Computational Finance and Risk Management (minor)

Minor in Computational Finance and Risk Management

Computational Finance and Risk Management lies at the intersection of finance, probability and statistics, optimization, and scientific computing. This minor equips students with the conceptual, quantitative, and programming skills needed to model, price, and manage risk in modern financial markets.

In a financial system characterized by uncertainty, digitalization, and increasing regulatory scrutiny, the ability to understand and control exposures to market, credit, liquidity, and operational risks is essential. The curriculum introduces the foundations of financial economics—including the time value of money, arbitrage, asset pricing, portfolio theory, and
factor models—as well as key financial instruments such as equities, fixed-income securities, and derivatives. Building on this foundation, students study core methods in mathematical and computational finance, such as stochastic modeling of asset prices, derivative pricing (e.g. Black–Scholes, Heston), risk measurement (Value-at-Risk, Expected Shortfall), stress testing and scenario analysis, and the design of hedging and risk-transfer strategies.

A central feature of the minor is its emphasis on computation and data. Students gain hands-on experience implementing models in languages commonly used in finance (such as Python or R), applying numerical optimization, Monte Carlo simulation, and time-series analysis to real or realistic financial data. Selected topics in financial technology—such as algorithmic trading, digital financial platforms, and data-driven or machine-learning methods for forecasting and credit risk—demonstrate how quantitative tools are deployed in contemporary practice.

The minor is designed for students in mathematics, statistics, economics, computer science, engineering, and related fields who wish to complement their primary studies with rigorous training in quantitative finance and risk management. It provides solid preparation for entrylevel
roles in risk analysis, quantitative research, asset management, and financial technology, as well as a foundation for graduate study in financial engineering, quantitative finance, or related disciplines.

Upon successful completion of the minor, students will be able to:

1. Explain core concepts in finance and risk management
   
   Explain foundational ideas such as the time value of money, arbitrage, asset pricing, portfolio theory, derivatives, and the main categories of financial risk (market, credit, liquidity, and operational).
2. Formulate and analyze quantitative models of financial risk
   
   Apply mathematical and statistical methods—including probability, stochastic processes, time-series analysis, and optimization—to model asset prices, portfolios, and risk exposures, and to support informed investment and risk-management decisions.
3. Evaluate financial instruments, markets, and strategies
   
   Understand and critically assess the structure, use, and risk–return characteristics of major financial instruments (equities, bonds, derivatives), markets, and investment or hedging strategies within a risk-management framework.
4. Use computational tools to solve financial problems
   
   Demonstrate proficiency in implementing and calibrating financial models in a high-level programming language (such as Python or R), using numerical, simulation-based, and basic data-science or machine-learning techniques to analyze financial data.
5. Measure and manage financial risk quantitatively
   
   Apply quantitative techniques—such as Value-at-Risk, Expected Shortfall, stress testing, and scenario analysis—to assess and monitor risk at the level of individual instruments and portfolios, and to evaluate alternative risk-mitigation strategies.
6. Communicate and collaborate effectively
   
   Work effectively in interdisciplinary teams and communicate complex quantitative financial analyses clearly, both orally and in writing, to diverse audiences including investors, managers, and regulators.
7. Recognize regulatory, ethical, and sustainability dimensions of risk
   
   Identify key regulatory and ethical issues in financial risk management, appreciate the limitations of quantitative models, and reflect on the responsible and sustainable use of financial engineering tools in practice.

The minor consists of 15–20 credits of compulsory core courses and 0-10 credits of optional courses from two subject areas (i) systems and operations research, (ii) computational methods.

Code: SCI3170

Extent: 20–25 ECTS

Curriculum: 2024–2026

Level: Advanced studies

Language of learning: English

Theme: Global business dynamics

Target group: All Aalto students

Teacher in charge: Mikko Jääskeläinen Ruth Kaila Ahti Salo

Administrative contact: Tarja Timonen

Organising department: Department of Industrial Engineering and Management

School: School of Science

Prerequisites: The minor requires basic knowledge in engineering mathematics and probability theory. Bachelor-level minor SCI3034 Systems Sciences is recommended.

Quotas and restrictions: No quotas for the minor, but some elective courses may have space for a limited number of students. The minor is available for master’s level students.

Application process: Open for all students of Aalto University. It is recommended that the student discuss the choice of courses with Ruth Kaila.

Content and structure of the minor

About the minor

Description of the minor

Welcome to the Minor in Computational Finance and Risk Management, where principles of managing financial assets intersect with the study of uncertainty. In the landscape of the finance, understanding and effectively mitigating risks is paramount. This minor provides you with a specialized and comprehensive exploration of the strategies and tools employed to identify, analyze, and manage financial risks.

From market volatility to credit uncertainties, financial risk management is a critical discipline ensuring the resilience and success of businesses and organizations worldwide. The curriculum will engage you with topics ranging from mathematical finance and stochastic modeling to derivative pricing and asset management. The program emphasizes the development of programming skills and the understanding of quantitative analysis tools, ensuring that the students are well-prepared to tackle the complexities of risk in today’s financial environment.

You might be interested in Fintech and exploring the power of technology in reshaping traditional financial services. In an era defined by digital disruption and rapid advancements, the minor offers students a unique opportunity to understand, harness, and drive the digital evolution of finance. Whether aspiring to pursue a career in risk analysis, investment banking, asset management, or financial technology, the Minor in Computational Finance and Risk Management equips you with the expertise needed to thrive in a world
where traditional financial practices are continually challenged by technological advancements. Join us in exploring the convergence of finance and engineering in tomorrow’s global financial system.

Intented learning outcomes

After completing the minor, student can:

1. Understand foundational concepts in finance and financial risk
   management, including asset pricing, risk management, portfolio theory, and
   derivatives.
2. Apply quantitative methods, such as mathematical modeling and
   statistical analysis, to assess financial risk and make informed investment
   decisions.
3. Understand and critically evaluate various financial instruments, markets,
   and investment strategies within the context of risk management.
4. Demonstrate proficiency in utilizing computational tools and techniques to
   analyze financial data and solve complex financial problems.
5. Develop programming skills in languages commonly used in finance, such
   as Python, R, or MATLAB, to implement financial models and algorithms.
6. Collaborate in interdisciplinary teams to solve real-world financial
   problems. Communicate effectively about complex financial concepts and
   analyses to diverse stakeholders including investors, managers, and regulators.

Content description

The minor consists of 15–20 credits of compulsory core courses and 0-10 credits of elective courses from two subject areas (i) systems and operations research, (ii) computational methods.

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Content

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