Just as a recommendation, for those who are coming from a computer science background. I would recommend going through the "Statistical analysis of finacial data in R" first out of all the book recommendations. It has the most familiar content in terms of the mathematics to what I was doing in my degree and it also starts introducing the underlying probability theory that is used in finacial mathematics too. I'm just starting the first two books on finacial calculus and its helped me so much from my starting point in that order.
Totally agree, particularly as a lot of buy-side quant funds are moving away from SDE modelling and more towards ML. Additionally, even on the sell side, they'll typically target physicists over mathematicians or statisticians for modelling as it's their forte. Lean into your strengths as much as possible IMO, all of the skills across the CS - Math - Physics spectrum are required and it's unlikely you'll possess them all until you've got decades of experience (and probably not even then as the literature never stops moving forward).
Hey QuantPy, I brought the two Stochastic Calculus books you mentioned here. I read the first one through, did all the exercises by hand and used the techniques to write an option pricing application for my portfolio. This most definitely was a huge factor in me getting my first Quant Dev job in finance ( I came from sports betting). Thank you so much for the recommendation.
Quant here, I read those books. You better know your mathematics and programming. It's very competitive. Use your knowledge of finance, engineering and programming to trade. What better way to show your thinking than winning trades
I would presume actually benefitting society, and not showing how good you are at stealing from consumers who have been manipulated to buy. Maybe I'm wrong, maybe life is about trading, and nothing else is important. Silly me. What better way to show how useless your thinking capacity is than to make such a fucking statement 🤣
Quants is an interesting topic. A topic that is applicable to computer science, financial engineering and artifical intelligence which will open door to quant science. I look forward to more quant research and research publications.
This guy said “are you even a quant if you don’t understand financial math”… Finance majors, MS, & certified learn financial math to the point you don’t need a computer programming software to develop models to make decisions. You can use the same data, make evaluations, & forecast with calculus, algebra, & applied stats. If you have these skills, you can master probability theories without computer science. That’s probably why the door is small.
A quant trader does not use market fundamentals like traditional stock market investors. Instead, he uses strictly technical analysis. A quant trader uses historical market data, mathematics, and statistics. This includes market volume, price action and support and resistance. This back-tested trading model is extremely consistent and therefore very reliable.
Currently working as a developer (non quant) in a team of 7 senior quant researchers under the CEO of a multi billion dollars hedge fund. No clue how I got myself here, but trying to become a quant dev - will try your books and come back to you, thanks!
@@dylancam812 I’ll be honest, I’m quite young (24), and haven’t specialised in any field of software development. So I’m seizing the opportunity that’s currently in front of me. I have a unique opportunity to learn from the very best in the world. But they won’t teach me the fundamentals, I need to do that by myself. I’d say (from low experience), that fields close to traditional engineering are more interesting, but finance pays better (of course subjective). I didn’t « pick » quantitive finance because of the salary, it was just an opportunity that presented itself. I didn’t actively look for it.
I am a PhD(Math) quant (20 years experience in banks) and there are now hardly any quant roles available in Australia since most of the roles were moved offshore a decade ago, to places like Singapore, where there is a bigger talent pool in this space for companies to choose from. For example, quants from Hong Kong, Singapore and Malaysia at close vicinity. Luckily, there are better-paying jobs for people like us, such as data engineer, data scientist, software engineer, MLOps Engineer. Why work in an industry where you may be taking 4-9 months to find the next available quant role, where you can find an IT role in 2 weeks? Quant is such a specialized niche role that you are putting all your eggs into one basket and there are not many new roles advertised. Most companies don't need an army of quants, but they can use an army of python programmers, for example. Oh, and whilst we are on this topic, I have met too many Actuaries who are supposed to be really smart in mathematics and finance, i.e. ideal for quant roles, who don't know much or have forgotten their mathematics, to be able to become real quants who understand stochastic differential equations.
Maybe not higher paying but close enough. The gentlemen above is absolutely right. Being a quant is kind of like being a basketball player. The few quants at the top make all the money. The rest fight for scraps, where as being a software engineer is like being a doctor, the world has a lot of room for doctors and the earning potential is equally as high
@@ТимофейЧерников-щ2х Yeah being a quant for a good company will beat any salary he just mentioned. Maybe in AUS, there is no available positions, but in the US you will get a min of 200k to 300k, and in EU around 100k to 200k as a beginner.
@@619ry7 That's the pay at top firms like renaissance tech, jane street,citadel etc. Idk about other companies so maybe other companies dont pay as much
Any MODEL is based on some ASSUMPTIONS, these needs to be constant, in order for the MODEL to work. To incorporate externalities, additional variables are added. Those again are constant and can be individually tested ( statistics ). It’s always a good point to start but should not limit one’s judgement.
The video gives good guidance, but for those just about to head to university, personally I don't think it's right to say that the mathematics is extremely difficult. It's just whether the person has the interest and is decent in math & stats, if they do then it's all dedication and putting in the hard work (Hard work meaning you will not be able to party till the day before the exam). I studied Actuarial Science where the dropouts move to Financial Mathematics. It's not as difficult as it seems because if the curriculum is good, they will bring you up slowly from basic linear algebra, hypothesis testing, partial differentiation, eventually to stochastic calculus, so don't be discouraged if you're considering this university path as a person interested in math & stats. While you will need to read the material more than once to fully digest, you do not need to pull all-nighters in this course unlike some other courses like architecture. Also, if you are a quantitative person deciding what course to study that gives high pay, other courses such as chemical engineering will not be much easier so follow what you think suits your skill set best, be sure you know what you sign up for and work for the knowledge
As a quant for about 10 years now, I'd recommend the excellent book "Financial Mathematics" by Campoleti and Makarov for the base background. Thereafter a masters or a phd in the field is appropriate. (I took this route with the aim of building out an entire suite of tools for derivative pricing, simulation and validation). The upshot was that my coding skills were sufficient to get me quickly past the entry graduate roles and into where I am today. Second, knowing at least Python AND C++ are musts. Research skills are fine but in today's era knowing how to program (specifically and generically) are essential.
You can understand continuous time series or statistics or probability without sigma algebra though. Sigma algebra is kind of in the background...primarily to know where the definition of a random variable is coming from. In practice, you don't need for stochastic calculus or pricing derivatives or risk management or portfolio management or financial data science.
Hey Jon, thanks for sharing. Being a quant at a prop shop in, I can say quants have to manage every work stream from data processing, modelling, to trading/reporting. A good quant ought to excel in all those 3 skill sets you mentioned.
Thanks for the vid. I’m eager to take a master degree in financial engineering. However, my background is finances, not enough CS. your vid helps me to understand better.
Love this video and how you explained who is quant and what skills are needed. Having background in finance (CFA) and few years experience in derivatives trading and some programming skill in Python but limited mathematics background I wonder if self-study would be enough to explore these topics. Definitely I will reach for one of these books to try and see. Thanks for inspiring videos!
No. Friends with 1st class degrees in mathematics from top universities struggle with some of the mathematics on MSc financial mathematics degrees. Is hard.
CFA is a great start, and you can definitely lean on those years trading if you want to break into a quant role. If you want to build a stronger math foundation, I would recommend doing the FRM certification. It gives a lot of probability and statistics knowledge, while also going into derivatives pricing & risk management. If you want to go even further, there is a free financial engineering certification on coursera that delves into a lot of the higher level math like PDE’s and martingales, and also covers the more advanced derivatives products. All the best in your journey
@@lancemartin1836 CFA is not really useful in trading. Masters in financial mathematics is better if going down quant trading route. CFA is better for asset management etc. Or just do a Masters in Finance.
@@dac8939 I agree with you. It’s just not always practical for everyone to do a masters degree, you know? But I would agree Master’s route is generally the best.
I just have a kind of confusion: do you think we learn enough measure-theoric probability with Shreve’s vol2, or it is just what is enough to a first look at Stochastic Calculus? As you have said that you didn’t buy a book on theory of probability during your training, so you do think that a huge knowledge of measure theory isn’t that useful? Just the elements of Lebesgue integral and measure given by Steven Shreve in his Vol2?
These are bare minimum skills and most of that can be taught, what we look for is people who have extremely strong math backgrounds. Having a very strong understanding of multivariate calc, linear algebra, and higher levels of mathematics (fourier transforms)... along with some programming knowledge. If one understands these areas the finance areas can be taught, but not the other way around.
@@abesstooicy5511 They are not looking for any masters or PHDs in quant, math, physics or CS. People in masters or PHDs usually start to show focus in a particular area of finance or econ. This is what the firms want. This also means that if your PHD math/physics is studying black holes or your CS degree is into something more computer technical then you are less useful.
I'm really interested in Financial markets and analysis. But I'm not really gifted in mathematics, just average, so I'm not sure I'd make a Quant. I've completed an IT degree and can code in various scripting languages.
You will be good at math if you just spent the times doing it. You just need to force yourself doing some very abstract thinkings sometimes. It will be painful at the moment. But after you understand it it will become easy. Sometimes it takes few hours or even days to understand why this works exactly. All you need to do it to stay calm and keep thinking.
Hi, thanks for the awesome video and book recommendations! I'm currently waiting for my Quantitative Finance Masters to start, guess i'll try to dig into some of the books before I get destroyed completely when school starts xd
Hi ! It was a pretty good video, but I think you didn’t mention the QIS (Quantitative Investment Strategies) department which design the systematic hedging strategies and the systematic indexes strategies among others, I don’t see this part of quant finance a lot in quant videos. I recommend you to do a video on the subject since it’s really interesting but quite obscure to the public :)
That’s great. One of my favourite books is from emanuel derman my life as a quant who came from a Physics background. What I would say, if they’re working in derivative valuations (/not data analyst jobs) then they would have had to learn financial mathematics in their own time, or with internal resources. I believe you can’t skip the theory?
Thanks for the question. Sure, you can change the underlying model to whatever you’d like and the probability measure to whatever you’d like. For example in your case you could adjust the growth rate of the stock to align with your directional view. However, sounds like you’d like to fit models to directional strategy. I’d caution this, the true winners in the financial markets are the directional players (who work off commission and service fees) and the directionless players (who work off bid ask spread and commission). Retail investors looking for alpha strategies is wishful thinking. Not that it’s impossible…
@@QuantPy Hello. I am a retail investor. I trade CME Futures. I think you are right. Finding an aloha strategy is wishful. But, can you please tell me how I can trade with the banks? Will your financial course teach me how to do just that using quantitative financial analysis?
Good video, but this narrow definition of what a quant is and does is very much that perpetrated by academia and banking, both which have a product to sell. In reality I would include all the roles on the buy side, where one takes a quantitative and systematic approach to devising trading strategies and construct investment portfolios. Also, on the buy side, a practitioner’s role almost always includes vetting and evaluating trades, strategies, products ‘sold’ to you by either banks or fund managers, and even colleagues - and you can’t develop an effective BS detector without having a pretty good understanding of both the theory and the reality of markets. Also, I would emphasize the importance of real-world data analysis - too many quants spend too much time learning to derive sophisticated quant models from first principles, but are lost when given, un-processed, raw, real-world data.
I've been told becoming a quant might be a good path for me, but after a bachelor's in math and some minor certifications in coding and data analysis...it just feels too abstract for me, I think. Seems like a shame, since I seem to have the aptitude for it and a systematic, analytical mind. But I get too restless at a computer more than a few hours a day. But it is what it is.
Ex-hedge fund quant here. This is a good intro, I think the couple of other quant roles I would add are quant trading and quant risk. Both of these roles typically sit on the trading floor.
I've read a couple of books about the folks that do this for a living, and I've seen the movies 'The Big Short,' and 'Margin Call,' too. All informative. My earned degree in Mathematics was accomplished well before cheap computers came along, so I have a skewed point of view, at least in today's lights. But still, I find this interesting. Timing seems to be a key factor. Just like in the movies.
Hey, Thanks for such comprehensive video on this topic. By any chance do you have any track in your mind? by that I mean let's say I am planning for masters what kind off specialization should I be looking for ? I have a CS background, do you recommend going for financial engineering kind of domain or more CS centric domain like high performance computing along with my own exploration of the book you recommended is better suited? Thanks in advance.
If you’re interested in quant finance, and come from an a background. You’d be a very strong applicant for implementation desks at firms. But of course job satisfaction is up to the individual, but you do really want to follow your strengths and interests I believe. I would only recommend the stochastic calculus books to people intent on studying financial mathematics, and want to do quant research. Implementation, as a entry level start it’s your cs skills that matter. Of course the more about derivate pricing you know the better. The implementation book would be more suited to you if you’re heading down that path. Good luck out there!
@@QuantPy Is it necessary to take a course (say MS in Finance) to get an entry level job in the Finance world? I'm from a CS background too and a bit confused with where to start. I want to go into the Quant trading domain. Basically an intersected domain where CSE skills (Python, R, Machine Learning) could be used along with Finance stuffs like Derivatives, HFT, Quantitative modeling etc. Any suggestions where should I start from? PS:- I love reading books. Thanks.
Electrical Engineer here. Why do all the quant jobs make you do mental math tests of the high school level when applying? 88 question in 8 minutes. What are realistic scores for these?
Great video. Are you currently employed as a quant yourself or successfully using what you have learned so far in trading financial instruments? If so, is the stochastic calculus and financial maths the difference in your success?
Hi Jonathan, Which masters program for Financial Mathematics would you recommend in Australia? Just trying doing some research to plan out my studies :)
Hi @QuantPy, thank you for the informative video? Do you give career advice? I’m a software developer with a MSc in ML applications thinking of trying to break into a quant dev role?
QuantPy is a company ? I've heard the term quant before and it seems interesting, but I haven't delved into it in depth. In general it seems that I understand the concept because my background is information technology (computer science).
What textbooks or courses do you guys recommend as a prerequisite/ base background knowledge before getting onto Stochastic Calculus, etc.? Because, I have BSc Chemistry background.
There is a conceptual mistake in the beginning. Replication/hedging of any contingent claim on the market AND any asset behaving like martingale(ensures no-arbitrage condition) assumptions are BOTH necessary in order to price with either PDE or E_Q approach.
thanks a lot for your video. I have a background in mechanicals and now want to begin quant. Besides your mentioned documents, how do you think about: "Paul Wilmott introduces quantitative finance by Paul Wilmott"? Thank for your response
Nice one, I haven’t read his introduction book, but I really enjoyed his Frequently Asked Questions in Quantitative Finance. Would highly recommend that book
Wow thank you for this content I and looking to expand in my career and your video has really helped me take a step forward, I was wondering however, Is there a book recommendation if we are interested in implementing models using machine learning?
Hi there. I would ask you a question in the matter of your stochastic calculus books recomendations. How necessary do you think it is to study the binomial asset pricing (vol. 1) before moving to study the continuous time models (vol.2)? I mean, this subjects deals with the same class of finance problems but only in different time scale levels? Or they have distinct applications in practice? As i mentioned before, i am already studing the vol.1 and my question arises (mainly) by my curiosity in moving to the continuous time models. Again, sorry if I do not sound so polite as i wish. My intention was the best. Your job is incredible!
@@danielwit5708 I guess you should not understood my question. I asked him if the books cover or not the same financial applications, but in different scales (discrete and continuous). My question was not about the underlying mathematics itself. About this, the difference is in the book title.
@@brunooww1 I'm not sure you can model same applications in both ways hence they must be distinct. By definition if underlying data is discrete you model it by using discrete processes if it's continuous you use continuous. However I'm not an expert, will let you know whet get my hands on the books 😅
@@danielwit5708 Oh cool..cool. This distinction is exactly the point I attemped to reach. Thank you for the help! It is a fascinant subject, i am really excited.
The sequence in the video provides a very logical and reasonable progression through the material. It’s very unlikely that you’re capable of jumping into continuous time scale models if you had to ask this question. There are orders of magnitude of difficulty separating discrete and continuous models, so unless you’re already a mathematician, the ordering provided in the video is the standard way of doing things! Good luck!
Been using your website mate, useful. Any plan to expand your content to option flows on ASX index? Less impactful when compared to US SPX but it could be something to work on I guess given it also lies in quantitative realm.
Hey man, I'm a statistics graduate in Australia, and want to be a quant. However, I'm apprehensive about studying these books, because I'm not in the industry yet. Should I first try to get my foot in the door? and would it useful to just get straight into the books you have recommended?
As with any career advise you get on the internet, please take this with a grain of salt. Definitely recommend some work experience first to gauge the financial industy - you might find out that being a 'quant' , front office analyst, middle office risk analyst isn't what you'd like as a career path
I have 3 coworkers EXACTLY like this. Regularly coming to me to put together their macro economic variable history for their scenario analysis. All sitting in New York and struggles in English except as applied to the MEVs 🤣 Gonna bug them to join their team soon once I build my skills up.
I come from a Physics/Applied Maths background and am currently doing a Data Science masters. Would these books be sufficient to study to get into Quantitative Analytics?
The quantitative finance he’s talking about isn’t really quantitative analytics. It’s derivatives pricing theory, which is fairly different. In quantitative finance, there are P-quants and Q-quants. P-quants study real-world patterns and distributions and are essentially data scientists. Q-quants apply mathematical theories to price and hedge derivatives, and the mathematical theories have little to do with real-world distributions (only indirectly through vol surfaces). If you’re interested in derivatives pricing, then yes, these books are the standard, especially Shreve’s. I’d also recommend Jim Gatheral’s book The Volatility Surface. Very elegant and concise mathematics. Dirac delta functions. Etc.
Okay wow i really need some guidance, I am a high school student senior year. The only exposure i have to finance through school is economics. I had maths till 10th but then dropped it cause i hated how school taught it. Going the CS or finance route is college gonna be hard for me because of some reasons. Can someone tell me how should i go about learning about ALL of this and more of finance through self study? Book recommendation, videos, or anything would be really helpful. I am really confused but super duper interested in this.
On a serious note 1. I would recommend the book on Probability Theory by Atanasious Papoulis. 2. Then the book Introduction to Econophysics Next what I would like to point is that everything you read on Finance will always use Gaussian distributions as the basic principle. However if you look at real market data you will see that real world is not “Normal”. But the first book that I recommended will give you the tools needed to navigate this abnormal market world.
Hi, I was wondering if you (or anyone else) had an opinion on the book "A first course in quantitative finance" by Thomas Mazzoni. I am a scientist curious about switching to quantitative finance and am in the beginning of going through this book. Does it give a good flavor for what is involved in the professional world of being a quant?
Is the distinction between education and knowledge important here? I'm getting the impression that the skills are more important that the specificity of education. Are there different routes to this kind of role?
I am not too fond of the first Shreve book. Sure, the discrete models are quite important, but Sherves book is just plain boring and a bit messy, I think. The second volume is pure gold for a beginner though. That is the book I used to get into the subject. It skips a lot of technical details though. For those Sheves/Karatzas harder book "Brownian motion and stochastical calculus" is really good, but not an easy read for a beginner.
My dream is to be a quant, im an econ & finance major in an OK uni in Canada, 4th year student with high gpa and top of the class for 2 derivative courses. I am also decent with python & machine learning (made a few small finance projects for fun) Problem is getting into a good grad school for quantitative finance.. will probably jus have to settle going for a masters of finance in a competitive school and take w.e job i can get
Hi I took you book recommendations and I am starting the Rene Carmona's Statistical Analysis of Financial Data in R book but I cannot find the Rsafd library available online. Do you know where I can find it? it seems to be deleted from his websites
im interested but before i dive deeper and decide to invest my time and money following this carrer, could I know more about how this has benefited you in your day to day and more importantly how profitable you are on your options trade assuming thet you do option. I would be more inclined to believe that this is a safer study to try out to get a better read on the market if I were to know more if you are a profitable trader since I correlate the 2 and feel as tho they are good indicators that there strat is working.
So for someone who has a solid knowledge in programming but very poor mathematical background, which book should I start with ? I think the best is the first one but I am afraid I'll get bored because its all theory ! And thank you for the very informative video.
None, quants suck as traders and are better at developing fin products for the sales desk. The traders that developed Stat Arb trading were computer science majors. The pure quants are really sell side and few traded successfully like Fischer Black. Look at Claude Shannon’s work if u want to trade.
For someone with a very poor background in mathematics, you will face an insurmountable wall of advanced calculus in these books. You may find that you need to revise Year 12 maths first, then spend a year doing first-year maths, then a year doing second-year maths, etc. Unlike programming, you can't bypass years of the missing foundation since mathematics builds on itself and gets progressively harder.
Great and well explained video. Also, I would recommend Hull J.C.-Options, Futures and Other Derivatives_9th edition, which is literally the Bible for Math majors, finances, and financial lawyers. It is a good transitional video from undergrad to graduate knowledge
@@kaiwang2924 Great book, you'll encounter some PDE models, but don't be intimidated, just go to your university math department or the math department of any nearby university. Simply, a beautiful book.
so i am CMA Holder also know programming create flutter application on google store so can i be suitable for this position and know i am ERP Consaltant?
Hi Jonathan! I have a question. So I have a background in Masters in Quantitative Economics from Indian Statistical Institute Kolkata and after that I have been working as Risk Model Validator at UBS bank. I am interested in doing something that requires me to be involved in mathematical derivation and statistical knowledge to develop a quantitative model. I want to keep studying mathematics and statistics as a part of my job. I believe Quant Research is the role for me. Do let me know if you think so. And if I understand the 4 books mentioned in the video, thouroughly, then do you think I should be able to find Quant Research role easily?
I am a physics major trying to get into quantitative finance. I love studying math but I dont particularly enjoy programming, I can use it as a tool if its required for some problem solving. Can anyone tell if becoming a quant is more math or programming? Can I successfully become a quant without doing a huge amount of programming?
I am currently doing a mathematics/statistics double major, hoping to eventually become a quant. I have no room to take any finance classes. Would they be necessary to take? Or would the maths and stats classes be alright?
I studied R programming last year and had to go to hospital for emergency surgery for a perforated colon and abdominal infection. I'm not saying that R caused it, but I'm warning people.
Just as a recommendation, for those who are coming from a computer science background. I would recommend going through the "Statistical analysis of finacial data in R" first out of all the book recommendations. It has the most familiar content in terms of the mathematics to what I was doing in my degree and it also starts introducing the underlying probability theory that is used in finacial mathematics too. I'm just starting the first two books on finacial calculus and its helped me so much from my starting point in that order.
you need to learn technical analysis instead
Hello arif, for me to start on zero with background just in engineering, what is your suggestion for books or any resources to start?
Totally agree, particularly as a lot of buy-side quant funds are moving away from SDE modelling and more towards ML. Additionally, even on the sell side, they'll typically target physicists over mathematicians or statisticians for modelling as it's their forte. Lean into your strengths as much as possible IMO, all of the skills across the CS - Math - Physics spectrum are required and it's unlikely you'll possess them all until you've got decades of experience (and probably not even then as the literature never stops moving forward).
@@mizutofu learn all of it. why would you ever stop learning.
Can we do stuff with js framework rather than r
Hey QuantPy, I brought the two Stochastic Calculus books you mentioned here. I read the first one through, did all the exercises by hand and used the techniques to write an option pricing application for my portfolio. This most definitely was a huge factor in me getting my first Quant Dev job in finance ( I came from sports betting). Thank you so much for the recommendation.
Hi Joe, great to hear this. Did you refer any video lectures to understand stochastic calculus book ?
Did those books help you create algos that made profit ?
Nice. What was your starting salary?
why did you leave sports betting? tell us your life story in this comment section
@@afterthought6889 yes how many kids do you have ? Did you experiment in college ?
Thank you for this video. I normally never comment, but this video is so valuable for me that I thought I should shower you with some appreciation
This is ...perfect. I had a course of 2 hours on it in Marseille and you summarized it in just 10 MINUTES !!!! Bravo!
On peut adapter des stratégies sur des timeframes plus courts du genre 1-5min ? J'ai l'impression que les datas restent plutôt daily, en quant.
Quant here, I read those books. You better know your mathematics and programming. It's very competitive. Use your knowledge of finance, engineering and programming to trade. What better way to show your thinking than winning trades
I would presume actually benefitting society, and not showing how good you are at stealing from consumers who have been manipulated to buy. Maybe I'm wrong, maybe life is about trading, and nothing else is important. Silly me. What better way to show how useless your thinking capacity is than to make such a fucking statement 🤣
@@davidjohnson8655 lol okay
I agree... if you're not using your talents and skills to actually better the world then you're useless
@@yannickyannick3317 banking can be ethical too though?
@@esteban_ruiz there's nothing ethical about present day banking as it's currently constructed .
Quants is an interesting topic. A topic that is applicable to computer science, financial engineering and artifical intelligence which will open door to quant science. I look forward to more quant research and research publications.
This guy said “are you even a quant if you don’t understand financial math”… Finance majors, MS, & certified learn financial math to the point you don’t need a computer programming software to develop models to make decisions. You can use the same data, make evaluations, & forecast with calculus, algebra, & applied stats. If you have these skills, you can master probability theories without computer science. That’s probably why the door is small.
Clearest video i've ever seen on this topico, cheers!
A quant trader does not use market fundamentals like traditional stock market investors. Instead, he uses strictly technical analysis.
A quant trader uses historical market data, mathematics, and statistics. This includes market volume, price action and support and resistance. This back-tested trading model is extremely consistent and therefore very reliable.
which is why they are bad...historical data is basically worthless....people need to read nassim taleb
Most are arbitrage traders, spread trades that can be automated.
bruh stfu, quant traders aren't day traders. Tech Analysis is garbage
This is not true.
Currently working as a developer (non quant) in a team of 7 senior quant researchers under the CEO of a multi billion dollars hedge fund. No clue how I got myself here, but trying to become a quant dev - will try your books and come back to you, thanks!
Why do you want to make the switch? Just curious as I’m currently choosing between pursuing quant and development/engineering
@@dylancam812 I’ll be honest, I’m quite young (24), and haven’t specialised in any field of software development. So I’m seizing the opportunity that’s currently in front of me. I have a unique opportunity to learn from the very best in the world. But they won’t teach me the fundamentals, I need to do that by myself.
I’d say (from low experience), that fields close to traditional engineering are more interesting, but finance pays better (of course subjective). I didn’t « pick » quantitive finance because of the salary, it was just an opportunity that presented itself. I didn’t actively look for it.
@@dylancam812 money
@@dylancam812 money
@@dylancam812exploration and money
I am a PhD(Math) quant (20 years experience in banks) and there are now hardly any quant roles available in Australia since most of the roles were moved offshore a decade ago, to places like Singapore, where there is a bigger talent pool in this space for companies to choose from.
For example, quants from Hong Kong, Singapore and Malaysia at close vicinity.
Luckily, there are better-paying jobs for people like us, such as data engineer, data scientist, software engineer, MLOps Engineer.
Why work in an industry where you may be taking 4-9 months to find the next available quant role, where you can find an IT role in 2 weeks?
Quant is such a specialized niche role that you are putting all your eggs into one basket and there are not many new roles advertised.
Most companies don't need an army of quants, but they can use an army of python programmers, for example.
Oh, and whilst we are on this topic, I have met too many Actuaries who are supposed to be really smart in mathematics and finance, i.e. ideal for quant roles, who don't know much or have forgotten their mathematics, to be able to become real quants who understand stochastic differential equations.
Isn't quant a better-paying role than DS or software engineer? Idk about Australia but in general it seems to be the case
Maybe not higher paying but close enough. The gentlemen above is absolutely right. Being a quant is kind of like being a basketball player. The few quants at the top make all the money. The rest fight for scraps, where as being a software engineer is like being a doctor, the world has a lot of room for doctors and the earning potential is equally as high
@@ТимофейЧерников-щ2х Yeah being a quant for a good company will beat any salary he just mentioned. Maybe in AUS, there is no available positions, but in the US you will get a min of 200k to 300k, and in EU around 100k to 200k as a beginner.
@@ТимофейЧерников-щ2х quant make 500k including bonus
@@619ry7 That's the pay at top firms like renaissance tech, jane street,citadel etc. Idk about other companies so maybe other companies dont pay as much
This is the video I have been looking for, thank you very much!
Any MODEL is based on some ASSUMPTIONS, these needs to be constant, in order for the MODEL to work. To incorporate externalities, additional variables are added. Those again are constant and can be individually tested ( statistics ). It’s always a good point to start but should not limit one’s judgement.
The video gives good guidance, but for those just about to head to university, personally I don't think it's right to say that the mathematics is extremely difficult. It's just whether the person has the interest and is decent in math & stats, if they do then it's all dedication and putting in the hard work (Hard work meaning you will not be able to party till the day before the exam). I studied Actuarial Science where the dropouts move to Financial Mathematics. It's not as difficult as it seems because if the curriculum is good, they will bring you up slowly from basic linear algebra, hypothesis testing, partial differentiation, eventually to stochastic calculus, so don't be discouraged if you're considering this university path as a person interested in math & stats. While you will need to read the material more than once to fully digest, you do not need to pull all-nighters in this course unlike some other courses like architecture.
Also, if you are a quantitative person deciding what course to study that gives high pay, other courses such as chemical engineering will not be much easier so follow what you think suits your skill set best, be sure you know what you sign up for and work for the knowledge
As a quant for about 10 years now, I'd recommend the excellent book "Financial Mathematics" by Campoleti and Makarov for the base background. Thereafter a masters or a phd in the field is appropriate. (I took this route with the aim of building out an entire suite of tools for derivative pricing, simulation and validation). The upshot was that my coding skills were sufficient to get me quickly past the entry graduate roles and into where I am today.
Second, knowing at least Python AND C++ are musts. Research skills are fine but in today's era knowing how to program (specifically and generically) are essential.
You can understand continuous time series or statistics or probability without sigma algebra though. Sigma algebra is kind of in the background...primarily to know where the definition of a random variable is coming from. In practice, you don't need for stochastic calculus or pricing derivatives or risk management or portfolio management or financial data science.
starting a new job as a grad quant next year. Looking forward to it
How much do you earn? And how much is the average compensation including bonuses of quants?
Thank you. I’m just trying to start my career switch from classic investments, equity analysis to quant
Hey Jon, thanks for sharing. Being a quant at a prop shop in, I can say quants have to manage every work stream from data processing, modelling, to trading/reporting. A good quant ought to excel in all those 3 skill sets you mentioned.
One of the best videos i have seen on the topic, thanks !!
Very informative video; thank you for the book recommendations!
Thank you! Life long student here!
Great video mate! In depth!
Thanks for the vid. I’m eager to take a master degree in financial engineering. However, my background is finances, not enough CS. your vid helps me to understand better.
My background is also finances, Not enough knowledge of CS. How do you get into Quants with that.
Love this video and how you explained who is quant and what skills are needed. Having background in finance (CFA) and few years experience in derivatives trading and some programming skill in Python but limited mathematics background I wonder if self-study would be enough to explore these topics. Definitely I will reach for one of these books to try and see. Thanks for inspiring videos!
Same question
No. Friends with 1st class degrees in mathematics from top universities struggle with some of the mathematics on MSc financial mathematics degrees. Is hard.
CFA is a great start, and you can definitely lean on those years trading if you want to break into a quant role. If you want to build a stronger math foundation, I would recommend doing the FRM certification. It gives a lot of probability and statistics knowledge, while also going into derivatives pricing & risk management. If you want to go even further, there is a free financial engineering certification on coursera that delves into a lot of the higher level math like PDE’s and martingales, and also covers the more advanced derivatives products. All the best in your journey
@@lancemartin1836 CFA is not really useful in trading. Masters in financial mathematics is better if going down quant trading route. CFA is better for asset management etc. Or just do a Masters in Finance.
@@dac8939 I agree with you. It’s just not always practical for everyone to do a masters degree, you know? But I would agree Master’s route is generally the best.
Impressive, im starting tomorrow !
Great video. Thanks for sharing all that information.
I love cs im currently double majoring in stats because I admire the math that it has, plus I want to get a phd in a specialized ai field
good shi bro!! keep us posted
Thank you for the content!
I just have a kind of confusion: do you think we learn enough measure-theoric probability with Shreve’s vol2, or it is just what is enough to a first look at Stochastic Calculus?
As you have said that you didn’t buy a book on theory of probability during your training, so you do think that a huge knowledge of measure theory isn’t that useful? Just the elements of Lebesgue integral and measure given by Steven Shreve in his Vol2?
Some knowlege of measure theory before hand in a non finance setting would obviously be more helpful
These are bare minimum skills and most of that can be taught, what we look for is people who have extremely strong math backgrounds. Having a very strong understanding of multivariate calc, linear algebra, and higher levels of mathematics (fourier transforms)... along with some programming knowledge. If one understands these areas the finance areas can be taught, but not the other way around.
The abiding lesson of studying physics was that trying to model three hydrogen atoms turns out to be a pretty difficult problem.
Without a Masters or PhD I’ve come to realise it’s extremely rare to find a quantitative job, with a heavy emphasis on the PhD
is that really true ?
My friend got a job as a quant straight out of uni, integrated masters in mech eng
@@blahbleh5671 bro you said it urself ‘integrated masters’. He might also be the exception and not the rule
@@joelgrey6786 yeh sure, just saying phd doesn't really seem mandatory if you can pop straight out of uni in to a quant job with just a masters
@@abesstooicy5511 They are not looking for any masters or PHDs in quant, math, physics or CS. People in masters or PHDs usually start to show focus in a particular area of finance or econ. This is what the firms want. This also means that if your PHD math/physics is studying black holes or your CS degree is into something more computer technical then you are less useful.
I'm really interested in Financial markets and analysis. But I'm not really gifted in mathematics, just average, so I'm not sure I'd make a Quant. I've completed an IT degree and can code in various scripting languages.
You will be good at math if you just spent the times doing it. You just need to force yourself doing some very abstract thinkings sometimes. It will be painful at the moment. But after you understand it it will become easy. Sometimes it takes few hours or even days to understand why this works exactly. All you need to do it to stay calm and keep thinking.
When I saw a Springer Verlag book on his desk, I knew he was serious.
Hi, thanks for the awesome video and book recommendations! I'm currently waiting for my Quantitative Finance Masters to start, guess i'll try to dig into some of the books before I get destroyed completely when school starts xd
Where you going?
Hi !
It was a pretty good video, but I think you didn’t mention the QIS (Quantitative Investment Strategies) department which design the systematic hedging strategies and the systematic indexes strategies among others, I don’t see this part of quant finance a lot in quant videos. I recommend you to do a video on the subject since it’s really interesting but quite obscure to the public :)
I know some quant researchers that have a PhD in physics and zero financial academic background
That’s great. One of my favourite books is from emanuel derman my life as a quant who came from a Physics background.
What I would say, if they’re working in derivative valuations (/not data analyst jobs) then they would have had to learn financial mathematics in their own time, or with internal resources. I believe you can’t skip the theory?
@@QuantPy i believe the financial part they learn inside the bank. They work in bank of america
Yes, because the processes which are going in physics are the same as in finance, ex. browning motions. So the skill set and the tools are the same
No matter what you say I am a Quant without having studied mathematics
same
Nice video! Have you come across much financial mathematics to benefit from directional price movement as opposed to risk neutral strategies?
Thanks for the question. Sure, you can change the underlying model to whatever you’d like and the probability measure to whatever you’d like. For example in your case you could adjust the growth rate of the stock to align with your directional view.
However, sounds like you’d like to fit models to directional strategy. I’d caution this, the true winners in the financial markets are the directional players (who work off commission and service fees) and the directionless players (who work off bid ask spread and commission). Retail investors looking for alpha strategies is wishful thinking. Not that it’s impossible…
@@QuantPy Hello. I am a retail investor. I trade CME Futures. I think you are right. Finding an aloha strategy is wishful. But, can you please tell me how I can trade with the banks? Will your financial course teach me how to do just that using quantitative financial analysis?
Good video, but this narrow definition of what a quant is and does is very much that perpetrated by academia and banking, both which have a product to sell. In reality I would include all the roles on the buy side, where one takes a quantitative and systematic approach to devising trading strategies and construct investment portfolios. Also, on the buy side, a practitioner’s role almost always includes vetting and evaluating trades, strategies, products ‘sold’ to you by either banks or fund managers, and even colleagues - and you can’t develop an effective BS detector without having a pretty good understanding of both the theory and the reality of markets. Also, I would emphasize the importance of real-world data analysis - too many quants spend too much time learning to derive sophisticated quant models from first principles, but are lost when given, un-processed, raw, real-world data.
100%
Great comment. Very narrow definition of a quant
I've been told becoming a quant might be a good path for me, but after a bachelor's in math and some minor certifications in coding and data analysis...it just feels too abstract for me, I think. Seems like a shame, since I seem to have the aptitude for it and a systematic, analytical mind. But I get too restless at a computer more than a few hours a day. But it is what it is.
Good video. Something new, different even thou Im bad at probability.
Thanks, this is soooo helpful!!
Useful. Thank you!
Thanks for the book recommendations! 😊
Great video! Leaving a reply here so that I can find it later.
I don't want to be a quant but it's important to know the intricacies. I plan to sell quant models. So important to learn for me.
Ex-hedge fund quant here. This is a good intro, I think the couple of other quant roles I would add are quant trading and quant risk. Both of these roles typically sit on the trading floor.
How much did you make? 😅
I've read a couple of books about the folks that do this for a living, and I've seen the movies 'The Big Short,' and 'Margin Call,' too. All informative. My earned degree in Mathematics was accomplished well before cheap computers came along, so I have a skewed point of view, at least in today's lights. But still, I find this interesting. Timing seems to be a key factor. Just like in the movies.
Hey, Thanks for such comprehensive video on this topic.
By any chance do you have any track in your mind? by that I mean let's say I am planning for masters what kind off specialization should I be looking for ?
I have a CS background, do you recommend going for financial engineering kind of domain or more CS centric domain like high performance computing along with my own exploration of the book you recommended is better suited?
Thanks in advance.
If you’re interested in quant finance, and come from an a background. You’d be a very strong applicant for implementation desks at firms.
But of course job satisfaction is up to the individual, but you do really want to follow your strengths and interests I believe.
I would only recommend the stochastic calculus books to people intent on studying financial mathematics, and want to do quant research. Implementation, as a entry level start it’s your cs skills that matter. Of course the more about derivate pricing you know the better. The implementation book would be more suited to you if you’re heading down that path.
Good luck out there!
@@QuantPy Thanks a lot for answering! keep up the good work, best wishes :D.
@@QuantPy Is it necessary to take a course (say MS in Finance) to get an entry level job in the Finance world? I'm from a CS background too and a bit confused with where to start. I want to go into the Quant trading domain. Basically an intersected domain where CSE skills (Python, R, Machine Learning) could be used along with Finance stuffs like Derivatives, HFT, Quantitative modeling etc.
Any suggestions where should I start from?
PS:- I love reading books. Thanks.
@@arpitpachori5746 so what are you doing now?
Electrical Engineer here. Why do all the quant jobs make you do mental math tests of the high school level when applying? 88 question in 8 minutes. What are realistic scores for these?
Great video!
Thanks for you video! It was interesting and a lot of helpful❤ do you have any other recommendations for programming from springer?
Great video. Are you currently employed as a quant yourself or successfully using what you have learned so far in trading financial instruments? If so, is the stochastic calculus and financial maths the difference in your success?
Of course not. Ultra successful traders don't need to waste their time making TH-cam videos
Hi Jonathan,
Which masters program for Financial Mathematics would you recommend in Australia? Just trying doing some research to plan out my studies :)
Thanks, now I know why I'm not a quant.
Great information
Hi @QuantPy, thank you for the informative video? Do you give career advice? I’m a software developer with a MSc in ML applications thinking of trying to break into a quant dev role?
QuantPy is a company ?
I've heard the term quant before and it seems interesting, but I haven't delved into it in depth. In general it seems that I understand the concept because my background is information technology (computer science).
What textbooks or courses do you guys recommend as a prerequisite/ base background knowledge before getting onto Stochastic Calculus, etc.? Because, I have BSc Chemistry background.
There is a conceptual mistake in the beginning. Replication/hedging of any contingent claim on the market AND any asset behaving like martingale(ensures no-arbitrage condition) assumptions are BOTH necessary in order to price with either PDE or E_Q approach.
thanks a lot for your video. I have a background in mechanicals and now want to begin quant. Besides your mentioned documents, how do you think about: "Paul Wilmott introduces quantitative finance by Paul Wilmott"? Thank for your response
Nice one, I haven’t read his introduction book, but I really enjoyed his Frequently Asked Questions in Quantitative Finance. Would highly recommend that book
@@QuantPy thank you so much!
Wow thank you for this content I and looking to expand in my career and your video has really helped me take a step forward, I was wondering however, Is there a book recommendation if we are interested in implementing models using machine learning?
Great video thank you
Hi there.
I would ask you a question in the matter of your stochastic calculus books recomendations.
How necessary do you think it is to study the binomial asset pricing (vol. 1) before moving to study the continuous time models (vol.2)? I mean, this subjects deals with the same class of finance problems but only in different time scale levels? Or they have distinct applications in practice?
As i mentioned before, i am already studing the vol.1 and my question arises (mainly) by my curiosity in moving to the continuous time models.
Again, sorry if I do not sound so polite as i wish. My intention was the best.
Your job is incredible!
The first one studies discrete distributions and the other continuous if you don't know the difference you should learn first about basic statistics
@@danielwit5708 I guess you should not understood my question. I asked him if the books cover or not the same financial applications, but in different scales (discrete and continuous). My question was not about the underlying mathematics itself. About this, the difference is in the book title.
@@brunooww1 I'm not sure you can model same applications in both ways hence they must be distinct. By definition if underlying data is discrete you model it by using discrete processes if it's continuous you use continuous. However I'm not an expert, will let you know whet get my hands on the books 😅
@@danielwit5708 Oh cool..cool. This distinction is exactly the point I attemped to reach. Thank you for the help! It is a fascinant subject, i am really excited.
The sequence in the video provides a very logical and reasonable progression through the material. It’s very unlikely that you’re capable of jumping into continuous time scale models if you had to ask this question. There are orders of magnitude of difficulty separating discrete and continuous models, so unless you’re already a mathematician, the ordering provided in the video is the standard way of doing things! Good luck!
Been using your website mate, useful. Any plan to expand your content to option flows on ASX index? Less impactful when compared to US SPX but it could be something to work on I guess given it also lies in quantitative realm.
Thanks so much.
Hey man, I'm a statistics graduate in Australia, and want to be a quant. However, I'm apprehensive about studying these books, because I'm not in the industry yet. Should I first try to get my foot in the door? and would it useful to just get straight into the books you have recommended?
As with any career advise you get on the internet, please take this with a grain of salt.
Definitely recommend some work experience first to gauge the financial industy - you might find out that being a 'quant' , front office analyst, middle office risk analyst isn't what you'd like as a career path
A Quant is an Asian guy living in the US and working in a US bank, but does not speak English. 😂😂😂
I have 3 coworkers EXACTLY like this. Regularly coming to me to put together their macro economic variable history for their scenario analysis. All sitting in New York and struggles in English except as applied to the MEVs 🤣
Gonna bug them to join their team soon once I build my skills up.
😂😂
What is that a reference to is it worth a watch
His name is Yang and he was top 1 in china. 😮😂❤
@@luhanshaikh5650the big short fs worth the watch
I come from a Physics/Applied Maths background and am currently doing a Data Science masters. Would these books be sufficient to study to get into Quantitative Analytics?
The quantitative finance he’s talking about isn’t really quantitative analytics. It’s derivatives pricing theory, which is fairly different. In quantitative finance, there are P-quants and Q-quants. P-quants study real-world patterns and distributions and are essentially data scientists. Q-quants apply mathematical theories to price and hedge derivatives, and the mathematical theories have little to do with real-world distributions (only indirectly through vol surfaces). If you’re interested in derivatives pricing, then yes, these books are the standard, especially Shreve’s. I’d also recommend Jim Gatheral’s book The Volatility Surface. Very elegant and concise mathematics. Dirac delta functions. Etc.
Hello, thank you for this video, for beginners with background just in engineering, what is your suggestion for books or any resources to start?
Okay wow i really need some guidance, I am a high school student senior year. The only exposure i have to finance through school is economics. I had maths till 10th but then dropped it cause i hated how school taught it. Going the CS or finance route is college gonna be hard for me because of some reasons. Can someone tell me how should i go about learning about ALL of this and more of finance through self study? Book recommendation, videos, or anything would be really helpful. I am really confused but super duper interested in this.
Paisa hi paisa hoga, Babu Bhayya!
On a serious note
1. I would recommend the book on Probability Theory by Atanasious Papoulis.
2. Then the book Introduction to Econophysics
Next what I would like to point is that everything you read on Finance will always use Gaussian distributions as the basic principle. However if you look at real market data you will see that real world is not “Normal”. But the first book that I recommended will give you the tools needed to navigate this abnormal market world.
Hi, I was wondering if you (or anyone else) had an opinion on the book "A first course in quantitative finance" by Thomas Mazzoni. I am a scientist curious about switching to quantitative finance and am in the beginning of going through this book. Does it give a good flavor for what is involved in the professional world of being a quant?
Is the distinction between education and knowledge important here? I'm getting the impression that the skills are more important that the specificity of education. Are there different routes to this kind of role?
I am not too fond of the first Shreve book. Sure, the discrete models are quite important, but Sherves book is just plain boring and a bit messy, I think.
The second volume is pure gold for a beginner though. That is the book I used to get into the subject.
It skips a lot of technical details though. For those Sheves/Karatzas harder book "Brownian motion and stochastical calculus" is really good, but not an easy read for a beginner.
Hey @QuantPy, What are the CAGR and MaxDrawDown of your algo strategies? Have your algo strategies been backtested over a 10-year period?
I have an ms in physics, do you think it will be too hard to get into quant? thanks!
Whats that couple of books behind that 4 books u recomended?
My dream is to be a quant, im an econ & finance major in an OK uni in Canada, 4th year student with high gpa and top of the class for 2 derivative courses. I am also decent with python & machine learning (made a few small finance projects for fun)
Problem is getting into a good grad school for quantitative finance.. will probably jus have to settle going for a masters of finance in a competitive school and take w.e job i can get
Im just starting in this world, so im a bit confused, this quant analysis is for technical investors or fundamental investors?
Technical
Did u have much experience in market making? Any good maths books around mm?
Hi I took you book recommendations and I am starting the Rene Carmona's Statistical Analysis of Financial Data in R book but I cannot find the Rsafd library available online. Do you know where I can find it? it seems to be deleted from his websites
Not sure, I implement the ideas and concepts in Python sorry
Good Day mate!
im interested but before i dive deeper and decide to invest my time and money following this carrer, could I know more about how this has benefited you in your day to day and more importantly how profitable you are on your options trade assuming thet you do option. I would be more inclined to believe that this is a safer study to try out to get a better read on the market if I were to know more if you are a profitable trader since I correlate the 2 and feel as tho they are good indicators that there strat is working.
So for someone who has a solid knowledge in programming but very poor mathematical background, which book should I start with ? I think the best is the first one but I am afraid I'll get bored because its all theory !
And thank you for the very informative video.
None, quants suck as traders and are better at developing fin products for the sales desk. The traders that developed Stat Arb trading were computer science majors. The pure quants are really sell side and few traded successfully like Fischer Black. Look at Claude Shannon’s work if u want to trade.
For someone with a very poor background in mathematics, you will face an insurmountable wall of advanced calculus in these books. You may find that you need to revise Year 12 maths first, then spend a year doing first-year maths, then a year doing second-year maths, etc. Unlike programming, you can't bypass years of the missing foundation since mathematics builds on itself and gets progressively harder.
Great and well explained video. Also, I would recommend Hull J.C.-Options, Futures and Other Derivatives_9th edition, which is literally the Bible for Math majors, finances, and financial lawyers. It is a good transitional video from undergrad to graduate knowledge
Ahh, classic Finance book !
It is literally the book I am reading now.
@@kaiwang2924 Great book, you'll encounter some PDE models, but don't be intimidated, just go to your university math department or the math department of any nearby university. Simply, a beautiful book.
Is this type of trading happenes or it just utube catch ?from dr
so i am CMA Holder also know programming create flutter application on google store so can i be suitable for this position and know i am ERP Consaltant?
Excellent video.
but can you use stochastic calculus effectively on crypto tho?
why wouldn't you be able to?
Whats the difference between "skill" and "skill set," besides jargon?
Hi Jonathan! I have a question. So I have a background in Masters in Quantitative Economics from Indian Statistical Institute Kolkata and after that I have been working as Risk Model Validator at UBS bank. I am interested in doing something that requires me to be involved in mathematical derivation and statistical knowledge to develop a quantitative model. I want to keep studying mathematics and statistics as a part of my job. I believe Quant Research is the role for me. Do let me know if you think so. And if I understand the 4 books mentioned in the video, thouroughly, then do you think I should be able to find Quant Research role easily?
Hey buddy what's your LinkedIn
I am a physics major trying to get into quantitative finance. I love studying math but I dont particularly enjoy programming, I can use it as a tool if its required for some problem solving. Can anyone tell if becoming a quant is more math or programming? Can I successfully become a quant without doing a huge amount of programming?
You're going to need to know some computer programming. There's no getting around it.
being a quant is more programming than math, you probably don't know anything about the markets yet.
Mathematics, Programming and Six-Figures. What more is there to ask for?
I am a computer science student in Turkey. What should I do please can you share your experiences
I am currently doing a mathematics/statistics double major, hoping to eventually become a quant. I have no room to take any finance classes. Would they be necessary to take? Or would the maths and stats classes be alright?
You’ll be right, with that background you’ll be able to pick up the financial mathematics and stochastic calculus
I studied R programming last year and had to go to hospital for emergency surgery for a perforated colon and abdominal infection. I'm not saying that R caused it, but I'm warning people.
Does a CFO need to know about risk in finance bro ?
Very good video BTW
No