Ph.D. in Applied Mathematics with Specialization in  Mathematical Finance and Actuarial Mathematics

Professor Dr. Pairote Sattayatham
Risk Lab Bangkok, School of Mathematics, Institute of Science,
Suranaree University of Technology, THAILAND
email: อีเมลนี้จะถูกป้องกันจากสแปมบอท แต่คุณต้องเปิดการใช้งานจาวาสคริปก่อน

• Stochastics,

• Numerics, and

• Financial or Insurance Applications.

The instructional component of the program consists of eight courses, which can be taken over four semesters of full-time course work. Four of these are core courses. They are required to ensure students preparedness to begin research in the mathematics of finance or insurance. Students generally take the core courses in their first two semesters of residence. These core courses can be waived for students who have passed equivalent courses at other universities. Students are also required by the Mathematics Department to pass a Preliminary Examination, covering topics in the core courses. The core courses are the following:

• Measure and Integration (4 credits).

• Functional Analysis (4 credits).

• Stochastic Analysis (4 credits).

• Mathematical Finance (4 credits).

The remaining four courses consist of Ph.D. seminars (3 credits) and three other courses to be selected from the following:

• Continuous Model in Finance (4 credits).

• Computional method for Finance (4 credits)

• Stochastic Optimal Control and Investment (4 credits).

• Financial Time Series (4 credits).

• Risk Management (4 credits).

• Non-life Insurance Mathematics (4 credits)

• Life Insuance Mathematics (4 credits)

• Loss Reserving Methods in insurance (4 credits)

• Interest Rate Models (4 credits)

• Credibility   (4 credits)

The program is suitable for bright students with bachelor (or master) degrees in mathematics, statistics, economics, and physical or engineering sciences, who wish to pursue a career in academic research, finance, or insurance industry. Since this program is in collaboration with Brunel University, students will have a chance to do research in London for at least four months. Moreover, SUT will seek internships for students in major companies.

Coordinator of the Program:

Prof. Dr. Pairote Sattayatham 

(Optimal control theory. Currently, I am interested in asset pricing in incomplete market,  Non-life insurance, and  Financial forecast)

The following faculty in the Department of Mathematics, all of whom have research interest in mathematics in finance and insurance, are affiliated with this Ph.D. program.

Assoc. Prof. Dr. Prapasri Aswakun, Chair, School of Mathematics

Assist. Prof. Dr. Eckart Schulz 

Prof. Dr. Bhusana Premanode Invited professor from Imperial College London

(Financial Forecast)

Application Procedures

Application forms are available and all application materials can be downloaded from the university web site http://www.sut.ac.th/ces.  
Examination guideline (Thai).

Alternatively, you may write to:

Registration Division, Office of Admissions,
Suranaree University of Technology,
111 Universiy Avenue, Nakhon Ratchasima, 30000, Thailand.

Telephone request: 044 224315 or 089 5849868

Email correspondence: อีเมลนี้จะถูกป้องกันจากสแปมบอท แต่คุณต้องเปิดการใช้งานจาวาสคริปก่อน

Prerequisites

Applicants should have a very good working knowledge of

• Probability Theory.

• Mathematical Statistics

• Partial differential equations

• Linear Algebra.

• Numerical Analysis.

Applicants should also have facility with a programming language such as MathLab.

• Students lacking these prerequisites will be advised to take the advanced undergraduate courses at the Department of Mathematics at Suranaree University of Technology.

Course Descriptions

103621     Measure and Integration        

         The concept of measure spaces, measurable functions, integration of positive functions, Lebesgue’s monotone convergence theorem, integration of complex functions, integration as a linear functional, Riesz representation theorem, Borel measure, Lebesgue measure, integration on product spaces, and the Fubini theorem. 

103622     Functional Analysis

         Review topological spaces, continuous mapping on compact spaces, compactness and total boundness, Arzela theorem, application of Arzela to Peono's theorem, normed space, Banach space, and bounded linear functional, the Han-Banach theorem for normed linear spaces, the L-p spaces, relationship between L-p spaces, approximation by continuous functions, Hilber spaces and some important examples, projection theorem, Bessel inequality, orthonomal basis, basis in L-2 spaces, conjugate in Banach and Hilbert spaces, Riesz representation theorem. second conjugate spaces and weak convergence. 

103721     Stochastic Analysis

         Construction of stochastic processes, martingale and stopping time, Brownian motion, stochastic integration with respect to Brownian motion, the Grisanov theorem, local time of Brownian motion, Markov property of Ito diffusions, stochastic differential equation, and stochastic control.   

103642     Computational Methods for Finance                                                       

            Computational techniques for solving mathematical problems arising in finance, Monte Carlo methods, randomness and pseudo random numbers, simulation of random variables, simulation of continuous time process, simulation of model with jumps, option pricing by simulation, variance reduction technique, PDEs and finite difference method, free boundary problems, solution methods for American options, multi-asset problems and exotic options.

103741     Mathematical Finance                                               

           The main goal of this course is to provide students with a sound understanding of the modern techniques and theories from Mathematical Finance which are used in financial institutions. The courses cover questions such as the pricing of derivatives, risk management or portfolio optimization.

Topics include:
An introduction to arbitrage-based pricing of derivative securities, by including the topics on arbitrage, risk-neutral valuation, the log-normal hypothesis, binomial trees, the Black-Scholes formula and applications, the Black-Scholes partial differential equation, American options, Future, Risk management, and Portfolio optimization.

103742     Stochastic Optimal Control and Investment                                     

            An introduction to aspects of stochastic optimal control most relevant to finance and investment. 

Topics include: Discrete time models of investment, decisions under uncertainty, continuous time models involving the Brownian motion process and the Ito-process, dynamic programming, Bellmann's principle for optimality and its consequences, and optimal stopping. Investment opportunities and investment timing: basic models and solutions, sequential investment, learning curve and optimal production decisions.

103743     Continuous Models in Finance                                                           

            A second course in arbitrage-based pricing of derivative securities.

Topics include: The Black-Scholes model and its generalizations, equivalent martingale measures, the martingale representation theorem, the market price of risk, applications including change of numeraire and the analysis of quantos. Interest rate models: the Heath-Jarrow-Morton approach and its relation to short-rate models. The volatility smile/skew and approaches to accounting for it: underlyings with jumps, local volatility models, and stochastic volatility models.

103744     Financial Time Series                                                                        

            Introduction to S-Plus and exploratory data analysis, continuous time processes, time series analysis, multivariate data analysis, and elements of the extreme value theory.

103745     Risk Management                                                                                          

            This course examines financial risk measurement and management from the perspective of both a risk management department and of  a trading desk manager with emphasis on the role of financial mathematics and modeling in quantifying risk.

Topics include: Financial risk exposures, risk measurement techniques, risk management techniques, and Monte Carlo simulation to determine headge effectiveness. Extensive use will be made of examples drawn from real trading experience, with a particular emphasis on lessons to be learned from trading diaster.

103756     Optimization Methods in Finance

            Dynamic programming methods, stochastic dynamic programming and application to option pricing, stochastic programming, multistage problem, and application in risk measures, robus optimization: theory and tool, robust optimization model in finance.

  103771  Non-Life Insurance mathematics    

         Model of the claim number process, premium calculation principles, pricing methods, the total claim distribution, ruin theory, and the calculation of loss reserves.

 103772  Life Insurance mathematics

    Basic concept of life insruance: Life annuities, benefit premiums, benefit reserves, Stochastics model for life insurance mathematics: markov model, stochastic model for interest rates and demography, cash flow and reserves, cover capital and Thile's diffferential equation, Hatterndorf's theorem and unit-linked policies.

 103773  Loss Reserving Method in insurance

            Loss Reserving is one of the central topics in non-life insurance .  Mathematicians  need to estimate adequate reserves for all open claims. These claim reserves have a direct influence on most of financial statements such as calculation of premium and solvency margin.  In this course, we present various methods to calculate loss reserves such as Stochastic chain ladder method, Bayesian method, Credibility method, Generalized linear model, and Bootstrap Methods.

103774  Interest rate Models

             In this course, we discuss some important models in theory of interest rate. Topic includes:  Short-rate models, HJM models, LIBOR market models, pricing and hedging, numerical method,  model calibration.

103775  Credibility Theory

              Topic includes: Introduction to credibility as a branch of Bayesian statistics, Buhlmann-Straub model, treatment of Large claims in credibility, and hierachical credibility.

Frequency Quations.                        

1. Do you have scholarship ?  if you have , what should i do for getting it?

2.  How much of the budget and fee in whole program ?  How much the budget and  fee that i have to pay  for each term?

3. Is it close for enrolling?  what is the last date for enrolling?