The time-series videos are moving towards the actual model building process on data. I also plan to do a credit model in the future however it takes a lot of time to engineer data for these projects. I will try to create more applied videos in the future though. I think it's important to understand that model development can take anywhere from 1 month to a year and a half. It's challenging to condense that into a video however I will try to convey the process through a series of videos. Then to validate a model takes usually another 3-6 months. This is a banking perspective though. The trading world would move a bit faster due to timing issues of the market. Thanks for the feedback!

Sorry for typos, I hate typing on phones

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A CS and Math dual major would be a great start! For a quant finance career, employers really care about the graduate degree and not so much the undergrad as it was a stepping stone to the grad degree. If a good grad program accepts you, companies assume your undergrad was good enough. As for Masters vs PhD....that's a really hard and personal question. PhDs are preferred however they take longer to get (5-7 years) however if you are bright it should be free. A masters is quicker however it costs a lot of money and isn't as desirable as a PhD. At times I wish I would have done a PhD instead of a Masters due to my passion for research and learning. The masters did save me time and I was able to get going on my industry career much quicker. It really comes down to personal preferences.

Just seen a link to video where I think you might have answered the first question at the very least. I'll pop over to that video and check it out! ;-)

No need to reply. I think I've got the answer from some of the earlier videos you've posted.

I'll provide some short answers here as well just for clarity. The FRM is a good high level view of risk. I was hoping it would help career wise however not many people care about it. One reason might be because it lacks a lot of depth. From a quant perspective it is nice to see the entire risk spectrum as many of us get too focused in one area. Overall though it isn't too useful for quants unless you want to be a manager. For switching degrees...it came down to a few reason. 1) I could have finished the degree however I spent too much time memorizing and not learning. I was behind on math which contributed to this issue however most of the other students were doing the same even with math backgrounds. 2) The program was having students take double the classes compared to other masters programs. Too much material in too short of time results in poor learning. 3) The program was closing the year after my class finished. This means no one would have heard of the program a few years after my graduation. This hurts your networking opportunities in the future. (My program no longer exists. There is a new program which is better now though.) 4) Since I was behind on the math, I wanted to take masters level math courses to help catch up. The program would not allow me to take masters level math courses. I had the option to take PhD level courses only which is odd in my opinion. The applied economics program had fewer core courses and allowed me to take masters level courses across different departments (math, stats, and CS). This allowed me to better tailor my degree to what I wanted to do. I don't think any one reason alone was responsible for my decision but due to a variety of issues combined, it looked better for me to switch programs. Luckily I was able to use my MFE courses as electives and a specialty for my degree. The applied economics department required students to have some sort of focus and mine was financial engineering. Many students specialized in economics, econometrics, or public policy.

I don't know of any specific trading books however I like the book linked below. It shows how to apply statistics to a variety of finance problems. I still reference this book for my day job. Statistical Analysis of Financial Data in R (my affiliate link) amzn.to/2UisOsp

If you are more interested in finance, then I would try to find a more traditional finance job (corporate finance or operations research). The jobs are so different (at least in the US) that there is rarely ever someone who works in one area and then later switches to the other side. Investment banks do hire engineers and other bright people and then train them to do traditional finance (like M&A).

A statistics degree would be the best out of the options you provided. An MSF is really another business degree with slightly more analytics.

Dimitri Bianco Thank you for the advice. Also, would it be impossible to get into the Quantitative industry if you took an MSF?

Your first job will usually set the course for your career. If you want to end up in trading (HFT) firms in the long run, I would take the HFT offer. It's a lot easier to move between companies than it is to move across job types (HFT vs risk). Small firms usually offer more hands on learning which is also a big benefit.

@@DimitriBianco one last thing. People have told me that it doesn't make sense to reject an offer from one of the biggest investment banks as a starter. What's your take on that? For better context, I also did an internship in risk at this bank during my masters so I already have it on my resume.

When you say "risk analyst" are you referring to a model developer position? The reason I ask is there are non-quant risk jobs as well as quant risk jobs at investment banks. Assuming the risk analyst job is a model developer (quant job), it really comes down to what career you want to have in the long run. I work on the risk management side at a bank and have worked at a variety of banks from regional to one of the largest in the world. I like risk management because the job is steady and the work is more focused on deep analytics instead of speed and market fluctuations. The work load is reasonable and most of the people I have worked with are nice. Now that being said, if I wanted to jump over to a hedge fund, it would take a lot of networking and most likely a step back career wise to be able to switch careers. HFT jobs are less stable (especially small firms) however the work is fast and exciting. HFT (assuming it's a hedge fund) can do proprietary trading and have less regulation making the job more dynamic and fun. The stress will be high though as you are dependent on the markets. Now for bank name recognition...this is a bit different in the quant world. When I was I finance student and when I had interactions with the MBA students it was a big deal to work for a firm such as Rothschild, Jefferies, or Goldman Sachs. Also having worked at a "bulge bracket" bank meant you would get great training and a lot of opportunities. On the quant side it is a bit different. Almost every bank I have seen does not have official training programs for quants. You are typically assigned easier work and work with a manager who will help guide you. I even spoke to a variety of banks last year on education and training (at a risk conference) and they were asking how to best train quants as almost none of them have actual programs. Now the size of the bank does have some impact. Larger banks have more levels and more people so it is more likely to get promoted. If you make it to the senior management level (director or executive) the pay is typically higher than smaller banks as they have bigger budgets. However this entire discussion is a comparison of banks based on size which excludes trading firms. HFT (again assuming a hedge fund) is a completely different industry and area. With a career on the trading side you could work at a small fund for a year or two and then try to jump to a larger more stable firm like 2 Sigmas or Citadel. Most quants also don't view large banks as more prestigious. It's fairly easy for a model developer to work at a small regional firm this year and then move over to Citi or JP Morgan Chase next year. Now if that same person wanted to jump to a hedge fund, it would be a big challenge.

@@DimitriBianco That was very helpful. Thank you. Let me tell you about the role. During my internship I was given the task of developing a few credit VaR models and building statistical justification for the models to counter a few issues raised by the model risk team. I was also tasked with fitting a diffusion model to the data for segregating them before model development. I had a lot of people from math/stats/physics around me but there were also a few MBAs and CFAs with a lot of work experience.

@@DimitriBianco So you're saying brand name doesn't matter much. I wanted to hear it from someone qualified. Your opinion means a lot to me. Thank you.

Quant finance is a lot of math, stats, and CS which are all built in layers. What I mean by this is that many skills are built on top of other skills. For example, it's hard to do stochastic calculus without calculus and probability theory. And to do those you need calculus which needs algebra and arithmetic. The best way to improve your skills is to select a topic and focus on that for at least 3-6 months. As you read books on the topic and you come across concepts that don't make sense, it's important to go back a few layers and figure out the underlying material. Memorization is never a good strategy when compared to actually understanding the ideas and theory.

find good research papers to implement and get ideas from

Markets are fairly efficient however they are only as smart as the people trading. I'll make a video on my economic perspectives as many people have asked. Algo trading has driven markets to be more efficient as well which is a good thing thing for the general population.

I would also want to get more information about this

EGE SÖNMEZ go to grad school

The process would be to get an undergrad (sounds like you'll get a physics degree) and then after that you'll need a Masters of PhD (grad school). I would consider a variety of degrees such as financial engineering, statistics, or mathematics. You could continue the physics route for graduate school however it makes getting into quant finance a bit more challenging as your degree doesn't perfectly match. If you do the pure physics route, you'll need to write a resume that highlights the skills you have that are needed in quant finance.

MS FinEng > any MBA for quant role. ACFA is more for traditional financial analyst and I don’t really think employers in more quant fields will care as much for it. Although, if you do already have the quantitative skills (quantitative degree, good projects, etc) then maybe a CFA could boost your chances a little bit. But overall, Financial Engineering masters > MBA + CFA.

@@jairevonhayes5503 thanks for the update...

If you want to go into quantitative finance, I would get the MS in Financial Engineering. Quant finance requires a lot of math, stats, and CS, Even with a masters you will be competing with PhDs for a job in quant finance. An MBA is only good for traditional finance.

@@DimitriBianco thanks sir!!

I don't think age is too important for quantitative finance. I have seen very quantitative people from other fields who eventually end up in quantitative finance. Most people in quant finance care about education and less about age. As for the degree vs learning...they are both required. A masters/PhD is really just the very beginning of a quant career. What you will learn in a graduate degree will just start to give you the basic tools. It takes many years after these degrees to fully understand a specific job. I've been in the industry with a masters for 6 years and I still have a lot to learn. The graduate degree is a requirement as it helps to ensure people have a very basic understanding (from a quant perspective). It might be possible outside of the US to do quant finance without a grad degree however in the US there is a lot of competition and the degrees are required.

I guess it is quite off topic but do anyone know of a good place to stream newly released tv shows online ?

@Dayton Wilder try flixzone. Just google for it =)

I think you are referring to "upper echelon."

Right. He’s being PC cuz he has a KZfaq channel. He knows this.