MSIN999: Alternative Investments

Overview

In a time marked by significant fluctuations and uncertainties in both institutional and personal investment landscapes, it’s crucial for investors to expand their horizons beyond conventional investment options like stocks and bonds.

The notable rise in gold prices serves as a prime illustration of the efficacy of alternative investments. This course delves into the realm of alternative investments, ranging from hedge funds, private equity, islamic finance, NFT, and venture capital, to real estate and commodities, demonstrating their potential as instruments for financial growth.

By blending theoretical knowledge with practical application through empirical exercises, this course offers you the opportunity to acquire hands-on experience in the field of alternative investments. You will learn to discern the return-risk profiles of various alternative investments, understand their attractiveness, interpret relevant technical literature, and devise a portfolio incorporating these assets.

Engaging in interactive sessions that provide practical experience with data, you will put theory into action by tackling real-life scenarios. This includes assessing investment portfolio risks, conducting analysis on a leveraged buyout transaction, and evaluating the financial success of a venture capital investment.

Key Information

Prerequisites: Basic mathematics and statistics. MSIN0104 Introduction to Quantitative Finance .

Level: MSc Level.

Lectures: 22 hours

Classes: 10 hours

Learning Outcomes

By the end of the semester, you will be able to…

  • Understand the risk-return profiles of various alternative investment types.
  • Apply the concepts taught in the course to assess the risks associated with diverse investment portfolios.
  • Determine the alpha values for different hedge fund strategies.
  • Analyse and assess the viability of leveraged buyout and venture capital deals.
  • Ready to go further and take CFA/CAIA certification exam and beyond.

Accessibility

If there is any portion of the course that is not accessible to you due to challenges with technology or the course format, please let me know so we can make appropriate accommodations.

The UCL is an inclusive learning environment, and we aim to enable all students to study as independently as possible during their time here. For more information: Support for disabled students

Textbooks

While there is no official textbook for the course, we will be assigning readings from the following textbooks.

Assesments

  • This course is delivered through a combination of lectures, class discussions and readings. As part of classwork, students will be encouraged to work with data, using Excel and Python, to apply the theory to real-world scenarios.

  • The course is assessed through three different examinations methdods.

    • One mid-term examination (20%) and
    • End of term presantation (group or individual) (20%)
    • One final examination (60%).
  • In preparation for the examinations, students will be given problem sets throughout the course each week, the solutions to which will be discussed in class.

Presentation

The purpose of the project is to apply what you’ve learned throughout the semester to analyze an interesting, data-driven research question.

Important dates

  • January 9: Lectures begin - Everyweek on Tuesday -09::11 at AAA
  • January 22: Regular class meeting schedule begins - check your tabula!
  • February 20: Mid-term exam (20%)
  • March 21-24: Presentation (20%)
  • May 30: Final exam (60%)

Information about when terms start and end and when UCL is closed for the holidays during 2023-24. Click here for the full UCL academic calendar.

Five tips for success

Your success on this course depends very much on you and the effort you put into it. The course has been organized so that the burden of learning is on you. Your TAs and I will help you be providing you with materials and answering questions and setting a pace, but for this to work you must do the following:

  1. Try to solve all problem sets before class.
  2. Ask questions. As often as you can. In class, out of class. Ask me, ask the TAs, ask your friends, ask the person sitting next to you. This will help you more than anything else. If you get a question wrong on an assessment, ask us why. If you’re not sure about the methodology, ask. If you hear something on the news that sounds related to what we discussed, ask. If the reading is confusing, ask.
  3. Read. Do the readings. Not just text book but real word examples from newspaper, journal, novel, financial history.
  4. Apply your knowlodge, skills, and patient to problem sets. Do it alone then ask later. Force yourself.
  5. Don’t procrastinate. If something is confusing to you in Week 2, Week 3 will become more confusing, Week 4 even worse, and eventually you won’t know where to begin asking questions. Don’t let the week end with unanswered questions. But if you find yourself falling behind and not knowing where to begin asking, come to office hours, and let me help you identify a good (re)starting point.