Course Spotlight - ME200: Computational Methods in Financial Mathematics

We sat down with Francesco, who took ME200: Computation Methods in Financial Mathematics, to hear about his experience of the course. 

 

Why did you decide to attend LSE Summer School?

I thought the possibility of studying at one of the most prestigious universities in the world would contribute to widening my horizons and perspectives about my future, and it really did.

Why did you choose ME200?

I sincerely believe that in a financial sector that is relying more on data and gradually moving toward AI, it is essential to enhance one’s ability to interpret numerical inputs, and link these to the creation of dynamic models able to deal with continuously changing economic scenarios. ME200 addressed these and combined aspects of computational finance with their practical application in Python, which I was really interested in.

Tell us about an average day as a student on ME200.

The experience is short but intense since a whole module is compressed into three weeks of classes. However, the extra-curricular experiences offered by Summer School helped to make an average university day different from the ordinary.

What was your favourite part of ME200?

I really appreciated the derivation of the Black Scholes Option Pricing model from the Binomial Model. Both Professor Veraart and Professor Ruf made the complex issue easy to understand and fun to discuss.

What advice would you give to students considering ME200?

My advice is to focus on both sides of the course, the theoretical and the practical. Having a clear understanding of what is happening on a theoretical level makes the practical application even more stimulating. So, my suggestion is to enjoy the course in its entirety and I assure you that the learning result will be outstanding.

What are your short-term professional goals, and how does ME200 contribute to these goals?

I dream of a career in finance, and alongside the relevant financial topics covered, the course was able to give me profound insight into the use of programming in designing investing strategies and hedging activities, a more concrete approach often left behind during the traditional university study.

Was meeting and talking to other students on your course easy?

Absolutely, the atmosphere was great and a sense of desire to meet new people was shared by all the students. Being able to respect the culture and habits of other people represents a fundamental skill that permits everyone to build long-term friendships and no one in the class lacked it.

How would you explain ME200 to someone who has never heard of it?

The course is divided into two parts. The first part explores the statistical background behind the financial models explained in the second part. The Python application of both statistics and finance is parallel during the whole course. Lectures in the morning are accompanied by classes in the afternoon in which LSE PhD students help Summer School students with exercises and answer questions. The main topics covered are the Monte Carlo technique and the derivation of the Black Scholes Option Pricing Model.

How did you find the course and teaching experience at LSE?

The course was perfectly structured. The first part, presented by Professor Ruf, provided a clear overview of the basics, which was crucial to understanding the more complex models presented in the second part by Professor Veraart. Moreover, dedicating the last hour of the lecture to Python permitted students to immediately see how the concepts just explained are applied in the programming system.

How will the course contribute to your longer-term goals?

The course gave me the opportunity to experience LSE in its entirety, with its excellent professors and international environment. Moreover, being in touch with this level of excellence has changed my perspective about the future, convincing me to apply for the Master’s Degree at LSE with the hope of starting my financial career in London.