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Courses Descriptions

 

MATH 101: Differential Calculus                                                           3 (3+0+0) credit hours

The concept of limit, computation of limits, continuity and its consequences, limits involving infinity, formal definition of limit, the concept of derivative, computation of derivatives (power rule, higher order derivatives, acceleration), the product and quotient rules, the chain rule, derivatives of exponential and logarithmic functions, implicit differentiation and inverse trigonometric functions, the mean value theorem, indeterminate forms and L'Hopital's rule,  maximum and minimum values, increasing and decreasing functions, concavity and the second derivative test, optimization, related rates.   

 

MATH 106: Integral Calculus                                                                3 (3+2+0) credit hours

Definition of Definite Integral and its Properties, The Anti-derivative, Indefinite Integral and the Fundamental Theorem of Calculus. Change of Variables, Integrals of natural and general exponential functions, Integrals of natural and general Logarithmic functions, Derivatives and Integrals of Hyperbolic and Inverse-Hyperbolic functions, Techniques of Integration: by parts, Trigonometric substitutions, Completing the square, Integrals of rational functions, Miscellaneous Substitutions, Indeterminate forms, Improper Integrals, Applications of Integration: Area, Solids of Revolutions, Arc length and Surface of Revolution, Linear Motion, Work, Momentum and Center of Mass, Numerical Integration, Polar coordinates, relation between polar and Cartesian coordinates, Graphs of polar curves, Area in Polar coordinates, Parametric Equations.

Prerequisite: MATH 101

 

MATH 132: Logic Mathematics                                                            3(2+2+0) Credit hours

Mathematical Logic and Proof Methods, Sets and their Operations, Cartesian Product for Sets and its Properties, Binary Relations and their Properties, Functions, Set Equivalence and Countable sets.

 

MATH 206: Multi-variable Differential and Integral Calculus                 4(3+2+0) Credit hours

Cartesian, cylindrical and spherical coordinate systems. Functions of two and three variables, limits and continuity, partial derivatives, the chain rule, extrema of functions of two variables, Lagrange multipliers. Double integrals, moments and center of mass, double integrals in polar coordinates, triple integrals, application of triple integrals, triple integrals in cylindrical and spherical coordinates, surface area. Sequences, infinite series, convergence tests, representation of functions by power series, Taylor and Maclaurin series, the binomial series.

Prerequisites: MATH 106

 

MATH 240       Introduction to Linear Algebra                                       4(3+2+0) Credit hours

Matrices and their operations, types of matrices. Elementary transformations. Determinants and their elementary properties. Inverse of a matrix. Linear systems of equations. Vector spaces, linear independence, finite dimensional spaces, subspaces. Inner product spaces. Linear transformations, kernel and image of a linear transformation. Eigenvalues and eigenvectors of a matrix and of a linear operator.

Prerequisites:  MATH 132

 

 

MATH 280       Introduction to Real Analysis                                        4(3+2+0) credit hours

Bounded subsets of the real line; supremum and infimum, completeness axiom; convergent sequences, Cauchy criterion, subsequences; series of numbers, generalized tests of convergence; limits of functions, continuity on an interval, intermediate value property, extrema; differentiability, mean value theorem and its consequences, Taylor's theorem; Riemann integral; Uniform convergence of sequences and series of functions, tests for uniform convergence, power series.

Prerequisites: MATH 206

 

MATH 380        Stochastic Processes                                                        4(3+2+0) credit hours            Axiomatic definition of probability, random variables and their probability distributions, relation with distribution functions. Expectations, conditioning with respect to a class of random variables. Stochastic processes, finite dimensional probabilities, independent processes. Discrete Markov chains, transition probabilities, recurrence, long term distributions. Continuous time Markov chains, Jump processes, birth-death processes, Poisson processes, Weiner processes.

Prerequisites: MATH 280, STAT 216

 

ACTU 262       Actuarial Corporate Finance                                          3(3+0+0) credit hours.

This course has Methods to evaluate financial alternatives and create financial plans. corporate finance from the viewpoint of financial managers. The concept of net present value, suitably adapted to account for taxes, uncertainty, and strategic concerns. A large segment of the lessons cover capital budgeting decisions. Emphasis is placed on the interaction of taxes and the cost of capital and buying decisions. Dividend policy, the CAPM, and capital market efficiency, as they relate to the value-maximization objective of the firm. Definitions of key finance terms: stock company; capital structure, bond, stock, basic options (calls, puts); dividends; price to earnings ratio . Key finance concepts: financing companies; characteristics and uses of financial instruments. sources of capital. financial leverage and long/short term financing policies. Characteristics of the principal forms of financial instrument. Structure of a stock company and the different methods by which it may be financed. Measures of financial performance: balance sheet; income statement; statement of cash flows; financial ratios (e.g. leverage, liquidity, profitability, market value ratios): the payback, discounted payback models; internal rate of return and profitability index models.

Prerequisite: FIN 200

 

ACTU 371       Financial Mathematics                                                 4(3+2+0) credit hours

Interest rate. accumulation function, future value, current value, present value, net present value, equation of value, discount factor, discount rate, convertible m-thly, nominal rate, effective rate, inflation and real rate of interest, force of interest, Level annuity, finite term, level  annuities, perpetuities, arithmetic progression annuities, geometric progression annuities, continuous varying annuities, loans, outstanding balance, amortization, sinking funds, price of the bond, redemption value, par value/face value, yield rate, coupon, coupon rate, term of bond, book value, amortization of premium, accumulation of discount, callable/non-callable. Yield rate/rate of return, dollar-weighted rate of return, time-weighted rate of return, current value, duration, convexity, spot rate, forward real risk-free rate, inflation rate, default risk premium,  liquidity premium, and maturity risk premium rate, yield curve, stock price, stock dividend, liability, immunization, swap rate, market value of a swap, settlement dates, settlement period, counterparties, deferred swap, amortizing swap, accreting swap, interest rate swap net payments.

Prerequisites: MATH 106

 

ACTU 372       Actuarial Mathematic Models                                      4(3+2+0) credit hours

Introduction to life insurance and basic notations, Survival models, Life tables and Selection, Insurance Benefits, Annuities: life annuities, comparison of annuities, evaluating annuity functions, Premium calculation: present value of the future loss random variable, equivalence principle, Gross premium calculation, Profit, portfolio percentile premium principle, extra risks, Policy values: Policies with annual cash flows, cash flows at discrete intervals, continuous cash flows, policy alterations, retrospective policy value, negative policy values.

Prerequisites: ACTU 371

 

ACTU  471      Financial Derivatives                                                      3(3+0+0) credit hours

Forward contract, prepaid forward contracts, outright purchase, fully leveraged, purchase.

payoff of long and short forward, net profit of long and short forward, marking to market, margin balance, maintenance margin, margin call, option Contracts: Call and put options, expiration date, strike price / exercise price, moneyness, European option, American option, Bermudan option, payoff and net profit of long and short option positions, swaps contract, Put-call parity, option spreads (bull, bear, box, ratio), collar, zero-cost collar, straddle, strangle, butterfly spread.

Prerequisites: ACTU 371

 

ACTU 472       Actuarial Mathematical models II                                        3(3+0+0) credit hours

Multiple state models: Kolmogorov’s equations; numerical evaluation of probabilities; premiums; policy values and Thiele’s differential equation; multiple decrement models; joint life and last survivor benefits; transitions at specified ages, Salary scale function; setting the DC contribution; the service table; valuation of benefits; funding plans, Interest rate risk: the yield curve; valuation of insurances and life annuities; diversifiable and non-diversifiable risk; Monte-Carlo simulation, Emerging costs for traditional life insurance: profit testing for traditional life insurance; profit measures.

Prerequisites: ACTU 371

         

ACTU 473       Models for Financial Economics                                           4(3+2+0) credit hours

One-period binomial model on a non-dividend-paying stock, principle of no-arbitrage, risk-neutral pricing formula, one-period binomial model on stocks, stock paying dividends continuously at a rate proportional to its price, currency, and futures contract, Multi-period setting for pricing European and American options, binomial model from market stock price data, Forward binomial tree, Cox-Ross-Rubinstein tree, lognormal tree. Black-Scholes model: lognormal distribution, probabilities and percentiles, means and variances, conditional expectations, analytic pricing formulas: cash-or-nothing calls and puts, asset-or-nothing calls and puts, ordinary calls and puts (the Black-Scholes formula), gap calls and puts, risk-neutral pricing formula using Monte-Carlo simulation, inverse transformation, path-independent and path-dependent options, Antithetic variate, stratified sampling, control variate, Black-Scholes formula to price exchange options, rate of appreciation, historical volatility, implied volatility, Option Greeks (Delta, Gamma, Theta, Vega, Rho, and Psi), Option elasticity, Sharpe ratio and instantaneous risk premium for both an option and a portfolio of options and the underlying stock, Black-Derman-Toy tree, interest rate caplets, floorlets and bond calls and puts.

Prerequisites: ACTU 471         

 

 

ACTU 474       Risk Theory                                                                3(3+0+0) credit hours

Definition of the notion of premium of an insurance policy and introduction of different methods for computing the premium, including the stop-loss reinsurance. Construction of individual and collective risk models for the aggregate loss of a portfolio of insurance policies when the number of claim of claims in known or unknown respectively, including the convolution formula, or by using moment generating function, introduction of computational methods of approximation including the normal and the normal power methods. Introduction to variant methods to generate new distributions from known ones, including scalar multiplication, power, exponentiation and limiting distributions.

Prerequisites: ACTU 372, MATH 380

 

ACTU 475       Credibility Theory and Loss Distributions                      4(3+2+0) credit hours

Severity Models (Calculate the basic distributional quantities: moments, Percentiles, Generating functions, Describe how changes in parameters affect the distribution, Calculate various measures of tail weight and interpret the results to compare the tail weights). Frequency Models (For the Poisson, Mixed Poisson, Binomial, Negative Binomial, Geometric distribution and mixtures thereof) Aggregate Models (Compute relevant parameters and statistics for collective risk models. Evaluate compound models for aggregate claims. Compute aggregate claims distributions. Evaluate the impacts of coverage modifications: (Deductibles, Limits, Coinsurance), Calculate Loss Elimination Ratios, Evaluate effects of inflation on losses.

Construction of Empirical Models, Estimate the variance of estimators and confidence intervals for failure time and loss distributions. Estimation of decrement probabilities from large samples. Construction and Selection of Parametric Models, Estimate the parameters of failure time and loss distributions with censored and/or truncated data using maximum likelihood, Determine the acceptability of a fitted model and/or compare models, apply limited fluctuation (classical) credibility including criteria for both full and partial credibility. Perform Bayesian analysis using both discrete and continuous models, Apply Bühlmann and Bühlmann-Straub models and understand the relationship of these to the Bayesian model. Apply conjugate priors in Bayesian analysis and in particular the Poisson-gamma model.

Apply empirical Bayesian methods in the nonparametric and semiparametric cases.

Prerequisites: ACTU 474

ACTU 483       Lab Financial Mathematics                                              1(0+0+2) credit hours

This course will allow students to learn to use the MATLAB Financial Toolbox™. It provides functions for mathematical modelling and statistical analysis of financial data. Optimize portfolios of financial instruments, optionally considering turnover and transaction costs.  The toolbox is used to estimate risk, analyses interest rate levels, price equity and interest rate derivatives, and measure investment performance.  Time series analysis functions and an app let you perform transformations or regressions with missing data and convert between different trading calendars and day-count conventions.

Prerequisites: Complete 123 credit hours

 

ACTU 484       Lab Actuarial Mathematics                                              1(0+0+2) credit hours

 R program  in actual sciences and finance (package  installation), Financial data for R Examples and Labs (historical data for some indices  and stock), Preliminary R explorations in finance, (Using quantmod package tools to  retrieve actuarial data and compute some statistics, Statistics of financial time series,  Correlations, causalities and similarities (Pearson vs Kendall correlation): Causality, Clustering, K-means, ARMA, ARCH and GARCH models (autocorrelation in exchange rates for currencies), Neural Networks (Nnet) and Support Vector Machines (svm), Brownian motion, binomial trees and Monte Carlo simulations, Computational actuarial science, Portfolio optimization.

Prerequisites: Complete 123 credit hours

 

ACTU  498      Field Training                                                                              6 credit hours

A plan is prepared so that students are offered suitable training at the Saudi Arabian Monetary Fund, banks, or insurance organizations and companies.

Prerequisites: Complete 138 credit hours

 

STAT 105         Statistical Methods                                                       4(3+2+0) credit hours

Some Statistical distributions - Sampling distributions - Central limit theorem - Chebyshev’s inequality - Interval estimation - Testing hypotheses (two populations case) - Introduction to experimental designs (CRD and RBD)- Analysis of variance (one and two ways) - Regression (simple) - Correlation (Pearson and Spearman) - Chi square tests and application - Some nonparametric tests.                                 

Prerequisites: STAT 101

 

STAT 216         Actuarial Probability                                                     4(3+2+0) credit hours

Set functions, Mutually exclusive events, Addition and multiplication rules, Independence of events, Combinatorial probability, Conditional probability, Bayes Theorem / Law of total probability, Random variables and distributions, Mode, median, percentiles, and moments,  Variance and measures of dispersion (including coefficient of variation), Moment generating functions, Transformations, Joint probability functions and joint probability density functions,  Joint cumulative distribution functions,  Conditional and marginal probability distributions, Moments for joint, conditional, and marginal probability distributions, Joint moment generating functions, Variance and measures of dispersion for conditional and marginal probability distributions, Covariance and correlation coefficients, Transformations and order statistics,  Probabilities and moments for linear combinations of independent random variables, Central Limit Theorem.

Corequisite: Math 206

 

STAT 328         Statistical Packages                                                      3(2+2+0) credit hours

Using program code in a statistical software package (Excel – Minitab – SAS – SPSS - R - Maple - Matlab) to write a program for data and statistical analysis. Topics include creating and managing data files - graphical presentation - and Monte Carlo simulations.

Prerequisites: STAT 105, CSC 115

 

STAT 332         Regression Analysis                                                     3(2+0+2) credit hours

Simple linear regression model - Multiple linear regression - Analysis of residuals and predictions – inference about the parameters - Stepwise regression - Some nonlinear regression models and data transformations - Student will use statistical computer packages such as R.

Prerequisites: STAT 328

 

STAT 336         Time Series and Forecasting                                          3(2+0+2) credit hours

Data sources: Historical data- the Web. Checking time series components: trend – seasonality - cyclical. Transformation:  Differences method - Seasonal adjustment. Forecasting: How to forecast future - adequacy of a forecast - regression forecasting against time series forecasting - some adequacy measures (MAD - MSE - MAPE). Decomposition and smoothing of times series: moving averages - exponential smoothing. Box-Jenkins models ARIMA(p -d -q): Autocorrelation and partial autocorrelation functions - identification of appropriate model - dealing with seasonal time series - fitting models to real and simulated data sets. Diagnostic checks on the residuals. Case studies: training on how to analyze real life data sets using the statistical package MINITAB - write reports.

Prerequisites: STAT 332

OPER 441        Modeling and Simulation                                  4(3+2+0) credit hours

Random number generators - Monte Carlo techniques - Simulation design - Input modeling - Model validation - Analysis of simulation output - Evaluation of alternatives -  Applications to various operations research models using simulation languages such as SLAM, GPSS and Arena.

Prerequisites: MATH 380

 

 ACCT 201 Principles of Accounting and Financial Reporting                3(3+0+0) credit hours

The course aims at providing an understanding of accounting by focusing on the accounting system and principles and practices of financial accounting and preparing of financial reports in merchandising and services proprietorships, in addition, the course introduces the principles of financial reports analysis.

 

ECON 101       Principles of Microeconomics                                       3(3+0+0) credit hours

This course aims at provide the necessary theoretical background on microeconomics theory. It includes: Introduction: definition, methodology, tools of economics, and the economic problem; the price mechanism: basics of supply and demand, and the market analysis of consumer behavior, market demand, equilibrium, and elasticity, theory of production and costs, market structures, supply and demand for factors of production.

 

ECON 102       Principles of Macroeconomics                                      3(3+0+0) credit hours

This course provides the necessary theoretical background on macroeconomics theory. It also includes concepts of national income, the national accounts, determination of the semester of equilibrium of national income, money and banking, inflation, foreign trade, economic growth and development, introduction to the aggregate demand and aggregate supply model.

Prerequisites: ECON 101

 

FIN 200           Principles of Finance                                                    3(3+0+0)  credit hours.

The main topics covered in this course include: financial environment, interest rates and time value of money, financial reports and their analysis, capital budgeting, and risk and return.

Prerequisites: ACCT 201

 

CSC 115                 Introduction to Programming with C++                      4(3+0+1) credit hours

Overall structure of a C++ program, compiling: linking and running programs, Data types: Variables and constants, Operators: arithmetic, relational and Boolean, Expressions, input & output, Control structures (Decision): If statement, If-else statement, Switch statement, Control structures (Iterations), While loop, Do-while loop, For loop, Array: One dimension array, Two dimension array, Introduction to classes, Methods and message passing, Introduction to Inheritance and polymorphism.

 Prerequisites: CT 101