Which order to read these books?

[matthewzz]

I recently bought these books, and started reading one of the interview books, but I want to know which order would be recommended to read in. For context im graduating Dec 2023 and will be recruiting for 2024 (hopefully I can start before summer tho bc of graduation date (if i happen to land something haha)). I'm an undergraduate math and econ major, finished with my real analysis classes super eager to become a quant trader.

1. Option Volatility and Pricing: Advanced Trading Strategies and Techniques, 2nd Edition - Natenberg, Sheldon
2. Stoch Calc for Finance I and Stoch Calc for Finance II - Shreve, Steven
3. Dynamic Hedging: Managing Vanilla and Exotic Options - Taleb, Nassim
Interview prep books, still I digress
4. Frequently Asked Questions in Quantitative Finance - Wilmott, Paul
5. A Practical Guide To Quantitative Finance Interviews - Zhou, Xinfeng

Any order I should read them or doesnt really matter, also am I missing any important books? Thoughts on "Options, Futures, and Other Derivatives" by Hull?

 

[MikeLawrence]

What is your current level of statistical/probabilistic knowledge?

A:
-----Frequently asked questions
-----A practical Guide to Quant. Fin. Interviews
B:
-----Shreve I and II
-----Dynamic Hedging

I'm not really sure where to list Sheldon's book.

You are trying to land an entry level role, I recommend starting with group A. Knock out FAQ really quick, then slowly work through the Interview book as you start to go through Shreve I guess. Hulls book would be good to read, especially if you don't have any financial knowledge prior. Basic options pricing will probably come up in interviews. You can also check out Neftci's introductions to mathematical finance and financial engineering. Those are standards for beginners with multivariable calculus and some probability knowledge.

I wouldn't read Dynamic Hedging at this point, not sure if I would read Sheldon's right now either, but you can skim them if you want. There are currently better uses of your time, and the material in those books will almost certainly not come up in interviews: they will not help you get a job. Once you have a job and some idea of what you are doing, or if you will even be working in an area that will require the knowledge in those books, then you can think about going into them.

What is your C++/coding ability?

 

[Dimitri Vulis]

Your reading list is a little skewed toward graduate-level option pricing...

As an undergrad, you should read Steve Shreve vol 1 (Binomial model) first and make sure you are extremely comfortable with everything in it. It looks like a thin little book, but it's quite dense, and covers some complicated topics using simple models.

Then you can read as much of Steve Shreve vol 2 (Continuous-time models) as you can on your own, skipping the parts that you don't need. Keep in mind that his book is a little dated. E.g. he praises the CIR model for not admitting negative interest rates, but these days, we no longer think it's such a good feature. His book tries to be self-contained, e.g. by explaining tooks like probability theory as much as needed. But if you haven't taken a good probability theory course as an undergrad, then you should read a good book more thoroughly explaining probability theory from measure theory viewpoint. Etc

I am reluctant to recommend Hull's book. It was a great book in the 1990s when I first read it. Although it was supposedly updated (11th ed, 2021), they did not do a good job, and it's very outdated. It may be good to keep around for reference, but not to study from, sorry.

Natenberg is good... As an economics major, you may like Akihito Asano - An introduction to mathematics for economics.

Since you bring up interview prep books, you may also like:

Probability and Stochastic Calculus Quant Interview Questions by Ivan Matić, Radoš Radoičić, Dan Stefanica - and if you do find yourself wondering about some question, then definitely look for another book to understand it more deeply.

Cracking the Finance Quant Interview: 51 Interview Questions and Solutions by Jean Peyre

150 Most Frequently Asked Questions on Quant Interviews by Dan Stefanica, Radoš Radoičić, Tai-Ho Wang

Challenging Brainteasers for Interviews (#3) by Rados Radoicic, Ivan Matic, and Dan Stefanica

Quant Job Interview Questions And Answers by Mark Joshi, Nick Denson, Andrew Downes

Heard on the Street: Quantitative Questions from Wall Street Job Interviews by Timothy Falcon Crack

 

[marcusaurelius]

Your reading list is a little skewed toward graduate-level option pricing...

As an undergrad, you should read Steve Shreve vol 1 (Binomial model) first and make sure you are extremely comfortable with everything in it. It looks like a thin little book, but it's quite dense, and covers some complicated topics using simple models.

Then you can read as much of Steve Shreve vol 2 (Continuous-time models) as you can on your own, skipping the parts that you don't need. Keep in mind that his book is a little dated. E.g. he praises the CIR model for not admitting negative interest rates, but these days, we no longer think it's such a good feature. His book tries to be self-contained, e.g. by explaining tooks like probability theory as much as needed. But if you haven't taken a good probability theory course as an undergrad, then you should read a good book more thoroughly explaining probability theory from measure theory viewpoint. Etc

I am reluctant to recommend Hull's book. It was a great book in the 1990s when I first read it. Although it was supposedly updated (11th ed, 2021), they did not do a good job, and it's very outdated. It may be good to keep around for reference, but not to study from, sorry.

Natenberg is good... As an economics major, you may like Akihito Asano - An introduction to mathematics for economics.

Since you bring up interview prep books, you may also like:

Probability and Stochastic Calculus Quant Interview Questions by Ivan Matić, Radoš Radoičić, Dan Stefanica - and if you do find yourself wondering about some question, then definitely look for another book to understand it more deeply.

Cracking the Finance Quant Interview: 51 Interview Questions and Solutions by Jean Peyre

150 Most Frequently Asked Questions on Quant Interviews by Dan Stefanica, Radoš Radoičić, Tai-Ho Wang

Challenging Brainteasers for Interviews (#3) by Rados Radoicic, Ivan Matic, and Dan Stefanica

Quant Job Interview Questions And Answers by Mark Joshi, Nick Denson, Andrew Downes

Heard on the Street: Quantitative Questions from Wall Street Job Interviews by Timothy Falcon Crack

Interesting information. Thank you! @Dimitri Vulis

 

[Paul Lopez]

Lovely thread!

 

[matthewzz]

What is your current level of statistical/probabilistic knowledge?

A:
-----Frequently asked questions
-----A practical Guide to Quant. Fin. Interviews
B:
-----Shreve I and II
-----Dynamic Hedging

I'm not really sure where to list Sheldon's book.

You are trying to land an entry level role, I recommend starting with group A. Knock out FAQ really quick, then slowly work through the Interview book as you start to go through Shreve I guess. Hulls book would be good to read, especially if you don't have any financial knowledge prior. Basic options pricing will probably come up in interviews. You can also check out Neftci's introductions to mathematical finance and financial engineering. Those are standards for beginners with multivariable calculus and some probability knowledge.

I wouldn't read Dynamic Hedging at this point, not sure if I would read Sheldon's right now either, but you can skim them if you want. There are currently better uses of your time, and the material in those books will almost certainly not come up in interviews: they will not help you get a job. Once you have a job and some idea of what you are doing, or if you will even be working in an area that will require the knowledge in those books, then you can think about going into them.

What is your C++/coding ability?

I've taken the university upper-division undergrad probability classes, real analysis classes and a stochastic processes class, but not any graduate measure theory classes. In the fall I'm hoping to audit my uni's (ucla) MFE Stochastic calc course since it's in the business school and doesn't require measure theory knowledge.

In terms of coding,
I have been coding in C++/Python for over a year now, and have taken all of my university courses on both of them. Im not super good at the Leetcode/HackerRank problems within a timed environment, but im practicing them in my spare time.

Any changes to your recommendations/anything else else you'd recommend?

 

[matthewzz]

Your reading list is a little skewed toward graduate-level option pricing...

As an undergrad, you should read Steve Shreve vol 1 (Binomial model) first and make sure you are extremely comfortable with everything in it. It looks like a thin little book, but it's quite dense, and covers some complicated topics using simple models.

Then you can read as much of Steve Shreve vol 2 (Continuous-time models) as you can on your own, skipping the parts that you don't need. Keep in mind that his book is a little dated. E.g. he praises the CIR model for not admitting negative interest rates, but these days, we no longer think it's such a good feature. His book tries to be self-contained, e.g. by explaining tooks like probability theory as much as needed. But if you haven't taken a good probability theory course as an undergrad, then you should read a good book more thoroughly explaining probability theory from measure theory viewpoint. Etc

I am reluctant to recommend Hull's book. It was a great book in the 1990s when I first read it. Although it was supposedly updated (11th ed, 2021), they did not do a good job, and it's very outdated. It may be good to keep around for reference, but not to study from, sorry.

Natenberg is good... As an economics major, you may like Akihito Asano - An introduction to mathematics for economics.

Thank you for the response! I'm hoping to work on an options or commodities desk which is why it might be skewed.
I will look into the Asano book.
As for

you should read a good book more thoroughly explaining probability theory from measure theory viewpoint. Etc

what would you recommend? I've taken real analysis I and II, but unfortunately don't plan on taking measure theory before I graduate.

 

[MikeLawrence]

Any changes to your recommendations/anything else else you'd recommend?

Well, I'm not really sure what to recommend you at this point. You have all the pre-req knowledge I can think of (I'm a bit behind you but you've done everything I have planned for) so I'm of limited use from now on. I guess just grind the leetcode/hackerrank to make sure you perform well in a timed interview environment.

Auditing the MFE's stochastic calc course is a wonderful idea, especially if you already know the prof well. Your knowledge base is actually strong enough you might be able to start on Taleb's book and actually get something out of it, but you'd know that better than I would. I'd still hold off on that until you lock down leetcode/interview prep though.

 

[Dimitri Vulis]

If you like commodity vol, then after you're done with Shreve vol 2, you should take a look at Commodity Option Pricing: A Practitioner's Guide by Iain Clark, Commodity Derivatives: Markets and Applications by Neil Schofield, and Commodities and Commodity Derivatives: Modelling and Pricing for Agriculturals, Metals and Energy by Helyette Geman. Helyette Geman was the PhD advisor of Nissim Taleb, whose book you mention. She published a few other books on risk management of commodities, commodity finance, etc, but this is a good start.

 

[Dimitri Vulis]

what would you recommend? I've taken real analysis I and II, but unfortunately don't plan on taking measure theory before I graduate.

there are many good books. Take a look at Measure, Probability, and Mathematical Finance: A Problem-Oriented Approach by Gan, Ma, Xie, for example.

 

[matthewzz]

there are many good books. Take a look at Measure, Probability, and Mathematical Finance: A Problem-Oriented Approach by Gan, Ma, Xie, for example.

Thanks!

 

[Dimitri Vulis]

Thanks!

The discussion here Suggestion for a probability theory book mentions other MT books you may want to browse.

 

[Daniel Duffy]

My books

 

[Paul Lopez]

View attachment 50726

Now that's a handsome stack of books.

 

[achirikhin]

I would agree regarding Shreve and then I would suggest Wilmott for the breadth of knowledge on derivatives. Piterbarg Vol 1 on methods.

For the quant and qd jobs, any good book on Algorithmics.

On the realities of the quant jobs, Quantitative Analyst, Developer, Strat: The Profession