Need some guidance on preparing for commodity derivatives interview

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7/24/18
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Hi Everyone,

Let me preface by saying this, I am a recent graduate with an arts degree so not a lot of technical skills I can boast of aside from introductory compsci courses using Python (sorting was probably most complicated topic for me), and a ML intro course based on supervised learning techniques working in R (not a fan of R btw, prefer Python, however, never used Python for data analytics).

That being said, I am keen to learn technical skills required for data analytics. While I struggled to grasp the statistical theory behind the models I learned in my ML course (ex, NN, Random Forest, GLM, among others), the application of these techniques on a real dataset (from Kaggle, cc fraud dataset) and the results made a lot of sense to me. For example, evaluation metrics such as specificity vs sensitivity, and the combination matrices allowed me to defend one model vs another.

So my actual question: I am interviewing for a position as a commodity derivatives trader. My interviewer helps his customers maintain their margins by hedging against fluctuations in price of food items. I really want to give this interview my best shot. How can I best prepare for this interview? Aside from behavioural and situational questions, there will be a technical component. How can I prepare for the latter? I am confident that I can defend my resume and cover letter (my ML course and project was not mentioned in either, so I assume they are not expecting me to be a wiz quant however, I would like to impress).

I appreciate any kind of input you may have for me.

Thanks
 
I am not a 'quant' by title but do have some equity derivative trading experience. I'd try and learn as much about futures pricing, especially when it comes to food commodities. If these are agricultural products find out how whether patterns effect harvest, or if live stock what things may effect their price. If you are not familiar with contango/backwardation read up on that. As for hedging, there are 'static deltas' and 'dynamic deltas' with the use of futures and options respectively. Also read up on the futures terms, like how is the final settlement price calculated, where and when are the deliveries of said futures.

I have a buddy who is a very successful energy derivatives trader. He rarely trades options, mostly just standard monthly futures. His degree is in finance, not sure if he ever took calc 2. Math probably won't be a deciding factor.
 
Nowadays, Machine Learning and AI techniques are being applied in a lot of fields. As for the job position you have mentioned, I think you would require a combination of technical as well as trading skills to not only ace the interview but also to be successful in your job. I come from a technical background and hence was looking for courses which would teach me to apply my skills to trading and found about courses on a platform called Quantra. Their courses have a perfect combination of technical and trading knowledge. I think you should check it out too, it can be helpful!
 
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