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Wish list for QuantNet 2023 and beyond

Just a general remark; have a directory structure.

Now we get all posts at top level; not everyone in interested in everthing but we see everything. (for me, GRE stuff is not for me).
We do have a directory, forum index right below the list of latest posts. The latest posts is just a list showing 20 or so latest posts. You can get the same thing by clicking on the What's New link on the top menu.
I'm not 100% convinced of keeping or removing the latest posts on the forum index. One hand, it's easy to have a quick snapshot of everything without clicking another extra link. On another, it may show posts from forums that one may not be interested in.
Maybe we can try to remove it for a week and see how it works.
 
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When I started QuantNet in 2006, I never envisioned that QuantNet will grow into a global hub for students inspired for a career in quantitive finance. I heard it from many program's directors and administrators that as many as 90% of their incoming students did their program research on QuantNet. Some commented that we are a "admissions decisions powerhouse".
However satisfying to hear, it's a collaborative efforts by every single member of this community who signed up, asked and answered questions on our forum, shared their admission timelines on the Tracker, wrote a program review, and partook our online courses.
We have many activities for the first time this year, such as Q/A with programs (UCLA MFE, NYU Courant, NYU Tandon, UCB MFE), AMA (Ask Me Anything) with many practitioners (quant C++ dev, derivatives pricing quant, buy-side quant researcher). More to come from this front.
We have a wave of new active members who can energize and make QuantNet better. I already got plenty of idea and feedback from @MikeLawrence and @marcusaurelius. We hope together we can make QuantNet an even better resource for inspiring quants.

Here is us reaching out to all members for suggestions of what you like to see on QuantNet for the future. What we can provide that makes your decision on programs, careers better.

Let's hear it.
A third C++ course. Maybe something that involves building some trading algos that we can show off as projects during interviews (whether for job or MFE interviews)
 
Maybe a course on Linux essentials with applications to finance? Also, kdb, as was mentioned in some QuantNet post a while ago.
great idea. How to develop in a linux/unix env using g++ and clang compilers.
kdb might be the most useful idea. I'm not entirely sure what the second one is, haven't seen it anywhere, purely off of exposure I have seen a couple firms state in internship things that kdb was required (or practically required) (I think it was 2sig and someone else). Also, CMU has a course on it. I know from the last time kdb was brought up on QN that Palley knows it, not sure if he is up for a third (fourth? I think he does python too) full time course commitment. You could always ask a QN member who went through CMU how they did it, and if he/she knows anyone who might want to spearhead it.

But that might just mean that I'm on the surface level for coding and haven't been exposed to the deeper stuff.
 
kdb might be the most useful idea. I'm not entirely sure what the second one is, haven't seen it anywhere, purely off of exposure I have seen a couple firms state in internship things that kdb was required (or practically required) (I think it was 2sig and someone else).
I've only seen it on Morgan Stanley job postings. Don't ever recall seeing it on the buy-side...at least not where I work.
Also, CMU has a course on it. I know from the last time kdb was brought up on QN that Palley knows it, not sure if he is up for a third (fourth? I think he does python too) full time course commitment. You could always ask a QN member who went through CMU how they did it, and if he/she knows anyone who might want to spearhead it.
Saw that too. I think CMU might be the only program that teaches it, but probably not in much depth. I'm assuming Avi learned it through work?
But that might just mean that I'm on the surface level for coding and haven't been exposed to the deeper stuff.
You're not alone here.
 
I've only seen it on Morgan Stanley job postings. Don't ever recall seeing it on the buy-side...at least not where I work.

Saw that too. I think CMU might be the only program that teaches it, but probably not in much depth. I'm assuming Avi learned it through work?

You're not alone here.
I learned q/kdb through work. Same for sql. But I'm old. I hope schools teach at least the basics now. :D
 
A third C++ course. Maybe something that involves building some trading algos that we can show off as projects during interviews (whether for job or MFE interviews)
Actually, we have been approached about this precise question a few times the last while. And I am coaching a student (who did QN C++ and Adv C++) to set up a prototype.
A lot of techniques are needed. And multiple participants. Kdb could be in there somewhere, as well as Python scripting.

In general, the requirements are well-known. But the devil in the (interesting) details.

@APalley
@Paul Lopez
@Andy Nguyen
@MikeLawrence
 
We have kind of resolved most interop use cases ->



The Interoperable World of the Big Three

C++, Python, C#



2023-2-5

Daniel J. Duffy



With my co-author Harold Kasperink we will have chapters on



Call C++ from Python and vice versa

Call C# from Python and vice versa

Call C# from native C++ and vice versa

(WRITE ONCE USE MANY TIMES. Look after the pennies and the pounds will look after themselves.)



Modern Multiparadigm Software Architectures and Design Patterns

with Examples and Applications in C++, C# and Python Volume I

Datasim Press 2023



Daniel J. Duffy and Harold Kasperink
 
Actually, we have been approached about this precise question a few times the last while. And I am coaching a student (who did QN C++ and Adv C++) to set up a prototype.
A lot of techniques are needed. And multiple participants. Kdb could be in there somewhere, as well as Python scripting.

In general, the requirements are well-known. But the devil in the (interesting) details.

@APalley
@Paul Lopez
@Andy Nguyen
@MikeLawrence
I would love to take this course. I have literally scoured the internet as well as countless continuing education courses at universities and can’t find anything. This would be the most valuable class I can think of.

QN is obviously filled with a lot of folks who aspire to be quants. However, I also think there are a lot of folks like me. I don’t aspire to be a quant. Instead, I set out to be a quant/algo developer. And, I think QN can round out it’s portfolio by offering courses for both considering how closely related the two roles are.

I did the first C++ course about two years ago and this helped me get an algo developer role. I then disappeared from QN for a while because there wasn’t any offering that could immediately help me succeed in my new role (and I was a bit overwhelmed with all I needed to learn). Now that I have my feet under me, I am back on QN and preparing for the advanced course.

However, it would have been great to have this third course there to support and educate me along the way.
 
" I have literally scoured the internet as well as countless continuing education courses at universities and can’t find anything."
Most institutions probably don't have the stamina, knowledge or mindset to get it up and running. Based on my experience of such orgs in the last 40 years. And it is too late for them to begin now.

Universities are not geared up to this kind of work.

And that's my honest (and accurate) opinion.
 
Question to all the MFE applicants.
When you research MFE programs through QuantNet, what are the crucial data that you need to help you decide which program to apply and to join?
Obviously, these are data you can't find it elsewhere.

Admission: acceptance rate?
Employment: average salary, % employment, location?
Student reviews?

I'm trying to see what kind of data you value the most and how we can go about providing them.
 
Question to all the MFE applicants.
When you research MFE programs through QuantNet, what are the crucial data that you need to help you decide which program to apply and to join?
Obviously, these are data you can't find it elsewhere.

Admission: acceptance rate?
Employment: average salary, % employment, location?
Student reviews?

I'm trying to see what kind of data you value the most and how we can go about providing them.
Average salary, tuition, and student reviews are some of the most important data for me. This is an investment, and we are all trying to maximize the expected outcome for it. Student reviews are important as they can give a decent feel for the program that isn't reflected in numbers.

Acceptance rate and other stats to show the selectivity of programs have never been particularly appealing to me when choosing programs, though it can be a source of pride once in them. I care more about the quality of the program than how many qualified applicants it manages to turn away.
 
Average salary, tuition, and student reviews are some of the most important data for me. This is an investment, and we are all trying to maximize the expected outcome for it. Student reviews are important as they can give a decent feel for the program that isn't reflected in numbers.

Acceptance rate and other stats to show the selectivity of programs have never been particularly appealing to me when choosing programs, though it can be a source of pride once in them. I care more about the quality of the program than how many qualified applicants it manages to turn away.
Most of the data can be found in the QuantNet MFE rankings but the reviews are much harder to obtain. We may have to form Seal teams to hunt down reviews. It's always "what is in it for me" mentality that we have to overcome :)
 
Average salary, tuition, and student reviews are some of the most important data for me. This is an investment, and we are all trying to maximize the expected outcome for it. Student reviews are important as they can give a decent feel for the program that isn't reflected in numbers.
On a second read, I agree with this. I think most people will approach this as a 100K investment and they want to have a >50% probability to regain that investment right after school. Unfortunately, some programs make it very difficult to make a good decision.
Many students went back to China because they couldn't find a job in the US. There are many micro and macro reasons for this but without a full picture, it's a pretty dicey decision.
 
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