Quant Marathon reviews
I did the Marathon in 2018. I believe I was in the first or one of the first cohorts to finish the Marathon. There were some minor technical and organizational glitches, nothing serious. The program was nicely structured with live instructors. There was some possibility for (on-line) networking with other students and of course access to the lecturers for discussing the topics and homeworks. The program was demanding, with a lot of sessions and homeworks. You must keep this in mind, especially if you have a full-time job. The exercises were done in Matlab/Python. I used the Marathon also as an introduction to Python. A small negative experience here: there was an introductory Python course and the lecturer was hard to understand. That was an exception - although most of the lecturers were non-native speakers, I usually had no problem understanding them. I guess in principle you could learn most of the stuff by yourself going over Attiio’s book (Risk and Asset Management). You would miss some of the more modern parts (machine learning etc), access to the code and lecturers. Also, it pushes you to stay at it – I don’t think I would be able to bring myself to go over the stuff in this intensity. The Marathon fees were paid by the company I work at. For me it was also possible to do the sessions/homeworks partly at the office (all the lectures were live, but maybe this changed meanwhile). So, to answer the question, yes, given my remarks above it was worth it for me to do the Marathon.
I had taken one course of the quant marathon back in 2019, and would say it's completely worth it. I would have taken the whole suite of courses if I had more time. One aspect I really enjoyed were the zoom sessions with breakout rooms. They both helped from a learning perspective, as well as providing a sense of being in a “classroom” with other people. The material was very interesting. The contents are quite complementary to what you would find in standard finance textbooks. I have a masters degree in mathematical engineering, and have taken courses in financial maths. Despite being familiar with some aspects of the material, there were still a lot of topics which I could dig into more. The online forum is especially useful in case you have any follow up questions regarding material in the lab you have not understood well. I personally would have preferred having a textbook instead of the lab, as I am more used to studying with physical objects instead of online material, but maybe that’s because of my age. However, just having the material online was not an issue at all. So overall, yes, go for it, its completely worth it!
I have participated in the first two courses of the Marathon; Data Science for Finance and Financial Engineering. The reading material organized in the lab is self-contained and very accessible with cross references that makes it easy to navigate around, so you don’t need any old books for support. The downside (if you don’t buy unlimited access to the lab) is that after finishing the course, you won’t have access anymore so if you don’t have photographic memory, take good notes. There is an extensive code library with code underlying examples, figures and exercises which I found extremely helpful since I also used the courses for getting started programming in Python. Every week there is homework which is reviewed and graded if submitted. I found that the level of these exercises varied a lot – some weeks I had to spend a lot of time while other weeks the questions were at a level much lower than the material taught. I definitely found it worthwhile to participate but be aware that it is quite time consuming because the material covered is rather extensive, especially for the Data Science course. I also followed the math and Python refresher, but in my opinion that was at a much lower level than the actual courses.
I took the ARPM Quant Marathon program last year and I can tell that it was totally worth it. It was a wild (and tough) ride but I enjoyed it. The thing I liked the most was the large amount of topics covered in the Lab (where you have all the study materials). Every aspect was detailed and well explained and I really appreciated that every “chapter” was filled with examples and code snippets to test (mainly on Python); this comes handy if you are keen on coding and learn better by examples than reading theory. Another interesting aspect was the Q&A forum where students helped each other and shared their thoughts; this was really useful in my experience because the personnel inside ARPM provided clarifications and answers to the most technical doubts I had. Since I took the Quant Marathon program, I have noticed that they have broadened their offer giving more flexibility to the students in terms of courses to follow. At that time we had four courses to follow but now there are seven. In terms of how the program is structured, most of the material revolves around the concept of the “Checklist”: a simple set of steps from data management and handling to financial engineering/modelling to portfolio risk/return management. It helped me a lot to have a guideline to follow gluing together all the material in the Lab. This is by far the most complete program I ever took and I totally recommend it.
From my experience, I can tell the ARPM Quant Marathon is totally worth it and I definitely benefited from the program, which I attended in 2018. The program is built on the “Checklist”, which is the basis theory around which all the extensive program is coherently structured. The learning experience is very detail-oriented and based either on rigorous mathematical and statistical theory and practical applications through lines of codes, which are one of the things I value the most. Practical assignments are scheduled and graded every week. It is a great moment to put in full practice the theoretical concepts that you learn as you progress with the Marathon. Everything is well documented from theory to pseudo-code. The way the program courses are implemented gave me a unique and solid framework on data science, risk management and portfolio management with lots of practical implementations to learn from. I also refined my coding skills, either in Python and Matlab, in numerous ways from writing pseudo-code to full implementation. Attilio Meucci is an absolutely terrific instructor and he is able to transfer his passion and vision of his work through his lectures. The program is complete and definitely brings value to your quantitative finance skills.
I signed up for the ARPM Quant Marathon program in fall 2020. I know some of the other contributors to this thread from the flipped classroom sessions that are part of the ARPM Quant Marathon. The ARPM Quant Marathon deals with both tough theory and how to bring the theory to use for a company’s investment and risk management activities. The math and the models in the courses close the gap between the purely theoretical approach of the mathematical academics (which is sometimes a bit rigid and far from reality) and the application-oriented approach chosen by some economists (that is sometimes a bit sloppy). The courses combine the best of both worlds. The central subject of the ARPM Quant Marathon is a framework that gives you guidance through all quant activities (the enumeration is not complete): Identify suitable risk drivers, choose a suitable mathematical model to describe the joint distribution of the risk drivers, estimate the model with historical data, project the risk drivers to your investment horizon, evaluate possible portfolios, construct and execute an optimal trading strategy. Here is one remark on the depth of mathematical formalism. If you don’t have the mathematical skills of a graduated mathematician, schedule a bit more time to penetrate the material. The math is really on master level. Personally, I really enjoy the program and I would sign up again.
I have signed up for the ARPM Marathon programme since Sept 2020 and I regard it as a highly valuable learning experience. The course week designs are well-balanced with extensive quantitative techniques. The first part focuses on data science for different financial instruments. After massaging the data, the second part concentrates on financial engineering, risk management and portfolio management at aggregate levels. A big plus is the machine learning applications on finance, up to date. I feel the examples and case studies are particularly supportive to understand the modelling. The course structure provides concise and clear visions about quantitative techniques on financial markets. A new course week starts every Monday, the online classroom begins on Thursday, and on Sunday the homework will be handed in and graded by the tutors. Homework is divided into theoretical and empirical parts. I enjoyed the online class sessions very much. Some puzzling problems are solved easily during the discussion sessions meanwhile the tutors are well-informed and down to earth. Many classmates are industry practitioners, their opinions and views expand visions. A variety of codes for Python applications are ready, one of the top features for constant practices. The email reminding system really reminds you of the intensity of this programme, time management is crucial, make sure you don’t skip any course week. My background is economics. The understanding of econometrics is certainly helpful, but it took me time and effort to catch up with postgraduate level mathematics and statistics. With diligence and determination, surely you will feel rewarded!
I’m currently enrolled in the Quant Marathon for 2020–2021 and have had an excellent overall experience. It isn’t easy and is not meant to be – so if you do decide to enroll, please prepare to put in the hours because that’s also the best way to maximize what you get out of the programme. In terms of what’s useful, there is no shortage of things that you’ve seen or that you’ll come across in finance – from generating correlated random variables to understanding time series analysis to derivatives pricing and calibrating implied volatility surfaces. You will definitely find something that you’ll want to understand in greater depth and the ARPM Lab will have enough material to keep you occupied and satisfied. Speaking of examples, there are plenty of worked examples and code available in the ARPM Lab that you can work through line by line – I found this to be extremely helpful. Downsides – the math can be very involved, and in some cases, I found the material to be too technical for me. This is where I found the worked examples to be particularly useful – if I couldn’t grasp the theory entirely, I would at least be able to understand the application. I signed up for the 12-month Quant Marathon course and am nearing the halfway point of the older version of the programme (the Data Science for Finance and Financial Engineering modules came first; I’ll be starting on Quantitative Risk and Portfolio Management in a few weeks). Truth be told, I’ve had a look at the newer programme and I’d definitely benefit from the Data Science Mathematics module - the ARPM is ever-evolving and upgrading. I paid for this course out of pocket, and don’t regret it one bit. I’ll be signing up for continued access to the ARPM Lab as well once I complete the Marathon.
From first hand experience, ARPM Quant Marathon is a very unique learning experience, even in an age of ever expanding options for on-line training and courses. Really a work of vision and passion, rather than a conventional subject-based on-line course from a professional professor. Prior to enrolling in the ARPM marathon I took Attilio’s risk management course at NYU Courant. I can see that he and team have spent many years since publication of his textbook (the basis for the Courant’s course) developing and evolving a grand unified theory, if you like, of risk management and portfolio analysis. A full coherent vision of quantitative financial risk management and portfolio optimization is presented, complete with extensive coverage of relevant quantitative foundations starting with the fundamentals such as linear algebra and functional analysis, all the way to more modern subjects such as machine learning. The consistency and coherence of the presentation (including notation) allow the various topics to re-enforce each other and connect in wonderful ways. Add recorded and live lectures, full implementation and data illustrating selected case studies. fully documented libraries in python, R and matlab, active Q&A forums, and graded homeworks, and you end up with, as I said earlier, a really unique and valuable learning experience. I see more recently that ARPM has started to package the quantitative foundations course of the ARPM program, which is substantial, as a separate data science offering. This would also be a worthwhile series of courses to take in its own right. The amount of material is quite extensive, and obviously what you will get will be proportional to the effort you put in. This is not an educational program you can enroll in casually, even if you come to it with relevant experience. My pet peeve regarding the program is that you couldn’t print any of the material out. As a die-hard paper and pen (and highlighter) learner, I found that challenging. So, in conclusion, yes, very much worth it.
Hi , I took the ARPM Quant Marathon in 2019, lasting one year and I can share with you my personal experience. First of all, I can confirm that it is really worth it. The fundamental aspect to take into consideration is that it provides you a complete framework (a real toolbox) which allows you to gain a deep knowledge of each quantitative finance subject covered (Data Science, Financial Engineering, Risk Management, Portfolio Management, etc.), putting all the theory into practice. Indeed, the following are just some of the learning sources available pursuing the Quant Marathon: you could join online (live) classroom discussing with lecturers and other students, you could watch the video lectures, you could do the weekly homework (which will be graded), you will have access to the forum where you can post (and reply to) any question, you will have full access to the ARPM Lab. Focusing on the last point (ARPM Lab) it consists of thousands of pages of theory properly organized, accompanied by practical case studies and data animations, but most important thing is that everything is reproducible through the code (Python in particular) easily accessible and deeply documented (pseudocode and comments line by line with references to the theory section). You could also create your own Python scripts. All these sources are coherent, consistent and linked among each other. This is to say that from a personal point of view you will gain a very distinct competitive hedge in terms of knowledge (and you could demonstrate it during the interviews and most important during your daily job). In addition I can tell you that in the last few years the ARPM has become more and more known and spread (I also noticed this from my network of contacts on LinkedIn). The possibility to write in your CV that you had Attilio Meucci (well known both by academic people and practitioners) as lecturer is an additional competitive edge (and this will increase the probability your CV will enter in the short list of the interviewers). Finally, I want to stress the fact that this is a real master-level quantitative finance course and not only a certificate.