	8

1.   INTRODUCTION

These regulations shall be read in conjunction with the General Regulations for Undergraduate Programmes and the Faculty of Science and Technology Regulations.

2.   Purpose of the programme

      The purpose of the programme is to equip students

•       with actuarial and economic concepts, principles and processes in the areas of Science, Engineering, Industry and Commerce.
•       with a background for post-graduate studies in actuarial and related areas.
•       with skills to design and implement computer programming tasks.
•       with a sound knowledge, of actuarial and of business studies which they can apply across a broad spectrum of areas.
•       for teaching secondary school mathematics and actuarial courses at tertiary institutions.
•       for conducting research at whatever level.

•    For all entry pathways candidates must have at least five Ordinary Level subjects/ National
•    Foundation Certificates including English Language, Mathematics and a Science subject at  
•  
•   grade C or better.
  

  Normal Entry:	At least 5 Ordinary level subjects/ National Foundation Certificates inclusive of Mathematics and English Language AND they should have passed “A” Level Mathematics and any other science or commercial subject or their recognized equivalents.
  Special Entry:	National Certificate, National Diploma or Higher National Diploma in relevant fields.
  Mature Entry:	Refer to Section 3.3 of the General Regulations.

Areas of Study:  Actuarial Science, Mathematics, Statistics, Economics, Operational Research

Specialist Focus:

Life Insurance, Health Insurance, Pensions, Investment, General Insurance and Enterprise Risk Management.

Distinctive Features: The programme is tailored to provide students with technical and analytical actuarial skills.

Orientation:

Teaching and learning are professionally oriented and focused on application of actuarial skills to solve real world problems.

 Career Opportunities and Further Education

5.1 Career Opportunities

•       Insurance: investigating, analysing and explaining a wide range of numerical information to create and price polices, or to ensure they have sufficient funds to cover claims.
•       Pensions: designing and advising on company pension schemes.
•       Investments: involved in research and on the pricing and management of investments.
•       Banking: calculating and quantifying an array of risks faced by these institutions such as the inability of some borrowers to repay their debt, or the risk of a fall in financial markets.
•       Healthcare: investigating, analysing and explaining a wide range of health and medical information to price contributions to medical schemes or assess the impact to the industry of changes in regulation.
•       Risk management: assisting businesses to better understand the multiple risks they face in a holistic and comprehensive manner, as well as provide assistance and guidance in terms of how to understand their impact and how they can best be managed.
•       Consultancy: Actuaries in administrative positions have to explain technical matters to executives, government officials, shareholders, policyholders.

5.2 Further Education

   Graduates could continue to an MSc in Applied Actuarial Science, an MSc in  

   Mathematics and its applications or an MSc in Statistics or an actuarial trainee analyst or

  a graduate management trainee risk analyst and a trainee-chartered accountant.

Program delivery Teaching and Learning Methods: Lectures, tutorials, practical exercises, group work, work    related learning (WRL) / Industrial Attachment report, mini WRL research project and individual independent study.                                                                                               7.   LEARNING OUTCOMES     Upon successful completion of the programme, a graduate will be able to:
·       Apply Statistics and Mathematics to solve real life problems encountered in Actuarial         Science. ·       Use several of the technical tools, computer languages or software packages used by   actuaries. ·       Demonstrate mastery of data analysis and statistical concepts of Actuarial Science. ·       Critically analyze statistics and mathematics related to Actuarial Science in journal articles. ·       Write technical reports and make technical presentations containing statistical and actuarial results.
8.  ASSESSMENT: Assignments and tests will be given for each module that a student takes. The continuous assessment mark C = 0.25 (assignment average) + 0.75 (test average). For each module a student will write a three-hour examination at the end of the semester and the final mark for each module is F = 0.4C + 0.6E, where E is the examination mark. Other: a) Research Project is assessed on the basis of the written research project (75%), oral presentation (15%) and student conduct in the laboratory (10%). b) WRL/Industrial Attachment is assessed based on WRL/Industrial Attachment report (30%), assessment by work supervisor (50%), and assessment by Academic supervisor 20%).
9. FAILURE TO SATISFY EXAMINERS   Refer to section 9 of the General Regulations. 10. PROVISION FOR PROGRESSION    Refer to Section 7 of the Faculty regulations.

11. WORK RELATED LEARNING GENERAL GUIDELINES

                   Refer to Section 10.2 of the General Regulations.

12.   GRADING AND DEGREE CLASSIFICATION

       Refer to Section 5 of the General Regulations.

13.   DEGREE WEIGHTING

                Refer to Section 11 of the Faculty Regulations.

Level 1.1

HMAT131* Calculus 1                                                                                     12

HMAT132* Linear Mathematics 1                                                           12

HACS111* Introduction to Actuarial Methods, Statistics and Applications 12

HSTA133* Probability 1                                                                                  12

CS131* Communication Skills                                                                            12

HCSCI132 Principles of Programming languages                                                12

Level 1.2

HSTA107* Statistical Inference 1                                                                       12

HACS112* Economic Principles for Actuaries                                                 12

HACS113* Accounting   and Finance for Actuaries                                     12

HSTA105* Regression and ANOVA I                                                                12

HSTA104* Statistical Computing                                                                        12                   

Total number of credits                                                                                         132                   

Level 2.1

HACS211* Corporate Finance 1                                                                        12

HACS212* Mathematical Risk Theory                                                              12

HACS238* Econometrics                                                                                    12

HMAT231* Ordinary Differential equations                                                            12

GS231* Gender Studies                                                                                       12

HACS213 Methods of Actuarial Investigations                                                12

 

Level 2.2

HACS214* Corporate Finance II                                                                  12

HACS 215 Life Insurance Mathematics                                                                 12

HSTA237* Time Series Analysis                                                              12

HACS216  Macro Economics                                                                                      12

TCNP201* Technoprenuership                                                                       12

 

Total number of credits                                                                                         132                                                                               

Level 3 Semester 1 and 2

Module   Description                                                                                  Credits

HACS331*   Work related Learning I                                                           40       

HACS332*   Work related Learning II                                                              80

 

Total number of credits                                                                                         120

Level 4.1

HMAT433*Partial Differential Equations and Fourier Series                    12

HACS411* Computational Finance                                                                       12

HACS412*  Life Contingencies                                                                           12

HACS413*  Financial Economics                                                                       12

HACS414*   Health Indicators                                                                                   12

HACS415*  Pensions and Benefits Insurance                                               12

 

Level 4.2

HACS416*   Financial Engineering                                                                    12

HACS417*   Investment and Asset Liability Management                              12

HSTA410*   Stochastic Modelling in Insurance and Finance                          12

HSTA412* Survival Models                                                                             12

HACS470*    Dissertation                                                                                    36

Total number of credits                                                                                         132

 MODULE SYNOPSES

HMAT 131: CALCULUS 1  
Limit of functions. One-sided and infinite limits. Continuity. Differentiation. Definition, basic properties. Rolle’s Theorem, mean value theorem, Cauchy’s mean value theorem. Leibniz’ rule. Applications. Taylor series. Integration, Definite integrals. Antiderivatives. Fundamental theorem of calculus. Improper integrals. Gamma and Beta functions. Definition of natural       logarithm as integral of 1/x and exponential as inverse. Area, volume of revolution, arc length, surface area. Parametric equations. Arc length, surface area. Polar coordinates. Graph sketching. Area in polar coordinates. Complex numbers. Algebra of complex numbers. De Moivre’s theorem, Exponential form.

     HMAT 132: LINEAR MATHEMATICS I

Complex numbers: geometric representation, algebra. De Moivres theorem polynomials and 

roots of polynomial equations. Matrices and determinants: algebra of matrices, inverses, 

   definition and manipulation of determinants, solutions of simultaneous linear equations,  

   applications to geometry and vectors. Differential equations: separable, homogeneous, exact, 

   integrating factors, linear equation with constant coefficients.

HACS 111: INTRODUCTION TO ACTUARIAL METHODS, STATISTICS AND APPLICATIONS.

Elementary mathematics, Statistics and multistate models. Principles of Mathematics of Finance, life contingencies, risk assessment and management; practice of investment, life insurance, general insurance and retirement provision and current topics.  Addressing questions concerning professionalism and what is actuary. Graphical techniques. Kinds of measures of central tendency. Measures of variability. Empirical distributions. Moments. Skewness and Kurtosis. Applications. Indicators. Contingency Tables. Introduction to Time Series trends. Sampling. Introduction to estimation procedures: Judgmental method and Method of moments. Introduction to Hypothesis testing. Ideas about non-parametric statistics. Chi-square contingency methods, Goodness of fit, Q-Q plots, using applications in agricultural and health statistics.

HSTA133: PROBABILITY THEORY I

Axiomatic probability, sets and events, sample space, conditional probability, Independence, laws discrete and continuous random variables, probability density functions, mean, variance, expectation. Independence, Chebyshev’s inequality, moments and moment generating functions. Common Discrete Distributions, Uniform, Bernoulli and Binomial, multinomial, hypergeometric, Poisson, Geometric and negative binomial. Use of tables. Common Continuous Distributions: Uniform, Normal, Exponential, gamma, beta.  Joint Probability Distributions. Conditional and marginal distribution, expectation, covariance and correlation. Approximations, Law of large numbers, Central limit Theorem, Normal approximation to Binomial, Poisson, etc.

HCSCI132 PRINCIPLES OF PROGRAMMING LANGUAGES

This module examines the concepts and structures governing the design and implementation of programming languages. It presents an introduction to the concepts behind compliers and runtime representations of programming languages; features of programming languages supporting abstraction and polymorphism; and the procedural, functional, object-oriented, and concurrent programming paradigms. Programs are required in languages illustrating each of these paradigms.

HSTA107: STATISTICAL INFRENCE 1

Deductive inference, population and sample concepts as the basis of statistical inference, parameters and statistics, review of probability theory. Central Limit Theorem, Chi-square, student-t and F distributions, distribution of min and max. Estimation: methods of estimation, properties of estimators and their sampling distributions. Interval estimation. and Hypothesis testing.

HACS112: ECONOMIC PRINCIPLES FOR ACTUARIES

Economics as a science, the scope of economics.  Introduction to microeconomics.  Demand and supply analysis, effects of controls on prices and supply; elasticity of demand and supply, production factors, cost analysis.  Utility theory and consumer behaviour.  Analysis of insurance problems in terms of utility.  Market forms and income distribution, general equilibrium theory. The theory of firms.

HACS113 ACCOUNTING AND FINANCE FOR ACTUARIES

This module aims to give students a broad understanding of the theoretical Framework of Accounting, and Finance; procedures for limited liability companies and partnerships. Basic understanding of the use of accounting and financial information for Actuarial decision making purposes and working knowledge of selected International Financial Reporting Standards.

HSTA105: REGRESSION AND ANALYSIS OF VARIANCE 1

Correlation and regression, scatterplots, correlation matrix. Method of least squares, associated lines, assumptions underlying regression. Checking validity of assumptions. Residuals and transformations. Outliers. Pearson’s and Spearman’s correlation coefficients, predictions. Regression in terms of sums of squares and sums of products. Estimation and testing, t and F-tests. Multiple linear regression: linear equations and matrices. Matrices in simple and multiple linear regression. Testing and inference in multiple linear regression using matrices. Partial correlation. Analysis of variance (ANOVA). Assumptions underlying ANOVA. One-way, balanced design ANOVA.

HSTA134: STATISTICAL COMPUTING I

Introduction to use of statistical software, R, Python, Stata, SAS. Use of these software for data entry, data management and analysis. Interpretation of analysis results and statistical report writing.

HACS211: CORPORATE FINANCE I

The aim of the module is to identify the objective that corporate finance managers pursue or ought to pursue to satisfy the needs of corporate stakeholders and to develop, in students, concepts and corporate analytical tools that will enable them to meet this objective. To this end, the course will cover the following critical areas: Goals of a firm and the agency theory; Time value concepts and valuation of bonds and shares; Capital Budgeting under certainty; Operating and financial leverage; Introduction to portfolio theory and capital asset pricing; the stock market and other sources of long-term capital; innovations in corporate finance.

hacs212: mathematical Risk theory

Classical approaches to risk include the insurance principle and the risk-reward trade off. Risk models, review of probability, Bachelier and Lundburg models of investment and loss aggregation. Fallacy of time diversification and its generalization. Loss distributions, geometric and Brownian motion and the compound Poisson process. Modelling of individual losses which arise in a loss aggregation process. Distributions for modelling size loss; statistical techniques for fitting data. Credibility theory. Economic rationale for insurance, problems of adverse selection and moral hazard. Utility theory; ruin theory. Capital asset pricing model, Black-Scholes option pricing model. Application of risk theory. To provide an understanding of the mathematical risk theory used in practice in non-life actuarial depts of insurance firms, to provide an introduction to mathematical methods for managing the risk in insurance and finance (calculation of risk measures/quantities), to develop skills of calculating the ruin probability and the total claim amount distribution in some non ‐ life actuarial risk models with applications to insurance industry.

HACS238: ECONOMETRICS

Role of Econometrics in Zimbabwe. Review of general linear model. Linear restrictions, Generalized least squares, GLS estimator, heteroscedasticity, pure and mixed estimation, group observations and grouping of equations. Autocorrelation. Heteroscedasticity. Multicollinearity. Stochastic regressors. Simultaneous equations systems. Restrictions on structural parameters. Two stage and three stage least squares.

HMAT231 ORDINARY DIFFERENTIAL EQUATIONS

Modelling with first order ODEs in population dynamics, and second order ODEs (mass-spring systems, RLC circuits). Methods of undetermined coefficients, reduction of order and method of variation of parameters. Existence and uniqueness of solutions, revision of continuous functions and Lipschitz conditions. Series solutions of ODEs, solutions near ordinary and singular points. Systems of linear first order ODEs, solution and stability. Differential equations of special functions. Laplace transforms and inverse Laplace transforms, applications to solving IVPs, Heaviside and Dirac functions.

Application: Use the practical big data for differential equations such as simple chemical conversion problems, growth of population problems, price of commodities models, Newton’s law of cooling problems, and other physical problems.

HACS213 METHODS OF ACTUARIAL INVESTIGATIONS 

The aim of the module is for students to upon completion understand regulations, concepts in the management of business activities of financial institutions and programmes including management of the various types of   risks faced. They must know about:

1.   The actuarial profession: statutory role of actuaries, Actuarial profession and the Board of Actuarial   Standards. Control Cycle and Risk Management Control cycle.
2.   Stakeholders and their needs: Actuaries clients and needs both public and private, effect of advice, client   information, providers of benefits and contingents.
3.   General environment: Risk environment: risk management process for business, risk classification, systematic and diversifiable   risk, credit risk, liquidity risk, market risk, operational risk, business risk, risk acceptance, rejection, portfolio approach, transfer of risk, pooling risk etc.

•       Regulatory environment: Principles and aims of prudential and market

conduct regulatory regimes, information asymmetry, certain features of financial contracts, implications of requirements.

•       External environment: Legislation – state benefits , state benefits, tax, accounting standards, corporate government, risk  management, commercial requirements, changing cultural and social trends, demographic, environmental issues, international practice and technological changes.
•       Investment environment: cash-flows of simple financial arrangements, principal investment assets, markets, returns on equities, bonds, cash and price.
•       Capital requirements: main providers of benefits on contingent events,

regulatory environment for provisioning and capital requirements, measures of need etc.

•       Specifying the problem: contract design, project planning and management, data requirements, risk management,
•       Solution of problems: modelling, assumptions settings, expenses, developing the cost and price, investment management, provisioning, relationship between assets and liabilities
•       Living with the solution: maintaining profitability, determining expected results, asset management,

Capital management, surplus management, insolvency and closure, options and guarantees, monitoring.

HACS214: CORPORATE FINANCE II
The aim of the module is to develop further, in students, concepts and corporate financial analytical tools. The areas covered will include the following: Introduction to capital structure theory and practice; Cost of capital and valuation; Introduction to capital budgeting under uncertainty; Dividend policy theory and practice; corporate working capital management; and innovations in corporate finance.

HACS215 LIFE INSURANCE MATHEMATICS

Actuarial science is the discipline that assesses the impact of risks. The aim of this module is to provide solid grounding and quantitative tools of actuarial science pertaining to individuals. This module develops skills of calculating the premium for a certain life insurance contract and analyses insurance problems adequately. The module also explains the concept of reserve for insurances and annuities contracts and analyses the annual loss or profit in different types of policies. This module can contribute to getting a CM1 exemption by The Institute and Faculty of Actuaries.

HSTA237: TIME SERIES ANALYSIS

Time series models, estimation and elimination of trend and seasonal variation. Tests of randomness and normality. Introduction to projects. Model building strategy. Variance and covariance of linear combinations. Time series as a stochastic process, stationary stochastic process, white noise, and random walk. Variance of sample mean estimation of trends and seasonal variation. Sample ACP. Variance of sample autocorrelation and corresponding significance test for zero autocorrelation. General linear process. Auto-covariance generating function. Moving average process. Invertibility. Autoregressive processes. Yule-Walker equations. Solution of difference equations. AR(1) and AR(2) processes: stationarity conditions. ARMA (1, 1) process. General ARMA(p, q) process. ARIMA models for non-stationary processes: IMA(1,1), AR(1,1) IMA(2,2) models. Log transformation to stationarity.  Identification of ARIMA models. Var (Z) for stationary processes. Partial ACF and applications to AR(1), AR(2) and MA(1) models. Parameter estimation: method of moments, least squares, and maximum likelihood. Properties of parameter estimators. Goodness of fit: Box Pierce statistics, over-fitting, autocorrelation of residuals. Forecasting: minimum mean measure square error forecast; forecast errors. Applications to ARMA and ARIMA processes. MA(1)12, AR(1) 12, ARMA(1,1) 12 models. Multiplicative seasonal ARMA(p, q) x (P,Q)s model. Introduction to the frequency domain. Periodogram and spectral analysis.

HACS 216: MACRO ECONOMICS

Introduction to Macro Economics and the role of government in Economics, public sector, finance and taxation.  National Income measures; the circular flow of income; the multiplier and accelerator; aggregate demand and supply.  Government fiscal policy and its effects. Government monetary policy and its effects.  The money supply and credit creation by banking systems.  The major factors affecting unemployment, inflation, economic growth.  Monetarist and Keynesian approaches.  International trade, exchange rates and the balance of payments.

HMAT233 INTRODUCTION TO PARTIAL DIFFERENTIAL EQUATIONS (PDEs) AND FOURIER SERIES

Second Order PDE’s and Method of Separation of Variables derivation of the wave and diffusion equations, solutions of second order equations, initial and boundary conditions, solution of the wave equation, Laplace’s equation, wave equation and the heat flow equation. Parabolic Partial Differential Equations- equation for time-dependent heat flow, explicit method, Crank-Nicolson method, the Theta method, parabolic equations in Two or Three dimensions. Hyperbolic Partial Differential Equations, wave equation. Introduction to solution of PDEs using finite differences and finite elements. Solution procedures: elliptic equations — Green functions, conformal mapping; hyperbolic equations — generalized d’Alembert solution, spherical means, method of descent; transform methods — Fourier, multiple Fourier, Laplace, Hankel (for all three types of partial differential equations); Duhamel’s method for inhomogeneous hyperbolic and parabolic equations.

 

HACS 411: COMPUTATIONAL FINANCE

Theory of interest rates: simple interest, compound interest, nominal rates of interest, accumulation factors, force of interest, present values, Stoodley’s formula for the force of interest, present values of cash flows. Basic compound interest functions: the equation of value and yield of a transaction, annuities certain, present values and accumulations, deferred annuities, continuously payable

annuities, the general loan schedule, the loan schedule for a level annuity. Nominal rates of interest: annuities payable , annuities payable , present values and accumulations, annuities  payable at intervals of time r, where r>1, the loan schedule for a pannuity. Discounted cash flow: Net cash   flows, Net present values and yields, comparison of two investment projects, different interest rates for lending and borrowing, effects of inflation, the yield of a fund, measurement of investment performance. Capital redemption policies: Introduction to premium calculations, policy values, policy values when premiums are payable p, surrender values, paid up policy values and policy

alterations, variations in interest rates, Stoodley’s logistic model for the force of interest, reinvestment rates. Application: Use of practical big data in the financial sector.

HACS412: LIFE CONTIGENCIES

Multiple life models; joint life, last survivor, contingent insurance:- values of premiums for multiple life annuities and assurances and reversionary annuities and compound statuses. Multiple decrement models: disability, withdrawal, retirement etc. and reserving models for life insurance. The control cycle. Introduction to the stochastic approach to life and other contingencies.

HACS 413: FINANCIAL ECONOMICS

This course aims at the development of the necessary skills to construct asset liability models and to value financial derivatives. These skills are also required to communicate with other financial professionals and to critically evaluate modern financial theories. Measures of investment risk: variance of return, downside semi-variance, shortfall probabilities, value at risk (VaR)/Tail VaR, investor’s utility function, comparison of investment opportunities, returns and thickness of tails influence on risk, mean-variance portfolio theory, optimum portfolio, variance covariance of returns of individual assets using the mean-variance theory, diversification. Single and Multifactor models of asset returns: macroeconomic models, fundamental models, statistical factor models, single index model of asset returns, diversifiable and non-diversifiable risk, different types of multifactor models, perform calculations using these types of models.  Asset pricing Models: principal results, assumptions, limitations of such models.  Especially, Sharpe-Lintner-Mossin Capital Asset Pricing Model (CAPM), Ross Arbitrage Pricing theory. Model (APT). Perform calculations of CAPM and discuss theory to overcome limitations of these procedures. Discuss the various forms of the Efficient Markets Hypothesis looking at evidence for and against and consequences for investment management. Stochastic Models: security prices given different models like; log-normal , auto-regressive models and Wilkie models,  justification, alternatives to these models, simple calculations involving  these models, use stochastic models especially Brownian Motion. Estimating parameters of Asset pricing models in view of: data availability, data errors, outliers, stationary time series and the role of economic judgement.

HACS 414: HEALTH INDICATORS

This course aims to help students at applying the principles of actuarial planning and control needed in health and care matters. Principal terms in health care, types of contracts: critical illness, income protection, long term care insurance, hospital cash, major medical expenses, private medical insurance, group and individual covers. Operating environments in health and care products: propensity to purchase/sell meeting customer needs, methods of sell, remuneration of sale  types of expenses, commissions, inflation effects, professional guidance constraints/ opportunities, IFA in group risks, role of the state, applying  actuarial techniques, nature of risks facing insurer, managing risks in insurance and reinsurance, principal modelling techniques, assumptions, methodology, supervisory reporting, business planning in health care.

HACS 415: PENSIONS AND BENEFITS

Principles of pension funds. Mathematical models for: retirement income, retiree medical benefits, disability benefits and survivor benefits. Computer applications, simulation. Guarantees and options. Principles of pension valuation: actuarial cost methods, asset valuation methods, actuarial assumptions, gain and loss analysis.

HACS416: FINANCIAL ENGINEERING

The primary objective of financial engineering is to optimize financial outcomes by designing sophisticated financial products and strategies that enable investors to manage risk, maximize returns, and achieve their financial goals. Financial engineers work with insurance companies, asset management firms, hedge funds, and banks. Within these companies, financial engineers work in proprietary trading, risk management, portfolio management, derivatives and options pricing, structured products, and corporate finance departments. It entails:

•       The use of mathematical techniques to solve financial problems.
•       The test and issue new investment tools and methods of analysis.
•       work with insurance companies, asset management firms, hedge funds, and banks.
•       Led to an explosion in derivatives trading and speculation in the financial markets.
•       It has revolutionized financial markets, but it also played a role in the 2008 financial crisis.

Types of Financial Engineering: Derivatives Trading and speculation

Criticism of Financial Engineering

HACS417: INVESTMENT AND ASSET MANAGEMENT   
Covers part of subject (CA1) of the Institute and Faculty of Actuaries   
The aim of the module is to develop necessary skills that will enable students to apply the principles of actuarial control planning and control to the appraisal of investments, and to the selection and management of investments appropriate to the needs of the investors. The structure of the course mainly follows the expectations required for subject CA1 of the Faculty and Institute of Actuaries (or old course 301 of the Faculty and Institute of Actuaries but not everything in this old course). Not everything pertaining to subject CA1 will be covered so no exemptions from the Faculty and Institute of Actuaries are expected. The following will be covered under this course

Introduction to investments and asset management; The actuarial control cycle (ACC); Taxation; Cash and money markets; Bond markets; Equity markets; Property markets; Derivatives; Collective investment vehicles; Overseas markets; Economic influences on investments; Other factors affecting relative valuation; Relationships between returns on asset classes; the institutional framework; personal investment; Investment indices; Valuation of individual investments; Valuation of Asset Classes and portfolios; Developing an investments strategy; Regulation of financial services; Capital project appraisal.

HACS418: STOCHASTIC MODELLING IN INSURANCE AND FINANCE

To include integer-valued variables: probability generating functions, convolutions. Markov chains: transition probabilities, classifications of states, stationary distributions, transient states. Gambler ruin, random walk. Markov processes: Chapman-Kolmogorov equations, transition rate matrix, forward and backward systems. Poisson process, normal equations, machine operation machinery breakdown, queuing model. This module covers stochastic modelling and its applications in different actuarial/financial problems.

HSTA412*: SURVIVAL MODELS       
Survival models and the life table; Describe the future lifetime as a random variable
Define probabilities of death and survival, Define the actuarial functions tpx, tqx, n/mqx,  Define the complete and curtate expectations of future lifetime, Describe the life table functions lx and dx, Describe the simple laws of mortality, Define simple assurance and annuity contracts and develop formulae for means and variances.
Estimating the lifetime distribution Fx(t); Describe how lifetime data might be censored, Describe the estimation of empirical survival function, Describe the Kaplan- Meier estimate of the survival function in the presence of censoring, Describe the Nelson-Aalen estimate of the cumulative hazard rate in the presence of censoring, compute it from typical data and estimate its variance.    
The Cox regression model; Describe the Cox model for proportional hazards and derive the partial likelihood estimate
The two state Markov model; Describe the two state model of a single decrement and compare the assumptions with those of the random lifetime, Derive the MLE for the transition intensities in models of transfers between states with piecewise constant transition intensities, Define waiting time in a state.
The general Markov model; Describe the statistical models of transfers between multiple states, State the assumptions underlying the Markov model of transfers between a finite number of states in continuous time,      
Binomial and Poisson Models of Mortality; Describe the Binomial model of mortality, derive a maximum likelihood estimator for the probability of death and compare the Binomial model with the multiple state models
Graduation and statistical tests; Describe how to test crude estimates for consistency with standard table or a set of graduated estimates, and describe the process       .
Methods of graduation; Describe the process of graduation by the three common methods and state the advantages and disadvantages of each.      
Exposed to risk; Define initial and central exposed to risk, and the various common rate intervals, Calculate the central exposed to risk in simple cases. State the principle of correspondence.

HACS470: DISSERTATION
Students will be expected to complete a research project on a topic of their choice but limited to the taught courses. The project is a consolidation of the theoretical knowledge gained in the taught courses and the practical experience gained from Industrial Attachment

CS131: Communication SKILLS

Refer to Communication skills

GS231 GENDER STUDIES

Refer to Gender Institute.

TCNP201 TECHNOPRENEURSHIP

Refer Faculty of Science and Technology