Questions for quants

This is my plan for after I finish the prequisitive maths for quantitative finance. The book choices are from another forum.
I have several questions about them.

Notes by david lando and rolf poulsen - alternative to Shreve1 (better imo)
2 - bjorks book on arbitrage theory - alternative to Shreve2 (more to the point imo)
3 - C++ by Bjarne Stoustrup, or joshis book
4 - Econometrics, Fumio Hayashi
5 - Glassermans book on MC
6 - A good book on PDEs for finance, Wilmotts might be a try but I don't know that book
(Option pricing: Mathematical models and computation)

(I am planning to learn stochastic processes from a book called mathematical modelling and computation in finance.)
1.Do Tomas bjorks and shreve’s books include enough measure theory?

2.Is Tomas Bjork a good alternative to shreve?
I saw that Tomas bjork doesn’t have anything on jump processes.

3.Are David landos notes a possible alternative for Shreve 1 and if so are they better or worse?

4.is the econometrics books attached any good?
 
A few cents...

3) - I'm probably biased since I followed several courses by RP and loved every one of them. I thought the notes gave a very nice intro to discrete time finance and provided a relative smooth transition to e.g. Björk, which is also a very well written book.

4) - Yes, Hayashi is definitely considered a good graduate econometrics book for time-series analysis. It provides a lot of theory with GMM as a unifying base, which one may like or dislike. Depending on the field of econometrics you're interested in, you may also consider other books. For primarily cross-sectional and panel type data, books such as "Papa" Wooldridge (2010) and Cameron-Trivedi (my favorite) are popular. For financial econometrics, Tsay or Taylor are fine intro books while Francq & Zakoian (2019) is more advanced and technical.
 
Hi Emetrics,
Thanks for answering so fast!
I have a few questions about what you wrote.
What would be the difference between a time series analysis focused econometrics book and a financial econometrics book, eg difference in focus?
Also, do you believe I should supplement jump processes from Shreve 2?
 

Daniel Duffy

C++ author, trainer
6)
2022 style state-of-art PDE/FDM (subumes all pde books in finance).


3) Joshi C++ is 1990s and (severely) outdated.

The best C++ training is Quantnet C++.
 
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Hi Emetrics,
Thanks for answering so fast!
I have a few questions about what you wrote.
What would be the difference between a time series analysis focused econometrics book and a financial econometrics book, eg difference in focus?
Also, do you believe I should supplement jump processes from Shreve 2?

Time series refers to the structure of the data, i.e. timely ordered variables, as opposed to cross-sectional or panel/longitudinal data. Financial refers to the topic/genre of econometrics that you're studying. Most often in financial econometrics you'll be working with financial time series, but the topic may just as well include cross-sectional data and analysis. Financial econometrics, at least when working with financial return series, is traditionally more skewed towards volatility inference rather than expected return inference, since it's a more feasible task.

Wrt. supplementing - Well, since Björk doesn't contain anything/much on jump processes and you seem keen on learning it, you don't really have a choice but to supplement. In general I like to consult several different books when learning a topic to get different views from different authors, but each to their own.

Wrt. remaining questions - I didn't (and I'm not going to) answer your remaining four original questions, since I'm no expert on neither C++ or numerical PDE computations. Daniel Duffys tips is most likely your best bet there.
 
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