Financial models are rather crude attempts at replicating human behaviours and thought processes. Highly useful, insightful, and enlightening in understanding the problem space, but ultimately rather crude. Problem is, behaviours and thought processes within finance are subject to constant change. What worked before may not necessarily work today. The mathematical, statistical, and decision-flow techniques that are employed to make financial decisions therefore need to be complemented with subject area know-how and emotional intelligence. More specifically, the limitations and decision-making of tools used in modern finance, and the environment in which they were first introduced, must be well understood.

 

That is the underlying principle of my teaching materials, which largely revolve around the application of statistical and mathematical models and frameworks to better-inform financial decision-making. I try to mesh the benefits afforded by decision-making tools in finance with their practical limitations - both in terms of their absolute limits, and their ability to misguide - in order to understand the human side of how these techniques and models operate. I do this by scoring my teaching materials with elements of model explainability and analyses of topical events using high-quality news outlets (FT, Bloomberg, WSJ, etc.), and getting students engaged in the process.

 

I want to create an environment where students can not only wield the cutting-edge tools used in finance, but know when and why they should be used.

Deep Learning for Finance, FI6015, Spring 2022 - 

• Module Lectures (~12.5mb, .pdf)

 

Finance is a data-driven sector, and excelling in Finance involves being adept at generating informed decisions using appropriate data. FI6015 helps learners gain an understanding of the latest developments in financial data analysis by applying cutting-edge statistical techniques to order to derive unique insights on financial phenomena. Specifically, learners are introduced to Deep Learning, a subfield of statistics involving the application of non-linear modelling techniques (Artificial, Convolutional, Recurrent, and Transformer Neural Networks) to swathes of data. Learners are instructed on the methods of applying these non-linear modelling techniques, the means by which data can be prepared for Deep Learning analyses, and introduced to emerging ways in which conventional and alternative financial data can be analysed. Learners also gain an appreciation of the multitude of contexts in which Deep Learning models can transform the way in which financial decisions are derived.

 

International Corporate Finance, FI6012, Autumn 2020 -

• Module Lectures (~48mb, .pdf)

 

FI6012 provides learners with knowledge and insights into international corporate finance and international financial market affairs. The course is driven by a combination of prevailing and historical corporate finance theories, underpinned by practical and topical news events from high-quality media outlets (FT, Bloomberg, WSJ). Emphasis is placed on investment valuations and sources of capital, and how international financial decisions impact on the value of the firm.  As the scope and content of International Finance is an evolving area, and capital markets are becoming globally integrated, a solid understanding of International Finance is vital for astute corporate decision-making. This module is more relevant given the recent pandemic, the deregulation of financial markets, and the ever-increasing volume of product innovations and technological advancements in finance.

FI6012 deals specifically with the interrelationships between the international monetary environment and financial planning for corporations with overseas operations.  It analyses the effects of exchange rate fluctuations, currency restrictions, business risks, and capital budgeting for foreign subsidiaries. It examines the financial management of multinational firms and the management of foreign exchange exposures.  The course teaches learners how to analyse key financial issues, financial statements and business strategies, and apply financial theories to practical issues in international corporate finance contexts.

Derivative Markets (Online), FI6035, Spring 2022 -

• Module Lectures (~8mb, .pdf)

 

In today’s market, financial practitioners must have a solid understanding of financial derivative concepts and instruments, as well as the uses of those instruments in capital markets. FI6035 helps learners gain intuition by linking theories and concepts together with a lecture series that emphasizes the core economic principles underlying the pricing and uses of derivatives. Learners are introduced to Derivative Markets, and the means by which the most common forms of derivatives (Forwards, Futures, Swaps, Options, Swaptions, and Exotics) are formulated. Learners are instructed on the key factors that underlie the valuation and performance assessment of a financial derivative, and the multitude of ways in which practitioners arrive at risk-neutral derivative valuations. Learners are also encouraged to appreciate major recent events within finance, and the impact this had on derivative valuation approaches over time. As part of this, learners are introduced to the latest developments in interest rate markets and the latest developments in derivative valuation techniques.

 

Research Methods in Finance, FI6112, Spring 2021 - 

• Module Lectures (~12mb, .pdf)

 

The aim of FI6112 is to provide learners with a structured framework upon which to conduct research in finance. FI6112 details how research ideas are turned into reality. In keeping with the diverse range of research interests expressed by finance learners, FI6112 course materials explore quantitative and qualitative aspects, as well as a mixture of both. The content incorporates elements of prospective topics, research tools, and effective report writing in order to assist in the individual research process. Learners cover course material related to research fundamentals; such as dissertation structure, report integration, formatting styles, writing styles, sourcing scholarly articles, and timeline expectations. Learners also cover course material relating to niche aspects of the research dissertation process. These include performing basic data descriptions and interrogations, identifying statistical methodologies and research analysis tools, forming research questionnaires, conducting research interviews, and evaluating the adequacy of published academic literature. Report-centred course material is also covered, such as how to imitate the format of journal articles, how to write an effective abstract, how to effectively structure an introduction, and how to conclude a research dissertation.

You can access the teaching materials used in older courses below (further links and details to follow):

 

Financial Regulation, IN6012, Spring 2021.

• Module Lectures (~8.5mb, .pdf)

 

The principal aims and objectives of IN6012 were to examine the nature of financial regulation following the Global Financial Crisis of 2008-2009. Our discussions centred on the implications of the crisis on regulation and supervision in Ireland, the EU, and beyond, encompassing Basel I-III, MiFID II/ MiFiR, and Solvency II regulations. The module also detailed the position of stakeholders in the regulatory process, the importance of regulation in relation to financial stability and consumer protection, and the efficacy of regulatory strategies. The course content also reflected contemporary concerns on how risks inherent in the financial sector should be regulated to protect the interest of the economy and that of wider society. The following topics were covered throughout the class:

• Fallibility of Humans and Money: Arguments for regulation

• Recent history of deregulation & 2008-2009 Financial Crisis

• Recap on 2008-2009 Financial Crisis & Consequent Regulatory Considerations

• Dodd-Frank and the Volcker Rule

• Dark Pools

• European Debt Crisis & Basel Frameworks

• Regulatory Oversight in the EU: The case of EIOPA

• Solvency II & Regulatory Reviews

• MiFID I & II, & US Arguments

• Principles vs. Rules-based Regulations: The Case of LIBOR & Compliance

• Consumer Protection