Which Quant project should I undertake to maximize learning and increase exposure to employers
Hi All,
I am trying to make a transition towards to a quant role and need to complete a project as part of this transition.
I have shortlisted these 4 projects to get me better insight into the quant world. I can only choose one.
- Using Fourier Transform to solve PDEs generated for option pricing.
- (Its an interesting one as it allows me to compare methods between fast Fourier Transform, Fourier space time-stepping and Fourier-cosine series, a bit similar to the kind of model comparison work quant industry practitioners do)
- Stock diffusion method using Kou jump-diffusion model
- (Personally not very interested in this topic as most of work will be around pricing exotic options and I am not sure how much they are applicable in Financial Industry based in London)
- Stock diffusion method using constant elasticity of variance model
- (Again not sure about how applicable in this current industry)
- Using alternating direction implicit (ADI) to solve PDEs generated for option pricing
- (Again sounds like a interesting topic but a bit concerned on the complexity of this topic / code implementation side . Also not sure about how much ADI method is currently used within the industry nowadays.)
I am aware that depending on the accuracy and time requirements , methods change from banks to option trading desks, but I wanted to gain some insight into which project will provide the closest experience to a real life quant role. Any suggestions will be greatly appreciated. Thanks
Based on the most helpful WSO content, here are some insights to help you choose the best quant project to maximize learning and increase exposure to employers:
Using Fourier Transform to solve PDEs generated for option pricing:
Stock diffusion method using Kou jump-diffusion model:
Stock diffusion method using constant elasticity of variance model:
Using alternating direction implicit (ADI) to solve PDEs generated for option pricing:
Recommendation:
Using Fourier Transform to solve PDEs generated for option pricing seems to be the most beneficial project for the following reasons: - It provides practical experience with techniques used in the quant industry. - It involves model comparison, which is a valuable skill for quant roles. - It is highly relevant to real-life quant work, especially in option pricing.
This project will likely give you the closest experience to a real-life quant role and make you more attractive to potential employers.
Sources: So you want to be a Quant?, Q&A: Quantitative Analyst - Machine Learning, Analytics, & Quantitative Research/Investing, Best internships for Quant Trading?, For Those Considering Banking - Some Broad Advice, Q&A: Non-Target +
what type of quant do you want to be? trader, research, developer, etc. What type of shop do you want to be at? Prop shop, bank, hedge fund, AM? There is no objectively better way to spend your time unless you know what you are aiming for
Edit: If you're aiming to be a trader, having these projects is obviously really beneficial, but at the end of the day shops are looking for people with experience in making fast paced and important decisions under pressure. There's a ton of math/stats/cs nerds who are 110% smart enough to be a trader, but they lack an intuition for it.
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