I agree, my biggest regret was following a generic commerce degree instead of a mathematics degree. My opinion is the generic Business/Commerce degree is the equivalent of an Arts Degree. People do them when they have no idea what they want to do.
Yes, it is like an escape route... people do this cause they can't do medicine, law, engineering, math, physics etc. But they think arts is stupid. So they settle for commerce.
Even for STEM students, getting into quant is hard... To prepare for interview for a quant position, I am practicing problems including stat/probability, math, brain teasers, ml, algorithm and coding. The only way I see a finance student to get a quant job is to double major in math or cs. For a finance student, investment banking fits much better.
Im in the kind of(ish) the same position as you were. Finance major who didnt even get into a finance role after college. Ended up working at a law firm in billing just cus its good money and wanted to save for school. Im finally financially prepared and ready to go back to school now. All i can say is, catching up on everything has been absolute hell. And im only applying to pre-req courses. LOL. Never give up!
I have a PhD in theoretical physics and am self taught in stats, probability, computer programming, and machine learning so I had initially thought this advice would not be relevant to me until he got to the end and spoke about the drivers / motivation. I was motivated by the money, and have no real interest in finance. I am a talented problem solver and can solve those interview questions with relative ease, and although I find those puzzles fun to solve, and mathematically abstract ideas come easy to me, I found I was pursuing this field for the wrong reasons; a fancy apartment in Manhattan, a nice car, and other material posessions. I am now starting to shift my values and beginning to understand that it is not these things that provide happiness thanks in part to the last few pieces of advice given by Fancy Quant. Thank you, Demitri!
Hey, I am intrigued by your comment and ability to learn complex concepts by yourself. I myself am a finance major , however , I have always been a good problem solver and loved puzzles and riddles as a kid. Also, I was very good at math, and probability theory. My high school teacher suggested for me to take an AP class in high school on statistics. Which I did, and I was mediocre in that class because my teacher wasn’t the best and just had RUclips videos teaching us. What a class for an AP student right ??? About two years ago I got invested into the stock market and ever since then I’ve been a stock market junky. I’m more of an investor than a trader but I have taken and closed positions on a much smaller time frame (swing trading, months, weeks). In my free time I’ve developed an interest in learning more about the markets, what participants there are, and how the set of rules both political , and regulatory, effect a position on a certain stock.
I’ve also stumbled across numerous content that covers Algo trading, computational finance, and Quantitative Finance. My only question to u is how did you go about learning all of the things you mentioned above while studying theoretical physics. Seems pretty hard but from your background it sounds like u are very bright and talented to be able to learn with ease. I wish to learn those exact topics but don’t know where to start, what books to read, or even who to talk to. My plan one day is to become a Quantitative trader or analyst. What drives me is the intellectual pleasure of solving problems and the fact that your compensation is a reflection of your performance, and ofc the money that is involved is lucrative and worth the work. I see trading and investing as a skill and art. The better person I am, the better a trader or investor I will be. I like the discipline it takes, and I’ve always been a hard worker. It would mean a lot to me to receive any advice or guidance on my journey. Thank you for reading this and good luck on all your endeavors
Good information. I study machine learning/statistical learning and come from a CS background myself but I do enjoy watching these videos despite having 0 interest in quantitative finance. Just neat to see smart people applying their skillsets to other fields I know nothing about.
Fantastic and genuine advice. Thank you Dimitri! I have a double major in BS Fin and BS math-CS and will head for an MS math. I've worked at "quant" positions during my studies and this is when I discovered that this job/team is where I want to be. I'm an ENTJ, so thanks for bringing in this aspect up as well. Really great video, you inspire me :)
Hello P! Actually I am currently pursuing BE in Computer Science but my interest is in the 'MATHS'. Could you please tell me whether the "quant" role is relatively math Rigorous or not?
15:15 this is so true. Me and my classmate from highschool picked up two different paths. I went for Finance university, she went for Mathematical Engeneering. At the end we end up working in the same Insurance company 😂, i work in the Investment Decision department, she works at the Actuarial Department. So at the end, she calculates scenarios and i decide which one to pick and invest 😂
Very often Finance grads (bus. or economics) are not people who want to spend their whole life into the realm of mathematics modeling or its real life implementation. The quants are not only people who can "read or use" a model, but who tinker it all the time. A very specific skillset who normallly attracts much more the engineers, physics graduates and alike (even some mathematicians don't like the "too applied" aspect of this job, at least as it is normally carried out in banks).
Fantastic video as always Dimitri, I think putting out another day in the life video would benefit a lot of people who are not too sure about the specifics of what quants do!
Hi, Dimitri. Thx for another amazing video here. I have a finance and economics background. The problem I have is that I find myself choosing the wrong major after I graduated. My personality, just like u mention, is more like a quant who like to analysis and stats. I understand that my background is not rigorous compared to that of quant undergrad. So I am wondering could u plz do a video talk about how I should catch up, including like what program should I take or what course should I learn?
Hi Dimitri , Thanks for doing this RUclips channel to explain to us layman what quant is about. I'm an engineer working in the oil field , and was always confused what quant is about. In my home country (Singapore ) , quant finance is only offered to the cream of the crop and only a handful a year . You have to choose maths as a major first , then the university choose you during sophomore year in the National University of Singapore (NUS).
Quantitative finance is applying advanced math and statistical methods to finance. To be able to do so you also need to be able to program as a way to express your ideas and test them out. Quants need a blend of math, statistics, and computer science.
I learned about this to late unfortunately, since I never really had a clue what finance actually was and the careers in this field. As a result I'm going to university for finance bachelor at the moment. Is there still a way to get into quant finance or what would the necessery steps be to do so?
Cant we say that economics is a quantitative field ? We take lots of Math like linear algebra, calculus,differential equations and lots of statistics like regressions hypothesis testings etc. and we took econometrics time series econometrics etc. can we say economics degree that ıve been taken is a quantitative degree? Thanks
This actually depends a lot of the program. Yes, there are economics degrees that are quantitative (I actually have a masters in applied economics). Your economics degree sounds like a quantitative degree. However there are also schools with economics degrees that focus a lot on theory and do minimal math and stats.
Dimitri thank you for this awesome video.. In an earlier comment you said you had a boss with Economics grad degree... I agree with you completely that quantitative finance requires hardcore maths and stats... Thats why i am taking courses on maths, stats and Econometrics... To give you an idea.. I have learned real analysis, metric algebra, linear Algebra, probability theory, differential equations.. Currently studying stochastic calculus.. Not in its full rigour... But learning from basics... On my own.. I have 3 econometrics courses so far from my university... And will take 6 more courses on it.. My university teaches econometrics from wooldridge cross sectional and pannel data, green... I have done time series from enders...on the software side of things i am intermediate in python... Can make apps... R working knowledge... Learning java at present... I am pursuing acturial courses on the sideline... I am already an economics masters student... Will pursue another quantitative economics masters degree.... Probably a phd if family constraints dont come... On the professional degree side i am pursuing cfa... This is my Portfolio till now... Can you please advise me if this will be sufficient for quant job...? My main concern is most of the Mathematical skillsets i have developed on my own... Only the econometrics and acturial courses i can show as the econometrics courses are conducted in my university... Will recruiters give any importance to self studied courses? How do i convince them that i know the stuff? Also is this learning sufficient... Or do u need much more to get started... Thank you for helping me earlier. Edit- I really want to dig into this field.. I know my passion resides here... I have done day trading for 6 months but i stopped thereafter as i want to implement algorithmic trading so currently learning about these... Do you think given my foundation and learning from books like 1. Successful algorithmic trading 2. Advanced algorithmic trading from michael more 3. Machine learning books from marcos prado.. 4. Time series by hamilton Will be sufficient enough for quant job? I have gone through many mfe and financial engineering curriculum and their suggested readings... I am tailoring my learning towards this...i am ready to make all the sacrifice and want to learn about markets...
From what you have provided you seem well prepared. Self learning is good however it isn't taken too seriously however if you have a masters degree like economics and can talk about a variety of areas like math, statistics, and computer science you can usually get an interview and an offer. The key for you will be to write a resume that matches the job description. So for example, if something like R or Python is required, make sure it is listed somewhere on the resume. This will get you past HR's review.
Hey can u share with us the sources you've learned all this by yourself mentioned above like math stats econometrics, linear algebra, etc etc and all the courses you've taken, can u please share this with us
Hi Dimitri, Recently found the channel and I am really enjoying your content. I am also a Michigan Alum as I graduated from Ross with a BBA in 2018. When you applied to the MFE program at Michigan, did you do so with just your Finance background? If so, that's very impressive. With my current Finance undergraduate degree I don't think I could come close to finishing a quantitative finance program. I am planning on applying to Graduate Programs in 2021 after taking 2 semesters of enrichment at the UofM Dearborn campus. I left my full-time job to go back to school and pursue quant finance. Do you think that me going back to school for undergraduate classes is the correct thing to do to strengthen my application for Master's programs? Thank you for your time.
If you are wanting to go into quantitative finance then I would agree that going back for undergrad math class will be helpful. Programs usually don't care too much about the degree as long as you can show that you have taken the courses they are interested in.
Hi Dimitri. First, thanks for sharing this, it's very valuable for those who are pursuing this career. My question is, when you say that you model things, which was the basic knowledge that you learn that make you able to model nowadays? Calculus, Differential Equations, Real Analysis, Linear Regression, and so on? I have an economics background and I would like to make this catching up as you did in your gap semester. Again, thank you for helping dreamers to get there.
It depends on the area you go into but in general understanding linear algebra and calculus 1-3 help you understand the underlying theory of statistics (regression and optimization). To really understand derivative pricing you need math (real analysis, measure theory, and stochastic calculus) as the general principles are built on top of this. For most quant jobs that aren't working with derivative you can get by knowing statistics really well. As you dig deeper though in different areas like time-series you'll end up needing the same math as in derivative pricing. As an undergrad I would focus on the core statistics concepts like hypothesis testing, coefficient estimation (OLS vs MLE), optimization (think neural networks and portfolio construction), linear regression (OLS, Logistic, FGLS, ARIMA), and data science (trees, clustering, dimensionality reduction, and neural networks.....and yes I consider data science a subfield of stats). Along the way you will need math such as what is taught in calculus 1-3 and linear algebra and you'll need to at least be able to program your statistical analysis in a language like R, Python, SAS, Matlab, or SPSS. There is always more to learn but the above should be enough to get you started in a masters. Once you work on a masters or PhD you'll realize there is so much more to learn and very limited time.
Thanks for the video. I was wondering if it would give one a comparative advantage to do quantitative finance but work in the world of general finance. The rationale is that one could be a bridge between not so quant financial people and modeling people.
@hovhannesnahapetyan9485 it is very challenging to do this as the general finance side cares more about making a buck than understanding how the world works. I've spent a decade trying to bridge this gap which is very frustrating. Sometimes you get small wins but often you end up trying to dumb down ideas and explain why they are critical only to be met with resistance as their experience knows more than the data.
@@DimitriBianco Thank you for the reply. It is somewhat surprising why would a financial institution have quant and general finance people if there is no mutually beneficial collaborative relationship between the two so that quant side bring the rigor of analysis and the non-quant side brings the qualitative knowledge that complements data. if there is no collaboration then why not have only one or the other (and save money on salaries and benefits)
Thanks for sharing this wonderful video. Truly insightful! I just have a quick question: What kind of a resources or path do you recommend for traditional finance which includes Data Science skill as well?
For traditional finance, self studying data science is enough. If you go this route I would encourage you to use textbooks over online resources so you get a fuller view. You could always get a data science degree however the traditional finance community really just values business degrees such as MBA's.
As always, very informative video. How important do you believe coding to be in making the switch? Had some experience with R while getting my Actuarial Science degree before I started working as an investment analyst 5 years ago. I've been working hard on learning Python for the last 2 months before I start my MFE in October. Do you think I just focus on refreshing math/stats concepts or keep pushing with coding?
Being proficient is usually enough to start an MFE program. You will enhance your coding skills during the program as well. Coding skills will make the difference between struggling with home work and being able to complete it in a reasonable amount of time. I would really focus on the math and stats at this point.
Hi, Dimitri! Fisrt, congrats for your insights and recommendations about Quant Finance here, on your channel. You've been doing a beautiful job! I wanna make just one sincere question: if you start to working by yourself, building models and trading your own capital, do you think you'd be capable of mantain a decent amount of income? Basically: do you think you'd "survive" only with your knowledge and some capital? Thanks in advance!
It's possible but rare. One reason is that you can make more money with less effort by working for someone else. Having investors and a team is a huge advantage.
Real question: how valuable is drunken studying? Say I'm awake for 16 hours per day and have 6 hours to study, and half the time I'm studying I'm inebriated or getting inebriated. I'd say three hours of sober studying plus three hours SWD = 3 + 1.3 = 4.3 hours of studying.
Hey Dimitri, great video as always! I don't know if you have already made a video on this, but would you be able to discuss and show the routine of study you did to educate yourself on the Calculus and Statistics you learned for the grad degree? Just like a template of how many hours or what mathematical / statistical exercises you did that helped you learn quicker. Thanks! Edit: Also interested in any particular textbooks you can remember for those topics!
Mate, if you look at the requirements for a MFE degree, they need a semester in linear algebra, differential equations and stats All of which you can teach yourself from MIT OCW Just if you want to qualify for applying for the master's program More in depth knowledge in these areas can be learnt through various books For starters, check out Carol Alexander's quantitative methods in finance Maybe start getting some coding experience in fin by making trading strats in your free time Quantopian is a good starting point You'll find a good path on which you can continue on from here I hope
One of the main math books I used was called, Calculus (I'll link a newer copy below). The book is over 1,200 pages and covers a lot of material needed for quantitative finance and general mathematics. Math: amzn.to/3d2JxFJ Stats: Introductory Econometrics: A Modern Approach ( amzn.to/2FVcgNa ) Stats Book Review: ruclips.net/video/uK8ZmKWnBuQ/видео.html
Well, this channel has been popping at my yt and i'd like to let my two cents. The Bs. in Economics is what has been recommended in comments about books and ideas are in this degree, i explain: descriptive stats, probabilistic models, hypothesis tests, econometrics, stochastic econometrics, Bayesian trees, games theory, behaviour economics( the backbone of Behaviour finance). But you've got a diferent degree like Business and want to get into the quant word. The best anwser is a master degree in Actuarial Science and Finance. Of course, you need to have coding skills, at the degree we use diferent kinds of programs like Stata, Eviews, R and Matlab. but No Excel (VBA) nor Python, so you need to learn and practice on your own. I expect helping someone, if want to ask something pls comment
Hello! I had a question about going a non-traditional route. I received my bachelors in 2017 in Psychology at NC State, but while there took math classes up to diff. eq. Additionally, I did research in Biological Mathematics, so I had a foot in the mathematics world. After college, I worked more in research and began to pursue a Masters in School Psych, but quickly realized the only part I liekd was the statistics and analysis side, I have been inworking in finance for over a year now as trade capture analyst in derivative rate products and about to finish a data analytics boot camp, which has only solodified my interest in the math and analytics world. I was interested in pursuing a masters in financial mathematics as a next step, but after watching your stuff am second guessing if I am even qualified. Would it be wise to still pursue this route? I would prefer to continue my career in a more math or statistics heavy area, but it seems like I just screwed myself from the very beginning as a confused college student with my psych degree.
Would you rather seek returns from a financial advisor or from computer that can compute mean reversions, algorithmic trading with AI screening. I'd trust my computer more than advisor(human) because computers can compute faster and effectively.
Hey dimitri I have Bsc Finance, Msc Finance and Banking, Msc in Quantitive Finance and a Data Science Academy certification and currently working as a Data Scientist. I am qualified enough to work as a Quant ? With my background ?
Hey Dimitri would you consider financial/quantitative mathematics(which is a track under the finance bs major at least at my school) in the same category as a typical finance major. I also have a cs/stats minor. I’m asking this question because it is a very quantitative track where I take classes like Stochastic processes, numerical analysis, mathematical and computational finance, and econometrics and time series; but it is still considered a “Finance” major.
I feel like you're going to need multivariate calc too unless your stochastic processes is a multivariate calc class? Back in my college days multivariate calc wasn't a prerequisite to take stochastic processes.
GOne I am taking that too along with linear Algebra, differential equations, probability, mathematical statistics, and options and future markets. I didn’t mention all of my related classes because I thought those were just fundamentals.
From a topics perspective it seems like a good foundation for quantitative finance but it's hard to tell from just class names. The rigor of materials covered is important and knowing core math and stats concepts is more valuable than the application to finance itself.
hello Dimitri; I am currently in my last year at high school and soon have to decide my major at university. I pretty like Maths and really love to study probability; and I also find some jobs like yours (a quant - which requires analytical skills; maths skills; etc) really interesting and want to do similar work in the future! So my question is: which degree should I pursue: mathematical finance; corporate finance or computer science (I don't take much interest in coding but like to do maths) and how to know if I am smart/good or suitable enough to pursue these degrees. Thank you! (in my country; I have to decide the major from the beginning without being taught or knowing anything about these fields; and have no chance to change later so I am considering a lot; I also wanna to study master degree in other countries in the future)
I would get a mathematical finance degree. If you don't like to code, a CS degree would not be a good fit. General finance teaches a lot of theory but you won't do too much math. And if you enjoy math, then a mathematical finance degree would be a good fit. It would also look good when applying for masters in quant finance or other analytical studies.
I'd agree with this. The ones you will lose will be those trying to be generalists. For example, focusing on corporate finance, investment banking, or quant finance will provide a better career and compensation compared to those trying to cover every topic.
I haven't watched this video in a long time but I'm guessing that comment was about undergrad degrees. I'm not a fan of financial engineering undergrads as they miss a lot of core skills that could be needed later on in a career. So a math or stats degree is better for undergrad as you will need a masters or PhD for a career (this is where a financial engineering degree should be taken). Now most graduate programs (masters or phds) have math prerequisites and not statistics ones. So often a math undergrad can be more helpful in getting into a good graduate program.
Dear Dimitri, I have an important question for you. I studied physics in my Bachelor, but then I realised I preferred maths and in the end doing something practical with it. I want to add that I do not consider myself to be a Genius. I loved to understand models but at the same time I love to work with people and put even some "opinion( not "Just" numbers)" into my job. Do you think is It Better to look for a job in tradizional finance? Is It possible with my background? Best Regards.
If I were you I would go with quant finance and get a masters. I work in risk management and we have a good mix of team interactions and also individual time spent coding and modeling. Besides talking technical topics which I enjoy, I've been on a lot of small and specialized teams. In these small teams I've made some great friends from a variety of ages and nationalities. We also meet with model owners who are the business people that request the model. You might get bored in traditional finance as the math would be very basic compared to someone with a math or physics background.
What would you suggest a physics undergrad (minored in computer science) looking to make the transition, would something like masters in econometrics be good enough
I'm starting to learn programming over the summer before i apply to an MFE next year. What languages do you think I should focus on first? I was thinking either Python/C++ then a stats language like R/Matlab. I only have basic experience in C, VBA and Matlab
It depends on the languages your program uses. When I was in school C++ and R were the main languages. Now Python has become more popular however it really depends on the class/program. Python would be a good starting point for learning as it can do stats and more traditional programming.
So I also did this, except I couldn't hack the math and dropped out. But I had a full scholarship (fellowship), I never would have paid money to attempt cause I knew I wasn't qualified.
So for my undergrad I did a Finance major with a math minor. In addition to my Finance courses I took (mostly introductory courses in): Calc 1-3 ODEs Linear Algebra Real Analysis Econometrics Python for Business Applications I went to an engineering school, so a lot of my friends are in computer engineering, but despite their much greater knowledge about computer hardware and programming, i don't feel like they have significantly more math background than I do. Is the difference really that large when you just consider the undergrad?
There is a large difference given the courses an average finance students takes. Your math minor and the courses you listed in math would prepare you just as well as STEM undergrads for a quant finance masters. However you need to make sure you look at the minimum requirements of masters or PhD programs before you apply.
@Dimitri, please tell me, is cs the best degree to get then? But I don't know how effective it will be as it misses the understanding of finance or economics
Whenever I see this question asked on forums it always makes my stomach churn. Either a lot of these people ACTUALLY don’t look at course material for these programs or are very delusional. The chances of a finance major working through a textbook like Steven Shreve’s and understanding it is close to 0. I’m a physics major who excelled in group & set theory courses, but working through that textbook and actually understanding the content was CHALLENGING (never took stats classes). But when you haven’t even taken high level calculus or stats classes and thinking you can just learn ito calculus and Brownian motion etc on the fly is VERY naive. Additionally, I’m not even considering the type of skills of problem solving skills that they’ve never had to do. Putting it bluntly, it’s like asking a high school grad to enrol in a master’s program. If you’re driven by money, it’s far worth your time to stay on the business side. You’re just too far behind in content and the type of problem solving skills. Like Dimitri said, he had to catch up for lost time because he was so far behind in the required math.
"You're just too far behind in content and the type of problem solving skills ." You could have said the same thing to Edward Witten just after he graduated in history.
@@arunavaghatak8614 I don't know who that is, but it doesn't really matter. Finance majors going into quant isn't gonna happen unless they take fundamental math classes. They're competing against mathematic & physics PhD grads and MS financial engineering holders for these jobs
Hi, I have a finance degree, have been working for 5+ years and realized I like the analytical side of finance way more than the client-facing side. I figure due to my background, a quant career is highly unlikely. Do you think switching to the data analytics/data science side of finance would be a good fit?
Hi Dimitri, I have a bachelor degree in Business Administration & Economics and I want to apply for a Master Degree in Quantitative Finance. Is it possible to become a risk manager or an asset manager with a quantitative finance master? (due to my background becoming a quant seems unlikely and impossible)
Hi Dimitri, I think I finally understand the difference between quant and traditional finance. Is it that quant do the number crunching while traditional finance interpret the results from quant?
No. Traditional finance uses simple calculations and analytics while quants build statistical and mathematical models. It's more about applying deep math and stats theory to finance not about just crunching numbers.
@@DimitriBianco Thank you for replying, I just got to say I found your content yesterday and absolutely love it😊 I'm still struggling understanding what exactly a financial analyst do then because I thought they did what quant did. Also why would any company hire a financial analyst when a quant can do everything plus more?
I studied Calculus 1-3 in high school as well as some Real Analysis on my own. Do I only need Differential Equations and Measure Theory(-tic probability) and stochastic calculus? Will this knowledge enable me to get an MFE (I studied stats in my Bachelors; would it be better to go for a Master's in Stats instead along with something like an FRM to cover the risk part?)
@@DimitriBianco Alright, thanks. In case you know of FRM's content, is the statistics covered in FRM's Quantitative Analysis (Probability, Prob Dist, Hypothesis Test, Regression, Time Series, Simulations) enough for an MFE or M Stat? Many universities require a Bachelor's heavy in Mathematics; my business degree had Statistics but no Math.
Just tell people to take CQF certification. They need to get started somewhere .. somehow. Can't discourage anyone who doesn't have background but is keen on learning this stuff.
I’m looking to get into PE/HF or some form of financial analysing in the future, I have an option of MSc in statistics, quant economics or High performance computing. Which do you think would be best? I feel the high performance computing would be as it’s so rare that few will have the skills it provides
For private equity you'll want a business degree like an MBA not a quant degree. For hedge funds it depends on the fund, whether it's traditional finance or quant. The type of degree will decide what you do at a firm. CS type degrees mean you'll be working on implementation while stats and math are more for research and model development.
@@DimitriBianco would you personally think a master's in high performance computing would be useful? I see there's only 2 in Europe so I do believe I'd stand out. I also have the highest score for finance in my university in my bachelor's and the highest score for Chinese
If you want to be a computer scientist at a hedge fund or algo firm then it could be a great option. If you want to be a quant and build math and stats models then it's not a great degree for that.
@@WolfAngelRock Some personality traits are found to be genetic to a certain extent so they are probably not total BS (though maybe not MBTI). I think personality tests can serve as guidelines in self-introspection.
I'm a big fan of the Myers-Briggs as I have seen it to work fairly well at defining people. Yes, people change over time and most people fall towards the middle of the 4 categories. Many people don't realize the tests have percentages between the binary classes. For example, if you are introverted, how introverted are you? I am an INTJ and percentage wise, I am far from the middle in each category (I am somewhat polarized). I usually re-take the test every year or two to see how I am changing. Quants can come from many if not all personalities however I have found that the "Decisions" (T vs F) is very defining. Those that have a high T score excel at being quants where as those that have a high F score excel at traditional finance and management. For me doing deep dive analytics and knowing very intricate details about statistical assumptions or model structures comes very naturally to me. As I transition more into a management role I have to work a lot harder. I can come off as cold or non caring when working with people. I also have to try and weigh what is correct versus what is feasible for the business' needs more carefully. This personality trait is a big hurdle for the industry as you need quant managers who really know what's going on when it comes to technical matters however you also want a manager that can build teams and add value alongside the business.
I’ve heard if you get a job working for a financial company (one that participates in trading) there are highly restrictive regulations on how much personal trading you can do on the side. Can you comment on how true this is in your experience?
If you have access to non-public information then you can't trade those securities. As for a company not allowing you to trade, I can't speak on that however if I were a trading firm I would not allow my employees to trade on the side.
Hey Dimitri what is your opinion on the double degree at UPENN. I want to be a Quant and plan to get a bachelors in cs and masters in fiance or stats. Doing this at UPENN would allow me to get both in 5 years. I promise my goals are aligned with quantitative finance.
make sure to read up on basel iii and risk regulations. banks are getting squeezed to death by regulation and money from trading are down. jobs in those area are little while data science are hiring like super crazy. hope this will help your decision
I would change your major to statistics. It will open up a lot of opportunities in quant finance as well as other areas. You can also minor in finance to get the basic finance skills as well.
I often require them to know the model so no app is needed. For large ML models like decision trees the packages can output the tree. The equating should be written in a word document.
I am currently working as a Data Scientist for a fintech firm, I wanted to pursue Financial Engineering. Yes, I do love math/stat/fin domain. Is It going to be a big switch?
Why did you decide to work in validation rather development. Does it not get frustrating to dig through other peoples code all the time instead of writing your own?
There are pros and cons for every role. I've actually worked across the entire model life cycle (development, validation, implementation, and audit). I enjoyed working in development as you get to go deep with modeling and model usage details. There is a fair amount of coding and it's fun to have a team working towards one project. Validation on the other hand gets a high level model perspective with the opportunity to dig deep on a specific part of a model. The entire development process must be validated however some of the tedious parts such as data clean is straight forward to review. A developer would have to spend more time on these parts which is a con for development. My validation team is in a mature state so we also build challenger models to show developers how a model could be built better or to show how and why their current model will fail. Another pro for validation is being able to see many different models. A developer will spend more time developing than a validator typically spends validating. This means I get to see all sorts of credit model, operational risk models, market risk models, and PPNR models. At larger banks you typically are focused in of those four areas however within those areas you see a lot of different types of models and usages. Now one of the big cons of validation is the amount of reading and writing. A model developer will develop a model and write the final report explaining the entire process. A validator now has to read the entire report along with a long list of other documents such as model development meeting minutes, previous validation reports, and previous development reports. Then we do some fun statistical analysis, model testing, and challenger model development if we're lucky. After that we then have to write a report (usually around 80 pages) plus about 5 other documents on model issues, remediation efforts, risk ratings, and effective challenge meeting minutes. I should also note than many validation teams prefer or require model development experience before joining the validation team. The reason for this is so that you fully understand how a model should be developed along with some understanding of their process and potential issues.
Oh and to respond to your code comment...yes it's frustrating when code is written poorly. If you write poor code I try to mention it in the report as well. But what's even more frustrating is when developers make simple model development mistakes and then you have to meet with them to explain they basically have to start over or make significant changes. Working with people and delivery bad news is a good skill to have as a validator. Both validators and developers in banking also have to meet with regulators for model reviews but usually this is a management job.
@@DimitriBianco Thank you for the detailed reply! What was the funniest reason that someone has ever given you as to why their model is good and your comments are wrong?
I am currently in my physics masters degree and would like to work as a quant. Would you recommend me doing a PhD and if yes rather physics or some other field?
It depends on your interests but there are quite a few quants with applied math, statistics, and econometrics degrees. It is possible to switch over with a physics PhD however it should be easier if you find a degree that is more closely related to quantitative finance.
I'll make a video as I am sure many would like to see the details however I will lay out some of it here for you. The low quant job placement rate is a global/industry problem and not unique to any one school. If you look at quantnet you'll see the average (non-weighted) 3 month placement is 79%. You would assume that going to a program would give you a high probability of being a quant however job placement is different than quant finance job placement. A large portion of these students who find jobs end up in non-quant roles. Most programs will argue with this however it comes down to the definition of quant finance. I know a lot of MFE grads who go on to be traders, analysts and entrepreneurs at cryptocurrency firms, financial analysts at banks, wealth management analysts, consultants, and tech professionals. Now don't get me wrong, many of these jobs sound great even to me. I define quant finance jobs by two criteria though. One, the skills of the job need to be "quant finance" meaning a mix of math, stats, and computer science. Two, they need to require a graduate degree. This definition is too strict for many people and I am fine with that. The real disappointment comes from students who paid a lot of money on a degree and loved the field only to end up working with a bunch of undergrads in an unrelated area. This is really a blow when you realize you could have skipped the masters which would have saved you time and money. If you look at the numbers from an industry perspective, having low quant job placement makes sense. Most banks and investing firms only hire a few new entry level quants each year. Some large banks hire more and some small banks or firms hire less. For example, a mid sized bank would have a development team and validation team which would be around 60 people. They usually bring in around 4 entry level roles each year. Let's say there are 200 firms which would mean there are 800 open roles for the year (US example). If you only look at quantnet, you'll see there are 1,736 students enrolled in programs. If half graduate each year we have 868 students to fill 800 jobs. 68 unemployed students will still give us a good placement rate. However most firms prefer PhD graduates and we also hire those from a variety of other quant backgrounds including statistics, econometrics, and mathematics.I have no idea what numbers to guess for these additions however I can tell you out of about 70 people I've worked with over the last five years, I've only had 5 who had some sort of financial engineering/quant finance degree. Those aren't very good odds, at least from my perspective. Getting hard data on this would be fascinating however schools and companies would not like to provide this data as it makes them look bad. In general the US is very competitive. It's really a global market as most quant finance professionals and students come from abroad. This makes it very competitive as you have people from every country and given that there are more graduates each year than jobs, it results in low job placement rates. From my personal perspective (not data backed), some programs have high quant placement rates and some have very low placement rates. With a boom in new quant finance masters programs, there continues to be too many students and not enough jobs though some of the top programs do have great quant job placement.
@@DimitriBianco is the situation in Europe or Asia different from the one in the US? I'm studying Mathematical Engineering (Quantitative Finance track) in Italy and don't know where is the best place to start my career
If you haven't covered enough math and stats it will be much more challenging. I came from traditional finance and economics to quant finance but it was very stressful.
Hey i have a question If u have a financial market undergrad and i do some mathematical and statistics certifications or short courses then can i apply for ms in quantitative finance
Every quant masters has different requirements for applications, so look and see what programs require. Programs also teach different material and have different focuses. Some programs welcome business students however their focus is more on high level application than the small details.
Im currently doing an MsC in Finance, where i have classes that cover machine learning for finance, econometrics and financial mathematics. Do you still think that i dont have a shot at quant finance?
You will probably need to study Real and Functional Analysis, Stochastic differential equations, Model Identification and Data Analysis to truly understand the math behind
For financial engineering (meaning engineering derivative products) will require a lot more math than other areas of quantitative finance. For example, I work in risk management where we build statistical models. Having a deep math understanding in say stochastic calculus isn't very useful for us. What I'm pointing out is that different areas of quant finance need more focus in different quantitative areas.
I have seen many engineering backgrounds in grad school but not many go on to quant jobs. I don't recall who had what engineering degree though. The math from an engineering degree should prepare you well for a quant masters. Just remember engineers don't know everything. Their egos often prevent them from getting quant jobs.
Technically anyone can be a trader. All you need to do is sign up for an account and trade online. Now being a successful trader is a challenge. Some take a traditional finance approach (no quant degree needed) and some take the quant route (quant degree is needed). To be successful at trading though, you really need a team of people including investors. The online ads of turning $500 to $100k is a joke. They are just looking for people to pay them money for their "education."
Refreshing as always to have such an honest, transparent perspective into the quant world. Keep up the good work!
I agree, my biggest regret was following a generic commerce degree instead of a mathematics degree. My opinion is the generic Business/Commerce degree is the equivalent of an Arts Degree. People do them when they have no idea what they want to do.
This makes me feel better about pursuing a math degree for my undergrad. Thanks lol
@@adamsusel3801 math degree with minor in finance is good. Can then do masters in many subjects as solid math is key to everything
Yes, it is like an escape route... people do this cause they can't do medicine, law, engineering, math, physics etc. But they think arts is stupid. So they settle for commerce.
Same.
Even for STEM students, getting into quant is hard... To prepare for interview for a quant position, I am practicing problems including stat/probability, math, brain teasers, ml, algorithm and coding. The only way I see a finance student to get a quant job is to double major in math or cs. For a finance student, investment banking fits much better.
Im in the kind of(ish) the same position as you were. Finance major who didnt even get into a finance role after college. Ended up working at a law firm in billing just cus its good money and wanted to save for school. Im finally financially prepared and ready to go back to school now. All i can say is, catching up on everything has been absolute hell. And im only applying to pre-req courses. LOL. Never give up!
I have a PhD in theoretical physics and am self taught in stats, probability, computer programming, and machine learning so I had initially thought this advice would not be relevant to me until he got to the end and spoke about the drivers / motivation. I was motivated by the money, and have no real interest in finance. I am a talented problem solver and can solve those interview questions with relative ease, and although I find those puzzles fun to solve, and mathematically abstract ideas come easy to me, I found I was pursuing this field for the wrong reasons; a fancy apartment in Manhattan, a nice car, and other material posessions. I am now starting to shift my values and beginning to understand that it is not these things that provide happiness thanks in part to the last few pieces of advice given by Fancy Quant. Thank you, Demitri!
Hey, I am intrigued by your comment and ability to learn complex concepts by yourself. I myself am a finance major , however , I have always been a good problem solver and loved puzzles and riddles as a kid. Also, I was very good at math, and probability theory. My high school teacher suggested for me to take an AP class in high school on statistics. Which I did, and I was mediocre in that class because my teacher wasn’t the best and just had RUclips videos teaching us. What a class for an AP student right ??? About two years ago I got invested into the stock market and ever since then I’ve been a stock market junky. I’m more of an investor than a trader but I have taken and closed positions on a much smaller time frame (swing trading, months, weeks). In my free time I’ve developed an interest in learning more about the markets, what participants there are, and how the set of rules both political , and regulatory, effect a position on a certain stock.
I’ve also stumbled across numerous content that covers Algo trading, computational finance, and Quantitative Finance. My only question to u is how did you go about learning all of the things you mentioned above while studying theoretical physics. Seems pretty hard but from your background it sounds like u are very bright and talented to be able to learn with ease. I wish to learn those exact topics but don’t know where to start, what books to read, or even who to talk to. My plan one day is to become a Quantitative trader or analyst. What drives me is the intellectual pleasure of solving problems and the fact that your compensation is a reflection of your performance, and ofc the money that is involved is lucrative and worth the work. I see trading and investing as a skill and art. The better person I am, the better a trader or investor I will be. I like the discipline it takes, and I’ve always been a hard worker. It would mean a lot to me to receive any advice or guidance on my journey. Thank you for reading this and good luck on all your endeavors
Good information. I study machine learning/statistical learning and come from a CS background myself but I do enjoy watching these videos despite having 0 interest in quantitative finance. Just neat to see smart people applying their skillsets to other fields I know nothing about.
Fantastic and genuine advice. Thank you Dimitri! I have a double major in BS Fin and BS math-CS and will head for an MS math. I've worked at "quant" positions during my studies and this is when I discovered that this job/team is where I want to be. I'm an ENTJ, so thanks for bringing in this aspect up as well. Really great video, you inspire me :)
Hello P! Actually I am currently pursuing BE in Computer Science but my interest is in the 'MATHS'. Could you please tell me whether the "quant" role is relatively math Rigorous or not?
I'm just so damn relieved that I added a dual degree in applied math to my finance major
Hey what career path did you go into? I have a similar academic background
im about to transfer to a 4-year. thats exactly what im about to do
15:15 this is so true.
Me and my classmate from highschool picked up two different paths.
I went for Finance university, she went for Mathematical Engeneering.
At the end we end up working in the same Insurance company 😂, i work in the Investment Decision department, she works at the Actuarial Department.
So at the end, she calculates scenarios and i decide which one to pick and invest 😂
Thanks for making this video man, it gave me a lot of much needed clarity.
thank you . This is very clear explanation and great warnings.
Very often Finance grads (bus. or economics) are not people who want to spend their whole life into the realm of mathematics modeling or its real life implementation. The quants are not only people who can "read or use" a model, but who tinker it all the time. A very specific skillset who normallly attracts much more the engineers, physics graduates and alike (even some mathematicians don't like the "too applied" aspect of this job, at least as it is normally carried out in banks).
Very true
dimitri , i am from computer science major background and your video has helped me a lot to explore about quants
I'm happy to hear they have been helpful!
Dimitri , this is a great video and thank you for the content🙏🏽
Fantastic video as always Dimitri, I think putting out another day in the life video would benefit a lot of people who are not too sure about the specifics of what quants do!
That's a good idea. I'll add it to my list.
Hi, Dimitri. Thx for another amazing video here. I have a finance and economics background. The problem I have is that I find myself choosing the wrong major after I graduated. My personality, just like u mention, is more like a quant who like to analysis and stats. I understand that my background is not rigorous compared to that of quant undergrad. So I am wondering could u plz do a video talk about how I should catch up, including like what program should I take or what course should I learn?
Very well said!
Hi Dimitri ,
Thanks for doing this RUclips channel to explain to us layman what quant is about. I'm an engineer working in the oil field , and was always confused what quant is about. In my home country (Singapore ) , quant finance is only offered to the cream of the crop and only a handful a year . You have to choose maths as a major first , then the university choose you during sophomore year in the National University of Singapore (NUS).
Quantitative finance is applying advanced math and statistical methods to finance. To be able to do so you also need to be able to program as a way to express your ideas and test them out. Quants need a blend of math, statistics, and computer science.
I think the "I'm not in it for the money" line applies to any profession at a higher level. You have to be obsessed with the task at hand.
Wow, very cool. doesn’t think that somebody do the same things. Respect to the author
I learned about this to late unfortunately, since I never really had a clue what finance actually was and the careers in this field. As a result I'm going to university for finance bachelor at the moment. Is there still a way to get into quant finance or what would the necessery steps be to do so?
This video discusses how to go from finance undergrad to quant finance.
ruclips.net/video/UK2V07JLU5c/видео.html
@@DimitriBianco thank you very much
Thank you Dimitri for your guidence
You're welcome! Thanks for being a part of the channel!
Cant we say that economics is a quantitative field ? We take lots of Math like linear algebra, calculus,differential equations and lots of statistics like regressions hypothesis testings etc. and we took econometrics time series econometrics etc. can we say economics degree that ıve been taken is a quantitative degree? Thanks
This actually depends a lot of the program. Yes, there are economics degrees that are quantitative (I actually have a masters in applied economics). Your economics degree sounds like a quantitative degree. However there are also schools with economics degrees that focus a lot on theory and do minimal math and stats.
Dimitri thank you for this awesome video.. In an earlier comment you said you had a boss with Economics grad degree... I agree with you completely that quantitative finance requires hardcore maths and stats... Thats why i am taking courses on maths, stats and Econometrics... To give you an idea.. I have learned real analysis, metric algebra, linear Algebra, probability theory, differential equations.. Currently studying stochastic calculus.. Not in its full rigour... But learning from basics... On my own.. I have 3 econometrics courses so far from my university... And will take 6 more courses on it.. My university teaches econometrics from wooldridge cross sectional and pannel data, green... I have done time series from enders...on the software side of things i am intermediate in python... Can make apps... R working knowledge... Learning java at present... I am pursuing acturial courses on the sideline... I am already an economics masters student... Will pursue another quantitative economics masters degree.... Probably a phd if family constraints dont come... On the professional degree side i am pursuing cfa... This is my Portfolio till now... Can you please advise me if this will be sufficient for quant job...? My main concern is most of the Mathematical skillsets i have developed on my own... Only the econometrics and acturial courses i can show as the econometrics courses are conducted in my university... Will recruiters give any importance to self studied courses? How do i convince them that i know the stuff? Also is this learning sufficient... Or do u need much more to get started... Thank you for helping me earlier.
Edit- I really want to dig into this field.. I know my passion resides here... I have done day trading for 6 months but i stopped thereafter as i want to implement algorithmic trading so currently learning about these... Do you think given my foundation and learning from books like
1. Successful algorithmic trading
2. Advanced algorithmic trading from michael more
3. Machine learning books from marcos prado..
4. Time series by hamilton
Will be sufficient enough for quant job? I have gone through many mfe and financial engineering curriculum and their suggested readings... I am tailoring my learning towards this...i am ready to make all the sacrifice and want to learn about markets...
From what you have provided you seem well prepared. Self learning is good however it isn't taken too seriously however if you have a masters degree like economics and can talk about a variety of areas like math, statistics, and computer science you can usually get an interview and an offer. The key for you will be to write a resume that matches the job description. So for example, if something like R or Python is required, make sure it is listed somewhere on the resume. This will get you past HR's review.
@@DimitriBianco Thank you so much Dimitri for replying..
Hey can u share with us the sources you've learned all this by yourself mentioned above like math stats econometrics, linear algebra, etc etc and all the courses you've taken, can u please share this with us
Hi Dimitri,
Recently found the channel and I am really enjoying your content. I am also a Michigan Alum as I graduated from Ross with a BBA in 2018. When you applied to the MFE program at Michigan, did you do so with just your Finance background? If so, that's very impressive. With my current Finance undergraduate degree I don't think I could come close to finishing a quantitative finance program. I am planning on applying to Graduate Programs in 2021 after taking 2 semesters of enrichment at the UofM Dearborn campus. I left my full-time job to go back to school and pursue quant finance. Do you think that me going back to school for undergraduate classes is the correct thing to do to strengthen my application for Master's programs? Thank you for your time.
If you are wanting to go into quantitative finance then I would agree that going back for undergrad math class will be helpful. Programs usually don't care too much about the degree as long as you can show that you have taken the courses they are interested in.
Hi Dimitri. First, thanks for sharing this, it's very valuable for those who are pursuing this career. My question is,
when you say that you model things, which was the basic knowledge that you learn that make you able to model nowadays? Calculus, Differential Equations, Real Analysis, Linear Regression, and so on? I have an economics background and I would like to make this catching up as you did in your gap semester. Again, thank you for helping dreamers to get there.
It depends on the area you go into but in general understanding linear algebra and calculus 1-3 help you understand the underlying theory of statistics (regression and optimization). To really understand derivative pricing you need math (real analysis, measure theory, and stochastic calculus) as the general principles are built on top of this. For most quant jobs that aren't working with derivative you can get by knowing statistics really well. As you dig deeper though in different areas like time-series you'll end up needing the same math as in derivative pricing.
As an undergrad I would focus on the core statistics concepts like hypothesis testing, coefficient estimation (OLS vs MLE), optimization (think neural networks and portfolio construction), linear regression (OLS, Logistic, FGLS, ARIMA), and data science (trees, clustering, dimensionality reduction, and neural networks.....and yes I consider data science a subfield of stats). Along the way you will need math such as what is taught in calculus 1-3 and linear algebra and you'll need to at least be able to program your statistical analysis in a language like R, Python, SAS, Matlab, or SPSS.
There is always more to learn but the above should be enough to get you started in a masters. Once you work on a masters or PhD you'll realize there is so much more to learn and very limited time.
That was extremely helpful. Thanks a lot more one time!
Thanks for the video. I was wondering if it would give one a comparative advantage to do quantitative finance but work in the world of general finance. The rationale is that one could be a bridge between not so quant financial people and modeling people.
@hovhannesnahapetyan9485 it is very challenging to do this as the general finance side cares more about making a buck than understanding how the world works. I've spent a decade trying to bridge this gap which is very frustrating. Sometimes you get small wins but often you end up trying to dumb down ideas and explain why they are critical only to be met with resistance as their experience knows more than the data.
@@DimitriBianco Thank you for the reply. It is somewhat surprising why would a financial institution have quant and general finance people if there is no mutually beneficial collaborative relationship between the two so that quant side bring the rigor of analysis and the non-quant side brings the qualitative knowledge that complements data. if there is no collaboration then why not have only one or the other (and save money on salaries and benefits)
Really good advice
Thanks!
Thanks for sharing this wonderful video. Truly insightful! I just have a quick question: What kind of a resources or path do you recommend for traditional finance which includes Data Science skill as well?
For traditional finance, self studying data science is enough. If you go this route I would encourage you to use textbooks over online resources so you get a fuller view. You could always get a data science degree however the traditional finance community really just values business degrees such as MBA's.
Dimitri Bianco Thanks for the clarification. Would you mind in suggesting textbooks details please?
As always, very informative video. How important do you believe coding to be in making the switch? Had some experience with R while getting my Actuarial Science degree before I started working as an investment analyst 5 years ago. I've been working hard on learning Python for the last 2 months before I start my MFE in October. Do you think I just focus on refreshing math/stats concepts or keep pushing with coding?
both
Being proficient is usually enough to start an MFE program. You will enhance your coding skills during the program as well. Coding skills will make the difference between struggling with home work and being able to complete it in a reasonable amount of time. I would really focus on the math and stats at this point.
Could you show us your room & equipment? Alternatively, you could do a house tour :D
Hi, Dimitri!
Fisrt, congrats for your insights and recommendations about Quant Finance here, on your channel. You've been doing a beautiful job!
I wanna make just one sincere question: if you start to working by yourself, building models and trading your own capital, do you think you'd be capable of mantain a decent amount of income? Basically: do you think you'd "survive" only with your knowledge and some capital?
Thanks in advance!
It's possible but rare. One reason is that you can make more money with less effort by working for someone else. Having investors and a team is a huge advantage.
@@DimitriBianco Great! Thanks for your answer, Dimitri! Keep up the good work here!
Had no idea you went to school at WSU! Are you from Washington State? Congratulations on your success post-WSU
Yep! I'm from Spokane.
Real question: how valuable is drunken studying? Say I'm awake for 16 hours per day and have 6 hours to study, and half the time I'm studying I'm inebriated or getting inebriated. I'd say three hours of sober studying plus three hours SWD = 3 + 1.3 = 4.3 hours of studying.
Drinking results in memory loss. Being drunk while studying is not a good idea.
www.healthline.com/health/alcoholism/alcohol-and-memory-loss
Hey Dimitri, great video as always! I don't know if you have already made a video on this, but would you be able to discuss and show the routine of study you did to educate yourself on the Calculus and Statistics you learned for the grad degree? Just like a template of how many hours or what mathematical / statistical exercises you did that helped you learn quicker. Thanks!
Edit: Also interested in any particular textbooks you can remember for those topics!
Mate, if you look at the requirements for a MFE degree, they need a semester in linear algebra, differential equations and stats
All of which you can teach yourself from MIT OCW
Just if you want to qualify for applying for the master's program
More in depth knowledge in these areas can be learnt through various books
For starters, check out Carol Alexander's quantitative methods in finance
Maybe start getting some coding experience in fin by making trading strats in your free time
Quantopian is a good starting point
You'll find a good path on which you can continue on from here I hope
One of the main math books I used was called, Calculus (I'll link a newer copy below). The book is over 1,200 pages and covers a lot of material needed for quantitative finance and general mathematics.
Math:
amzn.to/3d2JxFJ
Stats:
Introductory Econometrics: A Modern Approach
( amzn.to/2FVcgNa )
Stats Book Review:
ruclips.net/video/uK8ZmKWnBuQ/видео.html
@@DimitriBianco Thank you, appreciate it!
Well, this channel has been popping at my yt and i'd like to let my two cents. The Bs. in Economics is what has been recommended in comments about books and ideas are in this degree, i explain: descriptive stats, probabilistic models, hypothesis tests, econometrics, stochastic econometrics, Bayesian trees, games theory, behaviour economics( the backbone of Behaviour finance). But you've got a diferent degree like Business and want to get into the quant word. The best anwser is a master degree in Actuarial Science and Finance. Of course, you need to have coding skills, at the degree we use diferent kinds of programs like Stata, Eviews, R and Matlab. but No Excel (VBA) nor Python, so you need to learn and practice on your own. I expect helping someone, if want to ask something pls comment
Hello! I had a question about going a non-traditional route. I received my bachelors in 2017 in Psychology at NC State, but while there took math classes up to diff. eq. Additionally, I did research in Biological Mathematics, so I had a foot in the mathematics world. After college, I worked more in research and began to pursue a Masters in School Psych, but quickly realized the only part I liekd was the statistics and analysis side, I have been inworking in finance for over a year now as trade capture analyst in derivative rate products and about to finish a data analytics boot camp, which has only solodified my interest in the math and analytics world. I was interested in pursuing a masters in financial mathematics as a next step, but after watching your stuff am second guessing if I am even qualified. Would it be wise to still pursue this route? I would prefer to continue my career in a more math or statistics heavy area, but it seems like I just screwed myself from the very beginning as a confused college student with my psych degree.
I just responded on LinkedIn.
Would you rather seek returns from a financial advisor or from computer that can compute mean reversions, algorithmic trading with AI screening. I'd trust my computer more than advisor(human) because computers can compute faster and effectively.
Hey dimitri
I have Bsc Finance, Msc Finance and Banking, Msc in Quantitive Finance and a Data Science Academy certification and currently working as a Data Scientist. I am qualified enough to work as a Quant ? With my background ?
Hey Dimitri would you consider financial/quantitative mathematics(which is a track under the finance bs major at least at my school) in the same category as a typical finance major. I also have a cs/stats minor. I’m asking this question because it is a very quantitative track where I take classes like Stochastic processes, numerical analysis, mathematical and computational finance, and econometrics and time series; but it is still considered a “Finance” major.
I feel like you're going to need multivariate calc too unless your stochastic processes is a multivariate calc class? Back in my college days multivariate calc wasn't a prerequisite to take stochastic processes.
GOne I am taking that too along with linear Algebra, differential equations, probability, mathematical statistics, and options and future markets. I didn’t mention all of my related classes because I thought those were just fundamentals.
From a topics perspective it seems like a good foundation for quantitative finance but it's hard to tell from just class names. The rigor of materials covered is important and knowing core math and stats concepts is more valuable than the application to finance itself.
hello Dimitri; I am currently in my last year at high school and soon have to decide my major at university. I pretty like Maths and really love to study probability; and I also find some jobs like yours (a quant - which requires analytical skills; maths skills; etc) really interesting and want to do similar work in the future! So my question is: which degree should I pursue: mathematical finance; corporate finance or computer science (I don't take much interest in coding but like to do maths) and how to know if I am smart/good or suitable enough to pursue these degrees. Thank you!
(in my country; I have to decide the major from the beginning without being taught or knowing anything about these fields; and have no chance to change later so I am considering a lot; I also wanna to study master degree in other countries in the future)
I would get a mathematical finance degree. If you don't like to code, a CS degree would not be a good fit. General finance teaches a lot of theory but you won't do too much math. And if you enjoy math, then a mathematical finance degree would be a good fit. It would also look good when applying for masters in quant finance or other analytical studies.
@@DimitriBianco thank you very much!
I think the finance career is narrowing and people are looking for those big paychecks
I'd agree with this. The ones you will lose will be those trying to be generalists. For example, focusing on corporate finance, investment banking, or quant finance will provide a better career and compensation compared to those trying to cover every topic.
What do you mean that a pure maths degree is better for Financial Engineering than a stats degree? In what ways exactly?
I haven't watched this video in a long time but I'm guessing that comment was about undergrad degrees. I'm not a fan of financial engineering undergrads as they miss a lot of core skills that could be needed later on in a career. So a math or stats degree is better for undergrad as you will need a masters or PhD for a career (this is where a financial engineering degree should be taken). Now most graduate programs (masters or phds) have math prerequisites and not statistics ones. So often a math undergrad can be more helpful in getting into a good graduate program.
Dear Dimitri, I have an important question for you. I studied physics in my Bachelor, but then I realised I preferred maths and in the end doing something practical with it. I want to add that I do not consider myself to be a Genius.
I loved to understand models but at the same time I love to work with people and put even some "opinion( not "Just" numbers)" into my job. Do you think is It Better to look for a job in tradizional finance? Is It possible with my background?
Best Regards.
If I were you I would go with quant finance and get a masters. I work in risk management and we have a good mix of team interactions and also individual time spent coding and modeling. Besides talking technical topics which I enjoy, I've been on a lot of small and specialized teams. In these small teams I've made some great friends from a variety of ages and nationalities. We also meet with model owners who are the business people that request the model. You might get bored in traditional finance as the math would be very basic compared to someone with a math or physics background.
@@DimitriBianco by the way, what do you think about actuarial sciences?
What would you suggest a physics undergrad (minored in computer science) looking to make the transition, would something like masters in econometrics be good enough
Econometrics is a possibility if you take enough statistics.
I'm starting to learn programming over the summer before i apply to an MFE next year. What languages do you think I should focus on first? I was thinking either Python/C++ then a stats language like R/Matlab. I only have basic experience in C, VBA and Matlab
It depends on the languages your program uses. When I was in school C++ and R were the main languages. Now Python has become more popular however it really depends on the class/program. Python would be a good starting point for learning as it can do stats and more traditional programming.
@@DimitriBianco Thats good to know. I think i will learn Python first. Baruch have C++ as a must but the others seem to be more leanient.
Out of curiosity, what kind of jobs did your master of economics classmates land after graduation?
So I also did this, except I couldn't hack the math and dropped out. But I had a full scholarship (fellowship), I never would have paid money to attempt cause I knew I wasn't qualified.
So for my undergrad I did a Finance major with a math minor.
In addition to my Finance courses I took (mostly introductory courses in):
Calc 1-3
ODEs
Linear Algebra
Real Analysis
Econometrics
Python for Business Applications
I went to an engineering school, so a lot of my friends are in computer engineering, but despite their much greater knowledge about computer hardware and programming, i don't feel like they have significantly more math background than I do.
Is the difference really that large when you just consider the undergrad?
There is a large difference given the courses an average finance students takes. Your math minor and the courses you listed in math would prepare you just as well as STEM undergrads for a quant finance masters. However you need to make sure you look at the minimum requirements of masters or PhD programs before you apply.
@Dimitri, please tell me, is cs the best degree to get then? But I don't know how effective it will be as it misses the understanding of finance or economics
I recommend either a quant finance or statistics degree.
Whenever I see this question asked on forums it always makes my stomach churn. Either a lot of these people ACTUALLY don’t look at course material for these programs or are very delusional. The chances of a finance major working through a textbook like Steven Shreve’s and understanding it is close to 0.
I’m a physics major who excelled in group & set theory courses, but working through that textbook and actually understanding the content was CHALLENGING (never took stats classes). But when you haven’t even taken high level calculus or stats classes and thinking you can just learn ito calculus and Brownian motion etc on the fly is VERY naive. Additionally, I’m not even considering the type of skills of problem solving skills that they’ve never had to do. Putting it bluntly, it’s like asking a high school grad to enrol in a master’s program.
If you’re driven by money, it’s far worth your time to stay on the business side. You’re just too far behind in content and the type of problem solving skills. Like Dimitri said, he had to catch up for lost time because he was so far behind in the required math.
"You're just too far behind in content and the type of problem solving skills ."
You could have said the same thing to Edward Witten just after he graduated in history.
@@arunavaghatak8614 I don't know who that is, but it doesn't really matter. Finance majors going into quant isn't gonna happen unless they take fundamental math classes. They're competing against mathematic & physics PhD grads and MS financial engineering holders for these jobs
@@TTTTTe550 en.wikipedia.org/wiki/Edward_Witten
Once in a blue moon, but I guess it does happen.
Hi, I have a finance degree, have been working for 5+ years and realized I like the analytical side of finance way more than the client-facing side. I figure due to my background, a quant career is highly unlikely. Do you think switching to the data analytics/data science side of finance would be a good fit?
If you enjoy doing the analytics, moving to an analytics team should be a good fit.
@@DimitriBianco appreciate the insight!
Hi Dimitri, I have a bachelor degree in Business Administration & Economics and I want to apply for a Master Degree in Quantitative Finance. Is it possible to become a risk manager or an asset manager with a quantitative finance master? (due to my background becoming a quant seems unlikely and impossible)
Hi Dimitri, I think I finally understand the difference between quant and traditional finance. Is it that quant do the number crunching while traditional finance interpret the results from quant?
No. Traditional finance uses simple calculations and analytics while quants build statistical and mathematical models. It's more about applying deep math and stats theory to finance not about just crunching numbers.
@@DimitriBianco Thank you for replying, I just got to say I found your content yesterday and absolutely love it😊
I'm still struggling understanding what exactly a financial analyst do then because I thought they did what quant did. Also why would any company hire a financial analyst when a quant can do everything plus more?
I studied Calculus 1-3 in high school as well as some Real Analysis on my own. Do I only need Differential Equations and Measure Theory(-tic probability) and stochastic calculus? Will this knowledge enable me to get an MFE (I studied stats in my Bachelors; would it be better to go for a Master's in Stats instead along with something like an FRM to cover the risk part?)
Most programs just require Calc 1-3, ODE, and PDE. Real Analysis is a bonus.
An intro probability and statistics course is also required by many programs.
@@DimitriBianco Alright, thanks. In case you know of FRM's content, is the statistics covered in FRM's Quantitative Analysis (Probability, Prob Dist, Hypothesis Test, Regression, Time Series, Simulations) enough for an MFE or M Stat? Many universities require a Bachelor's heavy in Mathematics; my business degree had Statistics but no Math.
@user-gz5ho8br2o the FRM only covers the quantitative topics at a high level meaning you'll know what they do but you won't learn how to use them.
The short answer, no, the FRM won't cover any meaningful math or stats.
Just tell people to take CQF certification. They need to get started somewhere .. somehow. Can't discourage anyone who doesn't have background but is keen on learning this stuff.
WQU would be a better start as it is free. The CQF had a fairly expensive price tag.
I’m looking to get into PE/HF or some form of financial analysing in the future, I have an option of MSc in statistics, quant economics or High performance computing. Which do you think would be best? I feel the high performance computing would be as it’s so rare that few will have the skills it provides
For private equity you'll want a business degree like an MBA not a quant degree. For hedge funds it depends on the fund, whether it's traditional finance or quant. The type of degree will decide what you do at a firm. CS type degrees mean you'll be working on implementation while stats and math are more for research and model development.
@@DimitriBianco would you personally think a master's in high performance computing would be useful? I see there's only 2 in Europe so I do believe I'd stand out. I also have the highest score for finance in my university in my bachelor's and the highest score for Chinese
If you want to be a computer scientist at a hedge fund or algo firm then it could be a great option. If you want to be a quant and build math and stats models then it's not a great degree for that.
Dimitri, since you mentioned it, what Myers-Briggs personality types make a good quant then?
I don't think anyone should let a personality test define themself or their career goals. You are what and who you make of yourself.
I think INTJ or INTP is a typical quant
@@WolfAngelRock Some personality traits are found to be genetic to a certain extent so they are probably not total BS (though maybe not MBTI).
I think personality tests can serve as guidelines in self-introspection.
I'm a big fan of the Myers-Briggs as I have seen it to work fairly well at defining people. Yes, people change over time and most people fall towards the middle of the 4 categories. Many people don't realize the tests have percentages between the binary classes. For example, if you are introverted, how introverted are you?
I am an INTJ and percentage wise, I am far from the middle in each category (I am somewhat polarized). I usually re-take the test every year or two to see how I am changing. Quants can come from many if not all personalities however I have found that the "Decisions" (T vs F) is very defining. Those that have a high T score excel at being quants where as those that have a high F score excel at traditional finance and management. For me doing deep dive analytics and knowing very intricate details about statistical assumptions or model structures comes very naturally to me. As I transition more into a management role I have to work a lot harder. I can come off as cold or non caring when working with people. I also have to try and weigh what is correct versus what is feasible for the business' needs more carefully. This personality trait is a big hurdle for the industry as you need quant managers who really know what's going on when it comes to technical matters however you also want a manager that can build teams and add value alongside the business.
INTJ here, too.
I’ve heard if you get a job working for a financial company (one that participates in trading) there are highly restrictive regulations on how much personal trading you can do on the side. Can you comment on how true this is in your experience?
If you have access to non-public information then you can't trade those securities. As for a company not allowing you to trade, I can't speak on that however if I were a trading firm I would not allow my employees to trade on the side.
Hey Dimitri what is your opinion on the double degree at UPENN. I want to be a Quant and plan to get a bachelors in cs and masters in fiance or stats. Doing this at UPENN would allow me to get both in 5 years. I promise my goals are aligned with quantitative finance.
make sure to read up on basel iii and risk regulations. banks are getting squeezed to death by regulation and money from trading are down. jobs in those area are little while data science are hiring like super crazy. hope this will help your decision
This is a sound plan if you do the masters in stats. A finance masters isn't enough to work in quant finance.
hi, im a student of a undegradet in busines and finance in chile. I want to improve my maths and stats, which books do you recomend??
thanks
What would be your advice for the first year business/finance student who would love to switch to quant ?
I would change your major to statistics. It will open up a lot of opportunities in quant finance as well as other areas. You can also minor in finance to get the basic finance skills as well.
Could you become a quant with a PhD in traditional finance? Finance PhD’s use multi variable calculus, linear algebra, econometrics, coding, etc.
It's possible but unlikely. Many of them will still be behind even after completing their PhD.
Which app do you use to write out the formulas on the screen?
I often require them to know the model so no app is needed. For large ML models like decision trees the packages can output the tree. The equating should be written in a word document.
I am currently working as a Data Scientist for a fintech firm, I wanted to pursue Financial Engineering. Yes, I do love math/stat/fin domain. Is It going to be a big switch?
Have you taken real analysis? Stochastic calculus is the foundation of financial engineering and it requires measure theory and real analysis.
These are the hardest areas to master and require a strong math background.
Why did you decide to work in validation rather development. Does it not get frustrating to dig through other peoples code all the time instead of writing your own?
There are pros and cons for every role. I've actually worked across the entire model life cycle (development, validation, implementation, and audit). I enjoyed working in development as you get to go deep with modeling and model usage details. There is a fair amount of coding and it's fun to have a team working towards one project. Validation on the other hand gets a high level model perspective with the opportunity to dig deep on a specific part of a model. The entire development process must be validated however some of the tedious parts such as data clean is straight forward to review. A developer would have to spend more time on these parts which is a con for development. My validation team is in a mature state so we also build challenger models to show developers how a model could be built better or to show how and why their current model will fail.
Another pro for validation is being able to see many different models. A developer will spend more time developing than a validator typically spends validating. This means I get to see all sorts of credit model, operational risk models, market risk models, and PPNR models. At larger banks you typically are focused in of those four areas however within those areas you see a lot of different types of models and usages. Now one of the big cons of validation is the amount of reading and writing. A model developer will develop a model and write the final report explaining the entire process. A validator now has to read the entire report along with a long list of other documents such as model development meeting minutes, previous validation reports, and previous development reports. Then we do some fun statistical analysis, model testing, and challenger model development if we're lucky. After that we then have to write a report (usually around 80 pages) plus about 5 other documents on model issues, remediation efforts, risk ratings, and effective challenge meeting minutes. I should also note than many validation teams prefer or require model development experience before joining the validation team. The reason for this is so that you fully understand how a model should be developed along with some understanding of their process and potential issues.
Oh and to respond to your code comment...yes it's frustrating when code is written poorly. If you write poor code I try to mention it in the report as well. But what's even more frustrating is when developers make simple model development mistakes and then you have to meet with them to explain they basically have to start over or make significant changes. Working with people and delivery bad news is a good skill to have as a validator. Both validators and developers in banking also have to meet with regulators for model reviews but usually this is a management job.
@@DimitriBianco Thank you for the detailed reply! What was the funniest reason that someone has ever given you as to why their model is good and your comments are wrong?
I am currently in my physics masters degree and would like to work as a quant. Would you recommend me doing a PhD and if yes rather physics or some other field?
It depends on your interests but there are quite a few quants with applied math, statistics, and econometrics degrees. It is possible to switch over with a physics PhD however it should be easier if you find a degree that is more closely related to quantitative finance.
Why did most of your financial engineering classmates not end up in quant jobs? Any videos on this?
I'll make a video as I am sure many would like to see the details however I will lay out some of it here for you. The low quant job placement rate is a global/industry problem and not unique to any one school. If you look at quantnet you'll see the average (non-weighted) 3 month placement is 79%. You would assume that going to a program would give you a high probability of being a quant however job placement is different than quant finance job placement. A large portion of these students who find jobs end up in non-quant roles. Most programs will argue with this however it comes down to the definition of quant finance. I know a lot of MFE grads who go on to be traders, analysts and entrepreneurs at cryptocurrency firms, financial analysts at banks, wealth management analysts, consultants, and tech professionals. Now don't get me wrong, many of these jobs sound great even to me. I define quant finance jobs by two criteria though. One, the skills of the job need to be "quant finance" meaning a mix of math, stats, and computer science. Two, they need to require a graduate degree. This definition is too strict for many people and I am fine with that. The real disappointment comes from students who paid a lot of money on a degree and loved the field only to end up working with a bunch of undergrads in an unrelated area. This is really a blow when you realize you could have skipped the masters which would have saved you time and money.
If you look at the numbers from an industry perspective, having low quant job placement makes sense. Most banks and investing firms only hire a few new entry level quants each year. Some large banks hire more and some small banks or firms hire less. For example, a mid sized bank would have a development team and validation team which would be around 60 people. They usually bring in around 4 entry level roles each year. Let's say there are 200 firms which would mean there are 800 open roles for the year (US example). If you only look at quantnet, you'll see there are 1,736 students enrolled in programs. If half graduate each year we have 868 students to fill 800 jobs. 68 unemployed students will still give us a good placement rate. However most firms prefer PhD graduates and we also hire those from a variety of other quant backgrounds including statistics, econometrics, and mathematics.I have no idea what numbers to guess for these additions however I can tell you out of about 70 people I've worked with over the last five years, I've only had 5 who had some sort of financial engineering/quant finance degree. Those aren't very good odds, at least from my perspective. Getting hard data on this would be fascinating however schools and companies would not like to provide this data as it makes them look bad.
In general the US is very competitive. It's really a global market as most quant finance professionals and students come from abroad. This makes it very competitive as you have people from every country and given that there are more graduates each year than jobs, it results in low job placement rates. From my personal perspective (not data backed), some programs have high quant placement rates and some have very low placement rates. With a boom in new quant finance masters programs, there continues to be too many students and not enough jobs though some of the top programs do have great quant job placement.
@@DimitriBianco is the situation in Europe or Asia different from the one in the US? I'm studying Mathematical Engineering (Quantitative Finance track) in Italy and don't know where is the best place to start my career
Does this mean that with my undergrad degree in economics I’m screwed ? Is that what you’re telling me Dmitry
If you haven't covered enough math and stats it will be much more challenging. I came from traditional finance and economics to quant finance but it was very stressful.
@@DimitriBianco Thanks for your reply , If I were to self study, which topics of maths and stats I should focus on ?
Hey i have a question
If u have a financial market undergrad and i do some mathematical and statistics certifications or short courses then can i apply for ms in quantitative finance
Every quant masters has different requirements for applications, so look and see what programs require. Programs also teach different material and have different focuses. Some programs welcome business students however their focus is more on high level application than the small details.
Im currently doing an MsC in Finance, where i have classes that cover machine learning for finance, econometrics and financial mathematics. Do you still think that i dont have a shot at quant finance?
No, there won't be enough depth covered on each topic. You can try and apply though. Some firms may think there is enough.
You will probably need to study Real and Functional Analysis, Stochastic differential equations, Model Identification and Data Analysis to truly understand the math behind
12:10 Did you mean "someone who has a math degree will blow someone out of the water with a stats [finance] degree"?
For financial engineering (meaning engineering derivative products) will require a lot more math than other areas of quantitative finance. For example, I work in risk management where we build statistical models. Having a deep math understanding in say stochastic calculus isn't very useful for us. What I'm pointing out is that different areas of quant finance need more focus in different quantitative areas.
@@DimitriBianco Thank you for taking the time to respond!
Do you see many Quants with civil engineering undergrad, that of course pursue masters/PHDs after undergrad that then have become quants?
I have seen many engineering backgrounds in grad school but not many go on to quant jobs. I don't recall who had what engineering degree though. The math from an engineering degree should prepare you well for a quant masters. Just remember engineers don't know everything. Their egos often prevent them from getting quant jobs.
@@DimitriBianco Why is it generally that they don't get quant jobs other than their egos? Thanks and I love your channel!
Nice 👍🇧🇷
can I become a trader without a quant degree ?
Technically anyone can be a trader. All you need to do is sign up for an account and trade online.
Now being a successful trader is a challenge. Some take a traditional finance approach (no quant degree needed) and some take the quant route (quant degree is needed). To be successful at trading though, you really need a team of people including investors. The online ads of turning $500 to $100k is a joke. They are just looking for people to pay them money for their "education."
people still go there coz they love money
Maybe somebody have a better idea, then building a hedge fund inside crypto trader bots based on predictions? :)
If you enjoy math proofs you might have a chance
That's very true!
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