Major | Code | Subject | ||
---|---|---|---|---|

Common | 21603203 | Mathematical Statistics I | ||

21603205 | Stochastic Processes I | |||

21603245 | Multivariate Statistical Analysis I | |||

21603246 | Time Series Analysis I | |||

21603212 | Linear Models I | |||

21603215 | Mathematical Statistics II | |||

21603224 | Linear Models II | |||

21603233 | Survival Analysis | |||

21603242 | Seminar in Statistics I | |||

21603243 | Seminar in Statistics II | |||

21603244 | Seminar in Statistics III | |||

Statistics | 21603204 | Probability Theory I | ||

21603206 | Regression analysis | |||

21603207 | Experimental Design | |||

21603209 | Sampling Theory | |||

21603211 | Nonparametric Statistics | |||

21603213 | Statistical Consulting I | |||

21603214 | Statistical Consulting II | |||

21603216 | Probability Theory II | |||

21603217 | Stochastic Processes II | |||

21603218 | Statistical Decision Theory | |||

21603219 | Testing Statistical Hypotheses | |||

21603220 | Asymptotic Theory | |||

21603221 | Seminar in Theorectical Statistics I | |||

21603222 | Seminar in Theorectical Statistics II | |||

21603223 | Statistical Computing I | |||

21603225 | Nonlinear Models | |||

21603226 | Applied Probability Theory I | |||

21603227 | Applied Probability Theory II | |||

21603231 | Seminar in Applied Statistics I | |||

21603232 | Seminar in Applied Statistics II | |||

21603234 | Optimization Theory | |||

21603235 | Bayesian Statistics | |||

21603236 | Multivariate Statistical Analysis II | |||

21603237 | Time Series Analysis II | |||

21603238 | Statistical Computing II | |||

21603239 | Information Theory | |||

21603240 | Statistical Quality Control | |||

21603241 | Data Mining | |||

Insurance | 21603267 | Life Actuarial Mathematics I | ||

21603268 | Life Actuarial Mathematics II | |||

21603269 | Non-Life Actuarial Mathematics I | |||

21603253 | Principles of Insurance | |||

21603247 | Seminar in Actuarial Science I | |||

21603255 | Pension Mathematics | |||

21603248 | Financial Mathmatics I | |||

21603264 | Financial Mathmatics II | |||

21603270 | Non-Life Actuarial Mathematics II | |||

21603258 | Seminar in Actuarial Science II | |||

21603259 | Financial Econometrics | |||

21603260 | Actuarial Risk Management | |||

21603262 | Asset Liability Management | |||

21603263 | Financial Engineering | |||

21603265 | Life Insurance Product Development | |||

21603266 | Actuarial Science for Health Insurance | |||

50084019 | Stochastic Calculus for Finance |

Master’s Course | First Semester | Second Semester | ||
---|---|---|---|---|

Statistics Major | Actuarial Science Major | Statistics Major | Actuarial Science Major | |

1st Year | Mathematical Statistics I Financial Mathmatics I Regression Analysis |
Mathematical Statistics I Financial Mathmatics I Non-Life Actuarial Mathematics I |
Linear Models I (Multivariate Statistical Analysis I, Statistical Computing I, Stochastic Processes I) |
Life Actuarial MathematicsI Financial Mathmatics II Non-Life Actuarial Mathematics II |

2nd Year | Data Mining (1 subject among Time Series Analysis and Bayesian Statistics) |
Life Actuarial Mathematics II (1 subject among Pension Mathematics, Actuatial Risk Management, Life insurance product development, Principles of Insurance, Seminar in Actuarial Science I) |

Mathematical Statistics I |
---|

This subject deals with mathematical theories common to statistical application methodologies, which covers distribution theory, and estimation theory. This lecture covers various distributions, limit distributions, sufficiency and exponential families, various estimation methods including maximum likelihood estimation, and selection criteria for good estimators. |

Regression Analysis |

This course reviews basic contents such as simple regression and multiple regression analysis, and deals with problems such as residual analysis, model selection method, influence measurement, and multicollinearity search and resolution. It further looks into weighted regression, variable transformation problems, nonlinear regression, and nonparametric regression analysis for cases that deviate from general assumptions. |

Linear Models I) |

This subject introduces generalized linear models and discusses logistic regression models and log-linear models for frequency data, in terms of the generalized linear model. |

Multivariate Statistical Analysis I) |

This subject studies multivariate statistical analysis based on multivariate statistical theory. It introduces the multivariate normal distribution and uses it to study inference and hypothesis testing on the mean vector and covariance matrix. It also studies principal component analysis, factor analysis, canonical correlation variance, discriminant analysis, and cluster analysis using multivariate covariance structure. It conducts data processing practice using statistical packages. |

Statistical Computing I |

This subject studies numerical analytical methods to obtain quick solutions while reducing calculation errors of various statistical calculations. It deals with random number generation, algorithms for linear and nonlinear models, and software analysis using them. |

Stochastic Processes I) |

This subject is statistical theory about probabilistic events that occur over time. This lecture covers the contents of the Markov chain, Poisson process, regeneration process, martingale, etc. |

Data Mining |

This subject studies various mathematical and statistical models of data mining. This lecture covers computer learning systems, Bayesian decision-making, latent Markov models, parametric or non-parametric classification analysis, cluster analysis, neural network networks, evolutionary algorithms, and multi-dimensional reduction. |

Time Series Analysis I |

This subject studies the Box-Jenkins model for time series data. This lecture studies the moving average model, auto regression model, ARIMA model, and it discusses the identification, estimation, distinction, and prediction methods of these models. |

Bayesian Statistics |

This subject deals with Bayesian inference based on Bayesian decision theory. It deals with subjective probability, prior distribution, likelihood principle, predictive distribution, and Bayesian theories related to estimation, test, and regression analysis. |

Financial Mathmatics I |
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This lecture covers simple and compound interest methods, and the calculation of the present and closing prices of defined annuities. It deals with topics such as internal rate of return, amortization, sinking funds, and bond valuation. |

Non-Life Actuarial Mathematics I |

This lecture introduces basic actuarial theory and techniques related to indemnity insurance. It deals with topics such as characteristics of each indemnity insurance item, rate-related statistical data accumulation and management, basic rate determination, rate classification system composition method, risk premium, basic insurance premium calculation method, and long-term indemnity insurance settlement. |

Life Actuarial Mathematics I |

This lecture introduces actuarial theory and techniques related to life insurance. It covers topics such as interest theory, survival distribution model and experience life table, net premium, life annuity, installment premium, and liability reserve. |

Financial Mathematics II |

This lecture provides an overview of derivatives. It introduces various types of derivative products such as futures, options, and swaps, and covers topics such as investment strategies, valuation methods, and risk management techniques. |

Non-Life Actuarial Mathematics II |

This lecture introduces advanced actuarial theory and techniques related to indemnity insurance. It covers topics such as the reserve estimation method, the composition and evaluation method of the experience rate system, the application method of the reliability method, the project cost estimation method, the profit and loss evaluation method, the mathematical underwriting method, and various simulation evaluation methods. |

Life Actuarial Mathematics II |

Following the life Actuarial Mathematics I, this lecture covers various theories related to joint life insurance, multiple decremental tables, the basics of pension mathematics, business insurance premiums, and operating premium-type liability reserves. |

Pension Mathematics |

This lecture covers basic pension mathematics. It deals with the search process for optimal fundraising methods that can be developed in the future and the existing fundraising methods suitable for appropriate asset management, focusing on corporate pensions and public pensions, and covers its related mathematical techniques. |

Actuatial Risk Management |

This lecture provides theories and techniques related to investment management and financial risk management that have been recently studied and applied. It deals with asset allocation strategies, asset pricing, risk modeling, and management techniques, focusing on practical case studies. |

Principles of Insurance |

This lecture covers he basic theory of insurance. It covers topics such as risk and the nature of insurance, types and functions of insurance, principles of insurance contracts, insurance company management, risk selection, insurance financial analysis, risk management, and insurance supervisory policy. |

Seminar in Actuarial Science I |

This lecture selects and covers an appropriate course among topics such as correction theory, the preparation method for life table and risk table, demographics, climate and weather derivatives, insurance business cost analysis, life insurance mathematics, pension mathematics, advanced theory related to non-life insurance, and risk management. |