This thread is for newbies to the derivatives/option market who are wondering how to evolve in this field, and sometimes feel that they lack the quant background...

I have a confession to make – I’m a self-taught quant. unfortunately I found my passion for quant finance during
the 2nd year of my B.A in Eco, after I got hired by a Fintech company that specialized in option pricing modules

As I got drawn into this amazing world of derivatives, I soon realized that I lack the ability to understand technical/modeling papers…
At that point I had two options – 1. Drop out of Eco, wait a year and start CS/math, 2. Give up on my desire to advance in the world of derivatives modeling

Well, I chose option #3 – I decided to teach myself math/stats to a level where I can read,
understand, and implement quantitative models.

So I started… I took the curriculum of BS in math and learned each and every course in that curriculum (while completing my Eco BA, working, and taking care of a newborn baby). It was the most difficult I’ve ever done,
but it was so worth it…

Every course that I took was out of passion, I learned to code in three different languages, I developed a huge set of skills that students in the academia usually don’t appreciate.
I like to think that I’m a practical quant. As a practical quant you try to keep your knowledge base and focus very narrow (in the local environment/short time frame), as widening the scope of learning will get you lost in a sea of information and theories
The best way to go about this type of learning is to map a subject/paper/model and build a curriculum accordingly, so after you learn you know both the subject and relative theories.

This is what keeps my passion to derivatives burning… I’m in a constant learning mode,
and every time I come across a puzzle I need to solve, I end up learning something new…

I guess hard work and persistence can make up for lack of academic background...

Feel free to share your thoughts and spread the word to these who are seeking some guidance...
You can follow @VolQuant.
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