is dsa necessary for a quant role or is data science knowledge sufficient?kindly let me know as i am very confused whether i should start focusing on dsa or not!!!!!!!!!!!
Thanks for sharing! I love it. I have a small question, If I finished undergrad level of Econometrics with hypothesis testing, linear and non-linear regression, panel data set, time series analysis... which stats book should I start with? Thank you!
Every quant you tuber prescribe different books around 10-20. If you start studying those you need around 10-20 years to start from the beginning 😂😂 With thse many books one can finish engineering 😅😅
It depends what role you want to end up in. C++ is good for quant dev (implementing models) as C++ is very fast. For quant research, Python is a better choice. Firms that aren't as focused on speed might use python for implementation as well. Python is a fairly good overall language.
@tr0wb3d3r5 this has been a recent favorite that I would add. Machine Learning in Finance by Dixon, Halperin, and Bilokon. Link below is my affiliate link. The book is one of the few ML books for finance that is very rigorous and applied with some code examples. amzn.to/4dn1U7z
Just coming back to this video, I've been working through "Introductory Econometrics" so I can lean how to apply my stats modelling skills to a different domain since I'm becoming more and more interested in quantitative finance, specifically the risk stuff. Anyways, I just wanted to say the book is actually pretty fun to work through, but more importantly, there is a small companion book that works through the examples in the text using a computer that I'd also highly recommend if studying that text. There are two versions, "Using R for Introductory Econometrics" and "Using Python for Introductory Econometrics", they're the same material wise and follow the textbook exactly, just pick your preference for language. The packages used include all the data sets from the book and works through each example presented using R or Python. It's made reading the textbook even better. First I'll read an entire section and work through some examples with pencil and paper to make sure I still understand how the computations work and then double back to work through the examples/exercises with the companion book. Also, an FYI for anyone who reads the "Statistical Analysis of Financial Data in R" book, the R packages for that text are way out of date at this point and the datasets used in the examples aren't readily available anymore. I struggled for a few days to get them, but they're impossible to find at this point, it's just a bunch of dead links. I gave up on it even though the information was very good until that point. Not saying the text isn't useful, just know that if you buy it, you likely won't be able to work with the examples throughout the book and will have to just use it for the information to apply to your own datasets.
Lol, no. I read these books over many years of school and a few years after school. I try and read a few textbooks a year but time becomes limited as you become older and busier.
Hey Dimitri! I would like to be a quant someday. I come from a bachelor's degree of economics in business administration. I'm now enrolled in a master's degree in Statistical sciences applied to finance (which should prepare us to be quants). I put my academic path on pause due to my moving here to the US, someday I'll start a similar master's degree here in the US. However right now I'm looking for a job, what's in your opinion the best entry level job to gain the best skills and knowledge needed to pursue a quant career? Thank you for your videos anyway, they are really inspiring 😄
Hey Dimitri, Got a request, please do an in-depth review of WorldQuant University. 1. If their course is good (teaching,depth level etc) 2. If ssk the HR guys you know if they give any value to something like that. 3. In their catalogue they've talked about intellectual property rights in dense legal terms couldn't understand the point where they talk about students employer, talk about it's actual implications. 4. If those topics are available elsewhere for free ? PS- Do you plan on making tutorials on request of the subscribers ?
1) I will consider doing a video on WorldQuant however I try to avoid giving opinions on programs because it's hard to judge them from the outside. All programs are looking at each other and trying to list their classes the same. This prevents people from really judging the rigor of the program. In general, I avoid all online degrees regardless of the university offering it. This includes schools such as Harvard and MIT. 2) For quant finance in the US, recruiters also avoid online degrees unless you have something significant to overcome it such as 5-10+ years of experience at big name banks. 3) I am guessing that are trying to prevent students from copying their materials and redistributing them online as their work. This is a strict topic in the US however many other countries don't care that they steal intellectual property (ideas) from others. 4) No, I don't think you can find all the information online for free. Even if you could learn it for free, big companies (banks/hedge funds) usually require a degree from a good university. A lot of these companies actually want a PhD and will ask you about your dissertation research. I do consider subscribers' requests for videos however a lot of times I am unable to make the videos based on my channel's style. For example, I have been requested to make a video on exploding and disappearing gradients for neural networks. It's a great idea however I want to make sure I have created enough videos so that everyone can be on the same page. It is a topic that will be covered however it will be some time before I get to that video.
Hi Dimitri. I am an IT BA in my mid thirties looking to transition into quantitative finance industry with an FRM certification to my name . I dont have math and CS background in my undergrad although I did engineering. Can I seek your advice in terms of how to structure my journey to quant finance in terms of the approach I have to take . For instance, I am more interested to build a solid base in either math or stats/Datascience and top it with CS part of it.
Most quant jobs are in the US and the most common path to getting here and being qualified is getting a quant masters of some sorts. Quant Finance masters help get a well rounded skill set however other paths would be to get a math or stats masters. Getting a PhD is another path. It takes longer but is cheaper for out of pocket costs.
Das covers more topics than Hull as Hull is more of a very soft and easy introduction. I would recommend just buying Das. These books are a great first time book on products and how they work. The primer book by Stefanica is really meant as a study guide for undergrads getting close to apply for grad school. It could help you plan what math courses to take or act as a review on topics that you may have missed.
There are entire textbooks on cross-entropy but I am guessing that you are interested from a data science perspective. I would recommend, Hands-On ML (my affiliate linked below) as it will cover cross-entropy with softmax as well as many other topics and code you can learn for data science. I linked the second addition which is larger that the first edition and has code updated for TensorFlow 2. Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow: amzn.to/2YfN5ja
Hi Dimitri. Awesome video, thanks! I am a retail daytrader and am looking to turn my strategies into algorithms - I am also looking into HFT. Any specific books on the list you would you recommend for that?
Thanks for sharing such a valuable info...Please make a separate video on books that are your personal favorites, which you suggest someone to study chronologically starting from scratch building foundations and going on to become an advanced Quant.
What are Basic Introductory Is Necessary before going for Primer of financial engineering Please 🙏 Answer my Question dimitri I'm A Medico (no mathematical background) but interested in Trading Derivatives Please guide me @Dimitri
Most quant programs require Calc 1-3, ODE, PDE, and probability theory as they are the foundation. I'm not a fan of trading but to get a better idea of how they work without doing all the math take a look at the book, "Derivatives Principles and Practice" by Sundaram Das
Hi Dimitri, what would you say is the difference between a financial engineer and Quant? Yeah also not too sure where to put data scientists actually, how would you compare their skillset and work to quant work?
Financial engineers are a special area of quant finance. Technically financial engineers are those who engineer derivative products. I view data science as a skill set within quant finance where it is just another set of tools within statistics. Some firms are hiring specific data science teams while others are just nesting it within model development (quant finance).
I'm just getting started and going into a financial engineering program starting September. I was a physics undergrad. Which books would you say are most important for me to look at over the summer? I get the feeling that I should maybe read Emanuel Derman's story, practice programming with R and Python (the books you mentioned), pickup Schreves Stochastic Calc books, and then a book on stats to get up to speed. Is this a good start for the summer or am I missing anything key?
It depends on your background. If you are fresh out of high school I would recommend starting with statistics. Wooldridge's book is the one I would buy first.
I don't think traditional finance is dead however for a quant it isn't as important as math, stats, and cs. I can teach a new hire finance quickly however the other topics take a lot longer to teach. For this reason I don't push traditional finance as much.
@@DimitriBiancoI understood your argument. I have some background on econometrics, causal inference and computer science (banking, corp fin and equity research too, since I'm a phd student in finance/business in an emerging country), but I don't think I am prepared for a quant finance job and I don't like the traditional finance job market due to its deal-oriented focus. What type of work do you believe would be less deal-oriented, focused on econometrics/modeling, but without the requirement for stochastic/financial engineering?
How important are the shreve books for someone to read whose wanting to be a quant but not on sell side derivative pricing? Is it still something I should be reading? Is it like “entry level quant knowledge” for people who are trying to become a quant? Or if I’m not interested in derivative pricing I can skip it?
It depends. For anyone working with derivative products (both buy and sell side), reading those books and learning how derivatives are actually priced is important. That being said there are many quant jobs that do not work with derivatives. I do think it is important to learn about stochastic processes and time-series though as they are the foundation of many parts of finance. I would focus on discrete time-series first though as I find them more important than moving into continuous time (stochastic processes). The credit side of the sell side does not use stochastic processes though which is a really large area for jobs these days. Most quants take derivative pricing but most will never tough it.
I has the same job from high school through college. I worked at a startup doing both manual labor and office work (accounting, finance, marketing, and operations) for a manufacturing company.
Hi Dimitri, big fan of your channel. Have a question for you: I'm a masters student in financial math with an undergrad in economics. I'd like to work as a quant in the area of risk management for a bank but all the postings in my area seem to require at least 1-2 years of experience with CCAR, CECL, DFAST, etc.... My prior experience is a bit limited in this regard (Fed RA supporting academic financial research). What would you advise for someone who wants to break into this area? Are you aware of any entry-level training/rotational programs for grad students?
No, html and css are for web design so there is no need to learn them for quant finance. I'd jump right into R. I have some intro videos to get started if you are interested. ru-vid.com/group/PLBfqPS8Xvt2DtQge5oEpDuD5JMEugySVP
I'm currently pursuing a bachelor's in statistics and want to explore my career options. I'm looking to read about finance. I'm am an absolute beginner in finance, have no idea whatsoever about it. What are some resources you can suggest to gain an insight into finance? Like what it is, the different things in it?
Finance is simple the study of money and value. Key topics to look up are time-value of money, CAPM, and general accounting. If you search online for study materials for the CFA you should be able to find some free resources that would give you a better understanding of what traditional finance is.
Hey Dimitri! Great video! How is the book Elements of Statistical Learning by trevor hastie, Robert tibshirani and Jerome Friedman? And also an introduction to statistical learning by Gareth James, Daniela Wittenberg, Trevor has tie and Robert tibshirani. Thanks!
Hi Dimitri, I am graduating with a bachelors in BBA with a focus on Business Analytics and minor in CS. I'm applying to data analyst jobs, and eventually thinking of getting a masters in either Data Science or Financial Engineering. Just wondering what other steps I should take in order to be a quant. Thanks!
Take as much math and statistics as possible. This will help you with your masters degree but will also help you in your career. I personally define a quant as a process that never ends. When I was in school the big focus was on statistics and stochastic processes. The market has evolved and now data science has become the new hot topic. For me, a quant is someone who is always learning and working at the cutting edge. Being able to train yourself in the newest methods is crucial for quant career success.
I would start with the quant intro books first. Most business students won't make it very far in quant finance without a solid math and statistics background. If it really interests you, I would recommend taking a few more math or statistics classes during your undergrad or consider double majoring in statistics. For self studying, I highly recommend picking one book and working your way through at least a few chapters before deciding to read anything else. I typically spend 6 months on one book to really get a better understanding. Some more technical books that are a good starting point would be the following: Introductory Econometrics: A Modern Approach ( amzn.to/2FVcgNa ) Statistical Analysis of Financial Data in R ( amzn.to/2UisOsp )
Hey Dimitri, wondering if it's ok to start on Adult Hull rather than Baby Hull? I know this question might be a little difficult to answers since you don't know about any of my background, just wondering if you think the bigger book is at all accessible to someone who is just starting a Finance Major (switching majors halfway through college, oops) and is just starting to get interested in financial engineering.
Big Hull is a somewhat middle quant book. It's doable with a finance background as long as your willing to put in the time to fill the gaps you don't know.
Hey Dimitri, can you please elaborate on what kind of math background one would require to make the most of Dan Stefanica's book (A Primer for the Mathematics of Financial Engineering)?
Hey Dimitri, I'm a final year Economics (Hons.) student from India. Over the course of my undergrad, I have developed a strong interest in statistics, mathematics and econometrics and would definitely love to pursue a masters degree which is aligned with these quantitative disciplines (MFE, Quant. Finance, MS Statitics - all seem like a good fit). However, I have not got the opportunity to learn any programming languages (only packages like Stata and gretl which are used in applied econometric analysis). As a beginner with no background in computer science, what (according to you) would be a thorough yet efficient way to learn R and Python? (Should I take a look at some of the textbooks you've mentioned? Or should I take up an online course via coursera etc. instead?) I would love to know your thoughts on this. Thanks a lot!
If it is your final year, I would try and pick up a textbook to learn the basics of the language on your own. R and Python are typically learned while taking statistics classes. If you have the basics down you should be well prepared for a masters course that utilizes R or Python.
@@DimitriBianco Are the Python and R books mentioned in the video suitable for beginners? If not, would you happen to know any good introductory programming textbooks for R and Python?
Hey Dimitri. I love your channel and I get a lot out of it. Thank you for that and I hope you continue with your channel. Let me begin by saying this. I'm a potential doctoral candidate who chose to go the MBA/DBA route because I'm poor at math. If my math skills were as good as yours I would be in a doctoral program for economics as we speak. So while my understanding of economics from my personal readings is above average, my technical/mathematical understanding is primitive if not outright ignorant compared to yours. Here is what I what I would like your take on, or an idea for a future video. An economist of today would more accurately be described as a mathematical economist. This mostly has to do with the way mathematics has taken over economics(for both good and bad obviously). How would you describe the differences between someone of your profession and the average economist? From certain angles it looks like you're much the same but in reality I'm guessing the two tribes are very different. I would even go as far as to saying that if economists were as technical as the average quant their publishing would be far more accurate. If you could elaborate on this I would greatly appreciate it. Thank you.
I have never read a book for SQL but I do use W3schools. It's a free website with examples and lessons you can follow. I use it as a reference and look topics up as I need them. www.w3schools.com/sql/
Hello Dimitri, I just noticed you and i think your videos very helpful but could you suggest cheaper ways to get information about these books, because its really expensive where i live thank you.
Unfortunately, to get enough depth in learning you really need to use books. That being said, I would only recommend buying one book and then spending a lot of time working through it. Buying older versions is also a cost saving method. If you wanted to enhance your technical skills I would recommend either one of the books below. Both books have a lot of information and are fairly cheap for a textbook. They are older versions but the material is still good for learning. S-Plus is the old version of R. (the links below are affiliate links) Statistical Analysis of Financial Data in S-Plus amzn.to/2Ed9CoY Introductory Econometrics: A Modern Approach amzn.to/2FVcgNa
hi dimitri, to work in a mutual fund as an analyst to choose investments or to be able to do proprietary trading in some company, do you think it is better a master's degree in finance or a master's degree in quantitative finance?
This will depend on your background. If you have a business/finance background and want to work in traditional finance then an MBA or Masters in Finance will better suit you. If you have a math or stats background and want to work in quantitative finance then a Masters in Quant Finance or a PhD would better suit you.
I’ve a bachelor in economics and business administratin, I was admitted to both a msc in finance and a Msc in QF, and given my work goals (mutual funds as an analyst or prop trading) I wanted to ask you which choice between the two MSc is better
It depends on the programs and where they are placing students. In general I would consider mutual funds as traditional finance however prop trading is usually done by PhDs if you want to do research. If you just want to trade, Msc QF can be good. Again, all of my advice is US specific. If you are coming from a different country the industry standards can be different.
Something else to think about is do you want to do math and stats in SAS, R, and Python or would you rather analyze finance data (for example PE) for investments in Excel? The first option would be QF and the second would be Finance.
What do you mean by portfolio implementation? Any book under "Quant Technical" would be modeling. If you are interested in investing as a traditional finance professional then I would use "Security Analysis" and "Financial Modeling."
