Tsundoku - Why I Collect Non Quant Books
Audio Brief
Show transcript
This episode covers the strategic choice between studying pure quantitative finance versus mastering broader mathematical and scientific disciplines. There are three key takeaways. First, prioritize core mathematics, statistics, and programming. Second, maintain a diverse multi-disciplinary library for creative problem-solving. Third, align your technical profile with the specific demands of either hardcore research or applied business roles.
Mastering foundational analytical tools provides far greater versatility than memorizing specific, pre-built financial models. Rather than reading textbooks cover-to-cover, build a broad reference library to consult when facing unique, real-world challenges.
Finally, recognize that hiring managers value either deep theoretical rigor or immediate applied skills depending on the specific team. Broadening your scientific foundation ultimately builds a more resilient and versatile quantitative career.
Episode Overview
- This episode addresses a common dilemma for aspiring quantitative finance professionals: whether to focus solely on quant finance literature or to diversify into broader scientific and mathematical fields.
- The host uses his own bookshelf to illustrate the vast ratio of foundational math, stats, and programming books compared to pure quantitative finance books.
- It highlights why over-specialization in specific financial models can limit a quant's problem-solving abilities compared to mastering foundational analytical tools.
- This is highly relevant for students, career switchers, and current quantitative analysts looking to broaden their skill sets and improve their career prospects.
Key Concepts
- Foundational Tools vs. Niche Applications: Pure quantitative finance books often focus on off-the-shelf models (like Black-Scholes). However, the true "tools of the trade" are mathematics, statistics, and programming, which provide the building blocks to solve any complex problem.
- The Concept of Tsundoku: Embracing the Japanese practice of acquiring books and letting them pile up without reading them fully is highly beneficial. A diverse home library acts as a reference tool where one can dip in for 5 to 60 minutes to spark creativity or solve specific workplace challenges.
- Hiring Dynamics in Quant Finance: The quant job market is split. Hardcore quants value deep mathematical and statistical rigor, even from non-finance backgrounds (like psychology or engineering). Conversely, business-oriented hiring managers prefer candidates with specific, applied finance experience to minimize training time.
Quotes
- At 1:10 - "I really embrace the term of tsundoku, which is a Japanese term for just collecting unread books. A lot of the books I have, I've opened, I've read parts of them, I dive into them when I have interesting problems at work." - Explaining how a personal library functions as a dynamic problem-solving resource rather than a list of books to read cover-to-cover.
- At 1:48 - "I think quantitative finance is too pigeonholed, and I think MFE programs... are far too pigeonholed often in just trying to solve a very specific problem with very specific known tools." - Critiquing the narrow academic focus on pre-existing financial models rather than broad analytical skill-building.
- At 2:19 - "You really need to learn the tools of the trade here, and the tools of the trade here are going to be math, stats, and programming... I find the finance part can typically be learned on the job." - Explaining why foundational skills should take priority over finance-specific theory when preparing for a career as a quant.
Takeaways
- Prioritize mastering foundational subjects like mathematics, statistics, and programming over memorizing specific, pre-built financial models.
- Build a diverse personal reference library across different disciplines (such as operations research or engineering) to consult when you need creative angles for problem-solving.
- Tailor your resume and study habits based on the type of role you want: focus on deep theoretical rigor for hardcore research roles, or emphasize direct, applied project experience if targeting business-aligned or risk-management teams.
