Giuseppe STORTI | STATISTICAL MODELS FOR RISK MANAGEMENT
Giuseppe STORTI STATISTICAL MODELS FOR RISK MANAGEMENT
cod. 0222400037
STATISTICAL MODELS FOR RISK MANAGEMENT
| 0222400037 | |
| DEPARTMENT OF ECONOMICS AND STATISTICS | |
| EQF7 | |
| STATISTICAL SCIENCES FOR FINANCE | |
| 2024/2025 |
| OBBLIGATORIO | |
| YEAR OF COURSE 2 | |
| YEAR OF DIDACTIC SYSTEM 2014 | |
| AUTUMN SEMESTER |
| SSD | CFU | HOURS | ACTIVITY | |
|---|---|---|---|---|
| SECS-S/03 | 10 | 60 | LESSONS |
| Exam | Date | Session | |
|---|---|---|---|
| STORTI | 17/12/2024 - 09:00 | SESSIONE ORDINARIA | |
| STORTI | 17/12/2024 - 09:00 | SESSIONE DI RECUPERO | |
| STORTI | 13/01/2025 - 09:00 | SESSIONE ORDINARIA | |
| STORTI | 13/01/2025 - 09:00 | SESSIONE DI RECUPERO |
| Objectives | |
|---|---|
| KNOWLEDGE AND UNDERSTANDING THE COURSE AIMS AT PROVIDING THE STUDENTS WITH THE METHODOLOGICAL TOOLS FOR UNDERSTANDING ADVANCED QUANTITATIVE MODELS FOR THE ANALYSIS OF FINANCIAL MARKETS AND THEIR RISK STRUCTURE. IN PARTICULAR, IT IS EXPECTED THAT THE STUDENTS MASTER THE FOLLOWING NOTIONS -KNOWLEDGE OF THE MAIN DATABASES FOR RISK MANAGEMENT APPLICATIONS -KNOWLEDGE OF THE MAIN EX-POST VOLATILITY ESTIMATORS -KNOWLEDGE OF THE MAIN UNIVARIATE AND MULTIVARIATE MODELS FOR FORECASTING FINANCIAL VOLATILITY -KNOWLEDGE OF THE MAIN METHODS AND MODELS FOR FORECASTING FINANCIAL RISK MEASURES (VAR AND ES) -KNOWLEDGE OF THE MAIN METHODS FOR BACKTESTING FINANCIAL RISK MEASURES APPLYING KNOWLEDGE AND UNDERSTANDING THE COURSE AIMS AT HELPING THE STUDENTS TO DEVELOP THE ABILITY OF USING ADVANCED QUANTITATIVE MODELS FOR THE ANALYSIS OF FINANCIAL MARKETS. IN PARTICULAR IT IS EXPECTED THAT THE STUDENTS DEVELOP THE FOLLOWING ABILITIES -ABILITY TO IMPLEMENT INTO THE R LANGUAGE THE MAIN METHODS FOR ESTIMATION, FORECASTING AND BACKTESTING OF VOLATILITY AND THE MAIN FINANCIAL RISK MEASURES -ABILITY TO IMPLEMENT ON REAL DATASETS THE MAIN RISK MANAGEMENT APPLICATIONS INCLUDING FORECASTING AND BACKTESTING RISK MEASURES AND PORTFOLIO OPTIMIZATION |
| Prerequisites | |
|---|---|
| IT IS EXPECTED THAT STUDENTS ATTENDING THE COURSE HAVE A BASIC KNOWLEDGE OF PROBABILITY AND STATISTICAL INFERENCE. IN PARTICULAR IT IS DESIRABLE THAT THE STUDENTS TAKING THE COURSE HAVE SUCCESSFULLY ATTENDED THE STOCHASTIC PROCESSES AND STATISTICAL INFERENCE COURSES DURING THE FIRST YEAR OF THEIR STUDY PLAN. |
| Contents | |
|---|---|
| THE MEASUREMENT OF PRICES AND RETURNS (2 HRS) DEFINITION AND MEASUREMENT OF VOLATILITY: ESTIMATORS BASED ON END-OF-DAY DATA (SQUARED RETURNS, ABSOLUTE RETURN), ESTIMATORS BASED ON INTRA-DAILY DATA (HIGH LOW RANGE, REALISED RANGE, REALISED VARIANCE), IMPLIED VOLATILITY AND OPTIONS (10 HRS). EMPIRICAL PROPERTIES OF RETURNS AND VOLATILITY: FUNDAMENTALS OF TIME SERIES ANALYSIS, STYLISED FACTS IN THE MEASUREMENT AND ANALYSIS OF RETURNS, THEORY OF EFFICIENT MARKETS, VOLATILITY CLUSTERING, THE LEVERAGE EFFECT, THE ROLL MODEL, PORTFOLIO VOLATILITY (10 HRS) STOCHASTIC MODELS FOR RETURNS: MODELS FOR CONDITIONAL MEAN, MODELS FOR CONDITIONAL VARIANCE, JOINT MODELS FOR MEAN AND VARIANCE, ESTIMATION AND DIAGNOSTICS, PREDICTION OF LEVELS AND VOLATILITY OF RETURNS (14 HRS) MARKET RISK MEASURES: VALUE AT RISK (VAR) AND EXPECTED SHORTFALL (ES), FORECASTING VAR AND ES 1-STEP-AHEAD, FORECASTING VAR AND ES K-STEP-AHEAD, BACKTESTING RISK MEASURES (12 HRS). MULTIVARIATE MODELS FOR RETURNS: VECTOR AUTOREGRESSIONS, MULTIVARIATE GARCH MODELS (MGARCH) FOR THE CONDITIONAL VARIANCE AND COVARIANCE MATRIX: VECH, BEKK; MODELS FOR THE CONDITIONAL CORRELATION MATRIX: CCC, DCC; FINANCIAL APPLICATIONS OF MGARCH MODELS: HEDGING, VAR AND ES ESTIMATION, PORTFOLIO OPTIMISATION (12 HRS) THE PRESENTATION OF THE TOPICS WILL BE SUPPORTED BY THE DEVELOPMENT OF CASE STUDIES WITH IMPLEMENTATION IN R |
| Teaching Methods | |
|---|---|
| CLASSROOM LECTURES. THE LECTURES WILL INCLUDE A DISCUSSION OF THE MAIN THEORETICAL SUBJECTS AND WILL BE COMPLEMENTED BY THE COMPUTER IMPLEMENTATION (IN R LANGUAGE) AND DISCUSSION OF REAL CASE STUDIES. THE LECTURES WILL INCLUDE SOME COMPUTER BASED PRACTICALS INVOLVING THE ANALYSIS OF REAL DATASETS. |
| Verification of learning | |
|---|---|
| THE SATISFACTORY ACHIEVEMENT OF THE AIMS OF THE COURSE IS ASSESSED THROUGH AN EXAM WITH MARKS OUT OF THIRTY. THE EXAM IS BASED ON A WRITTEN TEST THAT INCLUDES NUMERICAL EXERCISES AS WELL AS THEORETICAL QUESTIONS. THE PASS MARK IS 18/30. THE WRITTEN TEST, OF DURATION APPROXIMATELY EQUAL TO 90 MINUTES, IS AIMED AT ASSESSING THE KNOWLEDGE AND THE ABILITY TO UNDERSTAND THE SUBJECTS INDICATED IN THE COURSE PROGRAMME, THE ABILITY TO MASTER AND APPLY THE ANALYTICAL TOOLS REQUIRED AND THE ABILITY TO APPLY THE THEORETICAL NOTIONS TAUGHT. THE WRITTEN TEST REQUIRES I) THE SOLUTION OF NUMERICAL EXERCISES RELATED TO THE MAIN TOPICS COVERED DURING THE COURSE (E.G. ASSESSING THE STATISTICAL PROPERTIES OF ESTIMATED MODELS, FORECASTING AND BACKTESTING FINANCIAL RISK MEASURES) II) ANSWERING TO THEORETICAL QUESTIONS ON THE TOPICS INCLUDED IN THE COURSE PROGRAMME. DURING THE TEST STUDENTS ARE NOT ALLOWED TO READ TEXTBOOKS, USE PCS, TABLETS AND MOBILE PHONES; THEY ARE ONLY ALLOWED TO USE A BASIC ELECTRONIC CALCULATOR AND THE USUAL STATISTICAL TABLES. IN THE ASSESSMENT PROCESS, THE FOCUS WILL BE ON EVALUATING THE ABILITY TO CORRECTLY APPLY THE TAUGHT METHODS, THE RIGOUR AND CLARITY OF EXPRESSION. |
| Texts | |
|---|---|
| THE LECTURER WILL MAKE THE SUPPORTING LECTURE MATERIAL AVAILABLE ON HIS INSTITUTIONAL WEBSITE: HTTPS://DOCENTI.UNISA.IT/005005/RISORSE IN ANY CASE, IT IS ADVISABLE TO SUPPLEMENT AND DEEPEN THE MATERIAL PROVIDED BY STUDYING THE FOLLOWING TEXTS FOR THE ENTIRE COURSE TSAY, R. (2005) ANALYSIS OF FINANCIAL TIME SERIES (2ND EDITION), WILEY SERIES IN PROBABILITY AND STATISTICS (CH 1-3-5-7-8.1-8.2.8.3-8.4-10). FOR THE ENTIRE COURSE EXCLUDING THE SECTION ON MULTIVARIATE MODELS STORTI G., VITALE C. (2011) STATISTICAL ANALYSIS OF MONETARY AND FINANCIAL MARKETS, ESI. |
| More Information | |
|---|---|
| FURTHER MATERIAL (EG DATA, SOFTWARE, LECTURE NOTES) WILL BE DISTRIBUTED THROUGH THE INSTRUCTOR'S WEBSITE. |
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