From Wall Street to UCLA Career Coaching. AMA

Dear All,

I am proud to be a Career Coach for the Master of Financial Engineering program at the UCLA Anderson School of Management.

• I hold a B.A. in Mathematics and a B.A. in Economics.
• I have held various positions on Wall Street for a decade
• My areas of expertise include Credit Derivatives & other Exotic Products, High-Yield Research, and Risk Management. I have worked closely with the Sales & Trading Desk, Quant Research/Modeling Teams, and Investment Banking Division.
• Some of my favorite activities include chess, classical piano, reading, and helping others. That's why I'm here!

AMA, and if I can answer, I will!

 

[MikeLawrence]

@MikeLawrence Hi Mike, I was not aware of this. Are you sure you are not confusing following the company with being employed by the company? Would you mind providing the source of your information? I just checked LinkedIn and saw a different picture. I will stand corrected if I overlooked something, but I didn't see what you are claiming.

It was a bit of an exaggeration. And I'm only looking at somewhat quantitative roles. Y'all have pretty much all of them, the non-quant analytics but still analyst roles are what are sometimes by graduates of any other program.

Y'all only have about a 7 : 15 (+/-1-2) ratio over every other school to ever do something with them that is not back-office that is tracked on LinkedIn.
Don't search UCLA Anderson and then cross reference with current or past employers. You will get zero search results.
Search Universa Investments LP and then cross reference with UCLA or UCLA Anderson or whatever you want. I've got at least 15 of y'all showing up, 67 total profiles when you don't try and cut it down with a search parameter. And then only look at the non operations, or fund controller, or support type positions.

 

[Olga Inglis]

It was a bit of an exaggeration. And I'm only looking at somewhat quantitative roles. Y'all have pretty much all of them, the non-quant analytics but still analyst roles are what are sometimes by graduates of any other program.

Y'all only have about a 7 : 15 (+/-1-2) ratio over every other school to ever do something with them that is not back-office that is tracked on LinkedIn.
Don't search UCLA Anderson and then cross reference with current or past employers. You will get zero search results.
Search Universa Investments LP and then cross reference with UCLA or UCLA Anderson or whatever you want. I've got at least 15 of y'all showing up, 67 total profiles when you don't try and cut it down with a search parameter. And then only look at the non operations, or fund controller, or support type positions.

This is quite a sleuth, @MikeLawrence! Without any official knowledge or documents on this matter at my disposal, I will go into probabilities. Think about "The Birthday Paradox" -- if you meet someone randomly, the changes that you two are sharing birthday is 1/365.25. Now say there are 23 random people in the room, what are the odds that there are two (randomly taken) people with the same birthday.....? It is ~50%.

 

[joe_boy]

This is quite a sleuth, @MikeLawrence! Without any official knowledge or documents on this matter at my disposal, I will go into probabilities. Think about "The Birthday Paradox" -- if you meet someone randomly, the changes that you two are sharing birthday is 1/365.25. Now say there are 23 random people in the room, what are the odds that there are two (randomly taken) people with the same birthday.....? It is ~50%.

You must take your opponent into a deep dark forest where 2+2=5, and the path leading out is wide enough for one - Mikhail Tal

 

[MikeLawrence]

This is quite a sleuth, @MikeLawrence! Without any official knowledge or documents on this matter at my disposal, I will go into probabilities. Think about "The Birthday Paradox" -- if you meet someone randomly, the changes that you two are sharing birthday is 1/365.25. Now say there are 23 random people in the room, what are the odds that there are two (randomly taken) people with the same birthday.....? It is ~50%.

You must take your opponent into a deep dark forest where 2+2=5, and the path leading out is wide enough for one - Mikhail Tal

I'm taking this to mean there definitely is a pipeline (how it got started is anyone's best guess) and @Olga Inglis just can't say why.
If there are 23 people in a company, and 365 possible masters degr- err, birthdays- the odds that 15 of them share the same... birthday... is not high.

Someone tell me if I worked/typed that right. P(15 sharing same birthday) * # of ways to choose the 15, correct? I'm falling asleep, so might as well acknowledge it if I wake up and see that I messed up what should be simple combinatorics.

 

[Olga Inglis]

I'm taking this to mean there definitely is a pipeline (how it got started is anyone's best guess) and @Olga Inglis just can't say why.
If there are 23 people in a company, and 365 possible masters degr- err, birthdays- the odds that 15 of them share the same... birthday... is not high.

Someone tell me if I worked/typed that right. P(15 sharing same birthday) * # of ways to choose the 15, correct? I'm falling asleep, so might as well acknowledge it if I wake up and see that I messed up what should be simple combinatorics.

Dear @MikeLawrence and @joe_boy,

To continue our discussion, purely based on uncertainty and randomness (which I am sure you you had or will have an exposure to in quant finance):

I learned about "The Birthday Paradox" from Nassim Taleb's excellent book "Fooled by Randomness."

You are taking it wrong -- the lesson is that randomness looks like non non-randomness.
The human mind is built to identify for every event a definite cause and thus has a difficulty accepting accumulation of random/unrelated events.

As for Misha Tal, he will always be remembered for his brilliant and speculative attacks. Tal was also a fan of quiet moves. He thought that they make a stronger impression. I know a few legendary traders who share the same motto.

"I would rather guess about what follows from more-relevant assumption than derive precise conclusions
from less-relevant assumptions.”
- Emanuel Derman

Thank you for the interesting discussion!

 

[Olga Inglis]

Quantitive Finance, Trading, Chess and Legendary Boaz Weinstein

Emanuel Derman, a legendary figure in quantitative finance, asserted that a good quant must be a multifaceted individual: part trader, salesperson, programmer, and mathematician. Chess certainly helps hone these skills, as both require strong analytical thinking, strategic planning, and the ability to manage risk effectively.

Though a source of particular intelligence, human intuition is not well suited to situations involving uncertainty. One cannot be confident that the answer is correct without a thorough examination of the situation at hand.

And speaking of hands, Siegbert Tarrasch said “when you see a good move, sit on your hands and see if you can find a better one.” To tie it all together, all the roads lead to…Chess. Chess, trading, and quantitative finance require strong analytical thinking, strategic planning, and the ability to manage uncertainty effectively.

Boaz Weinstein, an iconic trader whom I'm proud to call both mentor and friend, learned to make decisions under uncertainty at a very young age. Boaz’s prodigious talent for numbers, games of strategy, including chess at the age of five, naturally led him to attend a math and science high school.

At the age of sixteen, Boaz had achieved the rank of Life Master by the United States Chess Federation. He went on to become the youngest Managing Director in Deutsche Bank's history at twenty-seven. Boaz's Saba Capital Management recently won both prestigious Activist Hedge Fund Manager and Credit Focused Manager of 2023 at the Hedge Fund Industry Awards.

Boaz possesses the same extraordinary talent that Emanuel Derman describes as crucial in quantitative finance: the real insight into the relationship between value and uncertainty. This ability, along with his quick pattern recognition and hyperrationality, translated seamlessly from the chessboard to the quantitative and complex world of fixed income in the beginning of Boaz’s career. He became one of the most successful derivatives traders in no time.

***
In his 1786 essay, “The Morals of Chess,” Benjamin Franklin said that chess honed one’s:

• Foresight – looking ahead at the long-term consequences of any action
• Circumspection – surveying the entire scene, observing hidden dynamics and unseen possibilities
• Caution – avoiding haste and unnecessary blunders
• Perseverance – refusing to give up in dim circumstances, continually pushing to improve one’s position.

Just something to think about when you play the beautiful game next time.

 

[rodeo]

Hi Olga, another question I had is that the MFE program at UCLA is 15 months (shorter than few of the rest that are 18/24 months) and also covers a wider range of topics in the 10 week semesters.
Isn't it offering a more broader curriculum rather than a deeper one like you mention is more suited for careers in quant. (A few reviews on QuantNet point to the same)

Would love you thoughts on this. Thanks.

@Olga Inglis

 

[Olga Inglis]

@Olga Inglis

Hi Rodeo,

Thank you for your patience.
I will address your question by the eod today.

 

[Olga Inglis]

Hi Rodeo,

Thank you for your patience.
I will address your question by the eod today.

@rodeo

As promised:

Most MFE (and MFE-like) programs, including UCLA’s, have approximately the same end-to-end schedule (15-16 months, 3 semesters or 4 quarters). The small differences amongst these are usually due to factors like academic calendars (quarters vs. semesters, start dates, …) and whether/how pre-program coursework (e.g., boot camps, which most programs offer) and internships are counted.

As you mentioned, a few programs are longer (18-24 months) and at least one is only 12 months long. At least in theory, a longer program can allow for more coursework and potentially more depth.

Looking beyond just total program duration, the number of courses and total instructional hours are also important as programs can differ widely in intensity or pace.

In addition, while many core building blocks are roughly similar across top programs, curricula can differ in their overall objectives: some specialize quickly to focus on computational methods, mathematical finance theory, financial programming, and/or financial data science, etc., while others emphasize breadth and a more diversified toolkit.

In this context, UCLA MFE seeks to provide its students a broad skillset applicable to a wide variety of quantitative finance careers. As the student reviews frequently note, it's an intensive program that consequently goes deeper than one might guess just by looking at its duration. But yes, our focus is on building a strong foundation to prepare our graduates for diverse roles and the ability to adapt to changing career demands.

 

[KingEze]

Hi KingEze,

Thank you for your question.

If it were me, I would not change roles. After all, you are going to be changing roles regardless – changing gears after getting an MFE, entrance to which will require mandatory math, computer science, coding, and other expertise. You've probably already taken linear algebra and multivariable calculus as an undergrad. To apply to the program (of course, each program has specific requirements), it's safe to assume that you would need skills in coding, numerical methods, advanced statistics and probability, machine learning, macroeconomics, etc.

Starting a new role wouldn't make it easier, as most new roles have a steep learning curve in the beginning. Don't try to climb two mountains at once.

I would stick with the role you are doingright now– the one you are comfortable with – while taking the required courses through Coursera (math, ML, econ), Quantnet (offers C++), and others.

In the meantime, I would also devote more time to getting to know professionals from the quant groups, and pay closer attention to their work functions (there are different types of quant roles). Ask questions. The best way to learn and experience somethingis to be a part of it.

I hope you find this useful. This is my opinion, of course, and one should listen to many others before making up their own mind and choosing the path they want to take.

And always remember that the details of a job are minimal compared to the importance of knowing who you are, what you want and can do.

Hope this helps.

Thank you! Frankly aligns with my thoughts also. Would be helpful with suggestions on the types of courses - like do I learn Python (as everyone says) or C++. What alternatives can I pursue besides online learning (as I haven't done so well using self-learning courses) any tips might help.

 

[Barcelona]

Hi Olga,

I would like to add a question on top of @rodeo

Some 3-star UCLA MFE reviews from 2020 put me off by complaining about lack of rigour, repetitiveness and overlapping content of some classes. This makes me question the academic depth of the program. Also, it looks like there were some positive changes since 2020. For example, Econometrics and Derivatives are taught by different professors and the program shifted more to Python.

I would appreciate your comments on this. Thank you!

 

[Olga Inglis]

Hi Olga,

I would like to add a question on top of @rodeo

Some 3-star UCLA MFE reviews from 2020 put me off by complaining about lack of rigour, repetitiveness and overlapping content of some classes. This makes me question the academic depth of the program. Also, it looks like there were some positive changes since 2020. For example, Econometrics and Derivatives are taught by different professors and the program shifted more to Python.

I would appreciate your comments on this. Thank you!

Hi @Barcelona

Thank you for your question!

At the time the reviews you mentioned were written, some of our senior faculty had just retired and the program’s executive director at the time was transitioning out. Perhaps more importantly, the pandemic had just triggered a sudden transition to online learning, and that may have impacted some students’ perceptions of the curriculum’s rigor as both students and faculty adjusted to an unfamiliar learning environment.

A lot has evolved since then and that should be apparent from the more recent reviews.

As you mentioned, Econometrics is now being taught by a new faculty member, who has brought a renewed passion to the course along with a better balance of rigor vs. applications. That’s followed by the Empirical Methods/Time Series taught by Prof. Lars Lochstoer, whose teaching style and rigor are mentioned in a number of the reviews.

The most rigorous sequence of courses is probably Stochastic Calculus (taught by Prof. Panageas), then Derivatives (now taught by the new faculty director, Prof. Reiner, who previously taught the subject at Berkeley for nearly a decade and was a managing director heading quant teams on Wall Street for two decades before that) along with Fixed Income (taught by Prof. Longstaff), then Computational Methods (taught by Prof. Goukasian). Most current students would probably say that Derivatives has become the most rigorous and challenging course in the curriculum. The other courses in this sequence are also mentioned in many of the reviews here on QuantNet.

At this point, most courses emphasize Python and a 20-hour Python programming course that takes students as far as some of the more important ML and numerical packages is now offered as part of the pre-program coursework in August. A few, typically time-series heavy, courses make use of r and an r boot camp is offered during the first quarter of the program. C++ is encouraged (but not required) in the more computation-heavy courses (Derivatives, Computational Methods).

Our faculty director continues to look for ways to strengthen, evolve, and enhance the curriculum.

I’m guessing that few (if any) current students would complain that the curriculum lacks rigor or is boring or repetitive. The more recent reviews would seem to support my opinion.

Hope this information helps!

 

[Barcelona]

Hi @Barcelona

Thank you for your question!

At the time the reviews you mentioned were written, some of our senior faculty had just retired and the program’s executive director at the time was transitioning out. Perhaps more importantly, the pandemic had just triggered a sudden transition to online learning, and that may have impacted some students’ perceptions of the curriculum’s rigor as both students and faculty adjusted to an unfamiliar learning environment.

A lot has evolved since then and that should be apparent from the more recent reviews.

As you mentioned, Econometrics is now being taught by a new faculty member, who has brought a renewed passion to the course along with a better balance of rigor vs. applications. That’s followed by the Empirical Methods/Time Series taught by Prof. Lars Lochstoer, whose teaching style and rigor are mentioned in a number of the reviews.

The most rigorous sequence of courses is probably Stochastic Calculus (taught by Prof. Panageas), then Derivatives (now taught by the new faculty director, Prof. Reiner, who previously taught the subject at Berkeley for nearly a decade and was a managing director heading quant teams on Wall Street for two decades before that) along with Fixed Income (taught by Prof. Longstaff), then Computational Methods (taught by Prof. Goukasian). Most current students would probably say that Derivatives has become the most rigorous and challenging course in the curriculum. The other courses in this sequence are also mentioned in many of the reviews here on QuantNet.

At this point, most courses emphasize Python and a 20-hour Python programming course that takes students as far as some of the more important ML and numerical packages is now offered as part of the pre-program coursework in August. A few, typically time-series heavy, courses make use of r and an r boot camp is offered during the first quarter of the program. C++ is encouraged (but not required) in the more computation-heavy courses (Derivatives, Computational Methods).

Our faculty director continues to look for ways to strengthen, evolve, and enhance the curriculum.

I’m guessing that few (if any) current students would complain that the curriculum lacks rigor or is boring or repetitive. The more recent reviews would seem to support my opinion.

Hope this information helps!

Hi Olga,

Thank you for your detailed response. I appreciate your candor and the inside information.

 

[Olga Inglis]

Hi Olga,

Thank you for your detailed response. I appreciate your candor and the inside information.

You are very welcome and there is no "inside information" -- it is public!

 

[Olga Inglis]

Thank you! Frankly aligns with my thoughts also. Would be helpful with suggestions on the types of courses - like do I learn Python (as everyone says) or C++. What alternatives can I pursue besides online learning (as I haven't done so well using self-learning courses) any tips might help.

Hi @KingEze,

Perhaps if you used a different platform for online learning, you might have a different experience?

C++ is offered right here on QuantNet. You can find it in the "Online Programming and Options Courses" section under Online Courses above.
For Python, I suggest Coursera (Coursera | Degrees, Certificates, & Free Online Courses).
And for the future, LeetCode (https://leetcode.com/) is a great resource for anyone who wants to improve their coding skills and prepare for technical interviews.

Books:
Python Crash Course by Eric Matthes
C++ Primer by Stanley Lippman, Josée Lajoie, Barbara Moo

Good Luck!

 

[Yonona]

Hi Olga, I am a beginner in the securities trading industry. I wonder to know if there are any forums where I can read research reports on algorithmic trading, high-frequency trading, and quantitative trading.

I would greatly appreciate it if you could share some websites or research reports.

 

[Tapasbrk]

Dear All,

I am proud to be a Career Coach for the Master of Financial Engineering program at the UCLA Anderson School of Management.

• I hold a B.A. in Mathematics and a B.A. in Economics.
• I have held various positions on Wall Street for a decade
• My areas of expertise include Credit Derivatives & other Exotic Products, High-Yield Research, and Risk Management. I have worked closely with the Sales & Trading Desk, Quant Research/Modeling Teams, and Investment Banking Division.
• Some of my favorite activities include chess, classical piano, reading, and helping others. That's why I'm here!

AMA, and if I can answer, I will!

View attachment 51734​

Hi @Olga Inglis , I appreciate that you are taking your time to help prospective quants over here. I needed your suggestions on a problem that I am facing. I will be completing my BS in Finance very soon. I have a good understanding of finance concepts. I have felt during my undergraduate course that I perform strongly in subjects which are quantitative in nature and have realised that I am always interested in understanding the quantitative side of finance concepts. Also, I find subjects like statistics and business analytics very interesting. I will be doing an MS in Quantitative Finance from not so well known college after my bachelor.

Looking at the requirements of the quant jobs and people's profiles who have applied to some prestigious colleges, I feel I am already behind in terms of quant and programming subjects as that has not been the prominent focus of my bachelor's. I want to know how I can work towards having a better position in terms of quant knowledge considering that I do not have a strong background for the same in my undergraduate.

Also, I would like to know your opinion about which certification would be better to pursue along with masters, CFA, or FRM. To me, FRM looks more attractive due to its more quantitative approach but still would like to know your opinion.

 

[Olga Inglis]

Hi Olga, I am a beginner in the securities trading industry. I wonder to know if there are any forums where I can read research reports on algorithmic trading, high-frequency trading, and quantitative trading.

I would greatly appreciate it if you could share some websites or research reports.

@Yonona

Dear Yonona,

Thank you for asking. Before I answer, I need to know the context of your situation. What is your current academic standing? Are you in a specific school year, majoring in a particular field, or have you taken any courses relevant to your goal? The more details you can provide, the better I can assist you.
Pursuing your goals is much like putting together a jigsaw puzzle. When you envision the final outcome, you still have to work piece by piece.

Kind Regards,
Olga

 

[Olga Inglis]

Hi @Olga Inglis , I appreciate that you are taking your time to help prospective quants over here. I needed your suggestions on a problem that I am facing. I will be completing my BS in Finance very soon. I have a good understanding of finance concepts. I have felt during my undergraduate course that I perform strongly in subjects which are quantitative in nature and have realised that I am always interested in understanding the quantitative side of finance concepts. Also, I find subjects like statistics and business analytics very interesting. I will be doing an MS in Quantitative Finance from not so well known college after my bachelor.

Looking at the requirements of the quant jobs and people's profiles who have applied to some prestigious colleges, I feel I am already behind in terms of quant and programming subjects as that has not been the prominent focus of my bachelor's. I want to know how I can work towards having a better position in terms of quant knowledge considering that I do not have a strong background for the same in my undergraduate.

Also, I would like to know your opinion about which certification would be better to pursue along with masters, CFA, or FRM. To me, FRM looks more attractive due to its more quantitative approach but still would like to know your opinion.

Dear @Tapasbrk ,

Thank you for your questions. I need a few clarifications:

Could you provide some specific examples of your understanding of financial concepts?
What quantitative subjects were you most interested in during your studies?
What does "quantitative understanding of financial concepts" mean to you?
What do you find interesting about statistics and business analytics?

Here's why these questions are important to me:
I want to see the foundation you have in order to know how best to build on it.
Your goals, plans, daily activities, and habits can't be evaluated in isolation from one another.

Best Regards,
Olga

 

[Olga Inglis]

As the moon passes between the Sun and the Earth there is a solar eclipse. If the eclipse is total, the Sun’s outer surroundings flash into the view and the appearance is magnificent.

There is also a book titled Eclipse of Reason by Max Horkheimer, where the author argues that a distorted view of reason has eclipsed modernity. This distorted view, rather than producing a bright future, highlights negative consequences.

And, yes, there is yet another kind of eclipse. Some people give up the moment an obstacle stands right in front of their goal. Though others tenaciously continue to pursue a goal after years of frustration and failure.

What is the main difference between these two groups of people?
Believe or not, it has nothing to do with being patient. It is actually their sense of control.

Those who feel that they are not responsible for choosing their goals and pursuing them, tend to believe that results are arbitrary. To them, it doesn’t matter how hard they try or how talented they are, as being successful is like winning the lottery; it is all the matter of luck.

Those who persevere, conversely, recognize that they are ultimately responsible, not just for pursuing their goals, but for setting them.
When you are in control, what you do matters. Each tiny step taken is something toward magnificent, just as the description of the total eclipse of the sun.