Marco Marchioro

Learning Quantitative Finance with QuantLib

Welcome to my personal website

This website is being dismissed at the end of August 2016. 

Please refer to the new and improved website

A brief website map:

  • The Advanced Derivatives page contains material for lectures I give at the Milan University-Bicocca
  • The White Papers page has links to the latest version of my public papers
  • The Conferences page contains links to my recent seminars and guest lectures
  • The Thesis page contains a brief summary of my student's thesis and dissertations
  • The Links page has a list of useful links to interesting websites related to me
  • The Contact Me page can be used to send your feedback to me

Curriculum Vitae

This is my most-recent curriculum vitae. The latest variations on my job status can be found at the public profile on my Linked-in page

Quant Island

Since the summer of 2013 I moved to Singapore with my family and started “Quant Island” a quantitative-analysis consulting firm providing expertise to companies worldwide. The new firm will focus on creating new models for pricing functions, risk analytics, and performance measurement tools. Also, I will perform in-person and web training on advanced topics in quantitative analytics: risk modeling, fundamentals of derivative pricing, and fixed-income attribution for both performance and risk. If you would like to work with Quant Island, please let me know on my contact page.

In this role also acts as Chief Research Advisor of the StatPro Group. 

Learning Quantitative Finance with QuantLib

Most people start to use QuantLib after they become familiar with Quantitative Finance, usually because they want to become involved in the quant community.  In recent years, thanks to the excellent work done on the QuantLibXL add-in, it is possible to start using QuantLib even without having any programming experience. Hence, it makes a lot of sense to learn Quantitative finance and QuantLib at the same time.

On the QuantLib website you can read

Students could master a library that is actually used in the real world and contribute to it in a meaningful way. This would potentially place them in a privileged position on the job market.

This is not the only reason why a student should learn QuantLib, I can think of few more reasons:

  1. QuantLib can be installed on your computer in minutes and used with a spreadsheet without even installing a compiler
  2. Using the SWIG extensions it is possible to use QuantLib from languages different from C++: for example Python
  3. QuantLib contains some pretty-advanced C++. People already familiar with one of the SWIG versions of QuantLib can use QuantLib to learn C++

I am sure you can think of other reasons, drop me a line if you want to share them with me.

Teaching Quantitative Finance with QuantLib

After more than ten years as a professional researching and writing software for pricing and risk management of exotic financial instruments, I finally had the opportunity to share part of my knowledge with the students at the University of Milan-Bicocca in the Advanced Derivatives class.

In recent years I had already been doing internal training at StatPro using that terrific instrument that is QuantLib and in particular using the QuantLibXL add-in, hence, it became very natural to write the class material using many of the tools that QuantLib offers.

I created this website primarily for my students, however, I soon found out that many more people were interested in learning (or teaching) Quantitative Finance using the same tools I used. I want to share the material that I use in class so that it might be useful to other people.  Please provide feedback to help me to improve the lectures.

There are a number of reasons for which QuantLib should be used for teaching actual classes:

  1. QuantLib is free: neither students nor teachers need to pay any fee to use it.  Particularly in this economy when budgets are being cut left and right it is important to cut teaching costs as much as possible.
  2. QuantLib is for beginners and advanced users. Since QuantLib contains the basic building blocks of any financial library (e.g., day-count conventions and Black-Scholes formula) to the most advanced algorithms (e.g. Libor-Market Model), it can be use to teach introductory as well as advanced classes
  3. QuantLib is used by many companies around the world. Students can learn something that are likely to find in their actual work environment. It is a known fact that many companies use QuantLib (sometimes without telling anybody about it) and that bits of QuantLib code have been found in the biggest financial institutions and even in central banks. 

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