Topic outline

  • Why take this course in Investment Science?

    Investment science refers to the application of mathematical modelling to inform investment decisions. This course is focused on financial investments, including investments into securities such as bonds and stocks and derivative securities such as forwards, futures, swaps, and options. 

    The analysis of investment decisions requires a sound understanding of cash flow dynamics, stochastic processes, pricing, and valuation of investments. This course gives a well-rounded introduction to all these topics, thus ensuring that the students master these fundamental concepts of investment science and are able to apply them successfully in practice.


    Taking this course in 2023

    We welcome you to this course which is taught through normal lectures and exercise sessions.  The first lecture will be held on 4 September at 10:15 in lecture hall U3 (Otakaari 1).

    The topics of the course include:

    • deterministic cash flows (e.g. net present value, interest rate analysis)
    • single period random cash flows (Markowitz mean-variance portfolio theory, capital asset pricing model)
    • derivative securities and investment hedging
    • multi-period random cash flows (discrete and continuous)
    • arbitrage pricing theory and risk-neutral valuation
    • pricing of options and real options, and the Black-Scholes equation


    Learning Outcomes

    The student has a good understanding of the critical concepts and methods of investment science, including topics such as interests rates; cash flow analysis; Markowitz's portfolio theory; capital asset pricing model; arbitrage pricing theory; forward, futures and options contracts; pricing of options; hedging; interest rate derivatives; interest rate dynamics. 

    The student is able to formulate and solve problems involving financial instruments. The student has a strong foundation for pursuing advanced studies in financial engineering and quantitative finance. 

    Upon completing this course, the student should be able to:

    • understood how several important concepts arising from diverse fields involving investment decisions;
    • familiarise themselves with concepts and process common to investments;
    • know the main techniques for modelling and handling investment problems and how to apply them successfully in practice;


    Textbook

    D.G. Luenberger: Investment Science, Oxford University Press, 1998 (or newer editions).


    Zulip Link

    https://investiment-fall-2023.zulip.aalto.fi/join/2z43mca2aijevsbmdwvxyhmm/


    Grading

    The course is graded on a scale of 0-5 based on a Final Exam (65 %) and homework (35%). 

    The homework consists of 8 assignments and 11 exercises that will yield at total of 35%. Details about grading and schedule can be found in the 

    The course may feature activities that will reward extra points. You will be notified of these arrangements if this is the case. These points will be appropriately added to the total course points.

    The points are valid until the start of the next course.

    Course staff

    Lecturer:  Fernando Dias (forename.surname@aalto.fi)

    Assistant: MSc Leevi Olander (forename.surname@aalto.fi)
                    BSc Jaakko Wallenius (forename.surname@aalto.fi)

    Reception hour:
    Lecturer:  Wednesdays at 15:00 - 16:00 in room Y214 (Otakaari 1). Please confirm the appointment by contacting via email first.