Registry
Module Specifications
Archived Version 2021 - 2022
| |||||||||||||||||||||||||||||||||||||
Description The purpose of this module is to provide the necessary tools to measure changing market, investment, credit and liquidity risks. Emphasis is on the quantitative aspects of Financial Risk Management such as Value-at-Risk and Expected Shortfall. Providing a core body of knowledge for independent risk management analysis, students taking this module will be well prepared for GARP's annual FRM exam. | |||||||||||||||||||||||||||||||||||||
Learning Outcomes 1. Apply a risk management perspective to generate value through risk management. 2. Measure market, credit, investment and liquidity risk in financial institutions. 3. Use quantitative methods to model the distribution of financial assets for risk measurement and management purposes. 4. Apply sophisticated Value-at-Risk and Expected Shortfall methodologies to a wide range of settings. 5. Construct a risk assessment as an input in capital allocation decisions. | |||||||||||||||||||||||||||||||||||||
All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml |
|||||||||||||||||||||||||||||||||||||
Indicative Content and
Learning Activities The Rationale for Risk ManagementShareholders and firms perspective on risk management to generate value.Market Risk ManagementStylized facts of asset returns: expected returns predictability, conditional volatility and conditional distributions. Models and risk measures: Value-at-Risk (VaR) and Expected Shortfall (ES).Investment Risk ManagementPortfolio Risk Management: performance, risk, risk-adjustments and risk budgeting. Hedge-Fund Risk Management: leverage, long- and short-positions, agency-, counterparty-, fraud- and regulatory-risk.Credit Risk ManagementProbability of Default, Recovery Rate and Credit Exposure: analysis and measure to investigate how institutions may reduce default probability and risk exposure while increasing recovery rate.Liquidity Risk ManagementDefinition of Liquidity Risks. VaR adjustements for normal liquidity risk. Crisis liquidity risk.Implementation of Risk Measures and ModelsMonte Carlo Methods: Historical Simulations, Weighted Historical Simulations, Monte Carlo Simulations. Econometric Methods: ARMA, GARCH, Extreme Value Theory, Filtered Historical Simulations.Evaluation of Risk Measured and ModelsBacktesting of VaR and ES as a final diagnostic check on the aggregate risk model. Stresstesting: appropriate creation of extreme scenarios and assessment of the resulting output. | |||||||||||||||||||||||||||||||||||||
| |||||||||||||||||||||||||||||||||||||
Indicative Reading List
| |||||||||||||||||||||||||||||||||||||
Other Resources None | |||||||||||||||||||||||||||||||||||||
Programme or List of Programmes | |||||||||||||||||||||||||||||||||||||
Archives: |
|