Ashraf, a Maths graduate on his way to set up an HFT desk

3 min read

1980s: Anyone can invest. 
1990s: Anyone can trade. 
2010s: Anyone can algo trade. 

All you need is a good education, hard work, determination, and perseverance. 

“The best investment you can make is an investment in yourself. The more you learn, the more you’ll earn” - Warren Buffett

Get inspired by this story of Ashraf who started setting up his own High-Frequency Trading firm while in the first year of his Masters in Statistics from Bern University in Switzerland. In his own words, he shares his journey and aspirations in this domain. 

Hi Ashraf, tell us about yourself.

Hi everyone, I am Ashraf Mohamed, a full-time trader and strategies researcher from Switzerland. I have been in the finance industry for the past 4 years now. I completed my bachelors' economics and time series econometric then changed gears to the more quantitative type of study mainly in math and stat by enrolling in MSc statistics at Bern University, Switzerland.

What is your big plan in this industry?

I am currently involved in the process of setting up a High-Frequency Trading desk within a more general systematic type of trading fund using Algo and quantitative techniques especially in Asian markets and European ones leveraging techniques from M.L., time series, applied statistics just to name a few.

What made you choose the Quantitative trading domain?

I chose to work in the Quantitative Trading domain for many reasons, most important of which as my current manager approached me and we start discussing in more structured way the merits of such an idea of setting up such HFT desk and more in general systematic trading prop firm with very short to short-term holding periods from a purely entrepreneurial perspective.

Secondly I was just in my second semester in the MSc program and after reading quite a while as well as asking some finance professionals with some experience in the field, I have seen that given the right choice of resources and with enough discipline and determination, it is still profitable Endeavour to follow given that markets are still expanding, many more sophisticated investors putting some of their capital in emerging financial markets coupled with advancements seen in technology and science, I gave my okay back to my manager to start planning.  

How did you hear about Quantra?

My project manager had recommended Quantra courses while I was pursuing the Masters. I have enrolled in multiple quantitative trading courses including Mean Reversion Strategies and Neural Networks in Trading by Dr. Ernest Chan.

How did the Quantra courses help you?

These courses are really interesting and what a found especially interesting is the range of applications tackled by methods addressed, which come mainly from A.I. and machine learning as well as time series analysis models especially in the area of volatility modelling and forecasting sometimes down to intraday frequencies, so it really helps to see how such methods being applied as it provides a very systematic way of thinking of the whole process of creating and developing strategies with quantitative bent to it in great care, with helpful and open approach of Dr.Ernest Chan and the other faculty members, you are being seriously well-taken care of with reference to the materials covered.  

Be it making the shift from manual to automated trading, or starting your own High-Frequency Desk, with QuantInsti courses the goal will not be far. Quantra courses are self-paced bite-sized courses, a quick way to gain the skills you’ll need to create your own trading strategies using Python or excel. So you gain usable skills in a matter of hours.

Looking for classroom coaching and one-on-one interaction with faculty members? Enquire more here

Disclaimer: In order to assist individuals who are considering pursuing a career in algorithmic and quantitative trading, this case study has been collated based on the personal experiences of learners from QuantInsti®. Case studies are for illustrative purposes only and are not meant to be used for investment purposes. The results achieved post completion of any QuantInsti programme may not be uniform for all individuals.