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.

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 KZfaq 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

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?

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

That's a good idea. I'll add it to my list.

I'm happy to hear they have been helpful!

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.

You're welcome! Thanks for being a part of the channel!

Very true

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

Thanks!

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: kzfaq.info/get/bejne/q7FojdB8vNSmpYU.html

@@DimitriBianco Thank you, appreciate it!

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.

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.

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!

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?

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!

I just responded on LinkedIn.

Econometrics is a possibility if you take enough statistics.

@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.

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.

I recommend either a quant finance or statistics degree.

This video discusses how to go from finance undergrad to quant finance. kzfaq.info/get/bejne/i7FiiZNor7K5ZZc.html

@@DimitriBianco thank you very much

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!

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.

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.

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?

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.

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.

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.

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.

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.

If you enjoy doing the analytics, moving to an analytics team should be a good fit.

@@DimitriBianco appreciate the insight!

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.

It's possible but unlikely. Many of them will still be behind even after completing their PhD.

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.

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.

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.

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 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.

Yep! I'm from Spokane.

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.

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.

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

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!

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.

Drinking results in memory loss. Being drunk while studying is not a good idea. www.healthline.com/health/alcoholism/alcohol-and-memory-loss

WQU would be a better start as it is free. The CQF had a fairly expensive price tag.

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.

@@DimitriBianco Thanks for your reply , If I were to self study, which topics of maths and stats I should focus on ?

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?

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!

"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.

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."

That's very true!