Module Code - Title:
IN6131
-
RISK MODELLING AND DERIVATIVE MARKETS
Year Last Offered:
2025/6
Hours Per Week:
Grading Type:
N
Prerequisite Modules:
Rationale and Purpose of the Module:
Derivative markets are ubiquitous in finance and in other business settings. As such, financial practitioners must develop the knowledge and skillsets on how derivatives, and the markets in which they operate, are modelled, priced, evaluated, and used to generate or maintain economic value, and control financial risk. The purpose of this module is to give students a thorough grounding in the qualitative principles and quantitative methodologies for modelling financial risk by developing a strong understanding of market risk, derivatives, and derivative markets.
Syllabus:
The module commences with a look at simple derivative instruments such as futures, forwards, and swaps, and quickly progresses to cover options (on stocks, indices, currencies, etc.), and option trading strategies. The second half of the module will provide the foundations needed for modelling financial risk including market, liquidity, credit, and model risk. Emerging risks (e.g. cryptocurrencies) and market dynamics (e.g. Sustainable Investing and ESG reporting) will also be considered. The theoretical and applied aspects of risk forecasting, machine learning, and AI will be used to examine and model volatility, value-at-risk and expected shortfall methodologies. The theoretical material in this module is fundamental in the understanding of modern trading dynamics, risk management and compliance roles. The KBS Trading Floor will be used as a key physical asset and will underscore the lecture material with contemporary examples and assignments.
Learning Outcomes:
Cognitive (Knowledge, Understanding, Application, Analysis, Evaluation, Synthesis)
On successful completion of this module, students will be able to:
• Demonstrate the development of specialised technical data literacy and risk analysis skills together with an understanding of the role of derivatives instruments in portfolio risk management.
• Demonstrate the development of broad transferable skills such as data visualisation, problem-solving, and creative thinking as a premise to enable evidence-based decision-making.
• Identify and critically engage with seminal and contemporary literature, concepts and methods that inform the global finance and insurance industries.
• Demonstrate articulate communication and collaboration skills through class discussion, group work, and written assignments.
Affective (Attitudes and Values)
On successful completion of this module, students will be able to:
• Proactively engage in reflective learning and critical review as it relates to risk modelling and model assumptions.
• Demonstrate an appreciation of the values underlying sustainable investing and ESG reporting, and the role the learner plays in perpetuating these values.
Psychomotor (Physical Skills)
N/A
How the Module will be Taught and what will be the Learning Experiences of the Students:
This modules aims to provide experience in modelling financial risk from an intuitive heuristic. A constructivist learning environment will be employed to maximise the 'learn-by-doing' principle of understanding the various ways in which risks can manifest in financial markets, leading to curious and courageous learners. Labs and tutorials will also be run to develop learner curiosity and courageousness by elevating their applied modelling skills, as well as elevating their understanding of derivatives and the markets in which they operate.
Research Findings Incorporated in to the Syllabus (If Relevant):
Prime Texts:
Hull, J.C. (2021)
Options, Future, and Other Derivatives, 11th edition
, Pearson Education
Alexander, C. (2008)
Market Risk Analysis: Value-at-risk Models
, Wiley
Danielsson, J. (2011)
Financial Risk Forecasting
, Wiley
Wolke, T. (2017)
Risk Management
, De Gruyter Oldenbourg
Choudhry, M. (2022)
The Principles of Banking
, Wiley
Svetlova, E. (2018)
Financial models and society: Villains or scapegoats?
, Edward Elgar Publishing
Other Relevant Texts:
International Swaps and Derivatives Association (2022)
The Future of Derivative markets
, ISDA
Stulz, R.M. (2008)
Risk management failures: What are they and when do they happen?
, Journal of Applied Corporate Finance
McCullagh, O., Cummins, M. and Killian, S. (2023)
The fundamental review of the trading book: implications for portfolio and risk management in the banking sector
, Journal of Money, Credit and Banking
Henrard, M.P. (2019)
LIBOR fallback and quantitative finance
, Risks
Aziz, S. and Dowling, M. (2019)
"Machine learning and AI for risk management", in Disrupting finance: FinTech and strategy in the 21st century
, Springer
González-Urteaga A., and Rubio G. (2022)
Guarantee requirements by European central counterparties and international volatility spillovers
, Finance Research Letters
Jalan, A. and Matkovskyy, R. (2023)
Systemic risks in the cryptocurrency market: Evidence from the FTX collapse
, Finance Research Letters
Galletta S, Mazzù S, Naciti V. (2022)
A bibliometric analysis of ESG performance in the banking industry: From the current status to future directions.
, Research in International Business and Finance
Giese, G., Lee, L.E., Melas, D., Nagy, Z. and Nishikawa, L. (2019)
Foundations of ESG investing: How ESG affects equity valuation, risk, and performance.
, Journal of Portfolio Management
OECD (2020)
"Environmental, social and governance (ESG) investing", in OECD Business and Finance Outlook 2020: Sustainable and Resilient Finance
, OECD Publishing
Bouma, J.J., Jeucken, M. and Klinkers, L. (eds.) (2017)
Sustainable banking: The greening of finance
, Routledge
Programme(s) in which this Module is Offered:
MSFINATFA - FINANCE
MSINRMTFA - INSURANCE AND RISK MANAGEMENT
Semester(s) Module is Offered:
Autumn
Module Leader:
orla.mccullagh@ul.ie