By QuantInsti
Introduction: A Personalized Path
Peter Engel is a seasoned quantitative finance professional with a strong foundation in math and statistics. He began his career in credit risk, specializing in mortgage-backed securities, and spent years working in both large institutions and smaller hedge funds. However, despite his extensive experience, Peter had a vision to go beyond traditional financial roles: he wanted to build and manage his own algorithmic trading systems.
"Everyone’s trading journey is different. For me, finding the right guidance at the right time made all the difference," says Peter, reflecting on the milestones of his career.
Through a combination of independent exploration, structured mentorship, and practical training, Peter crafted a learning path that aligned with his goals. His experience underscores the importance of addressing individual learning needs—a principle that shaped his success.
Recognizing the Challenges of Transition
Peter’s journey to algorithmic trading began with a realization: his manual approach to trading was not scalable.
"I used to rely on identifying complex patterns on charts, making manual decisions for entry, exit, and position sizing. It worked to an extent, but I knew it wasn’t sustainable," he explains.
Despite a strong academic foundation in statistics and years of experience in portfolio optimization, Peter identified gaps in his knowledge—particularly in trade execution, options trading, and algorithmic system design. He needed a way to address these specific challenges while balancing his learning style and professional goals.
"It was important for me to find a program that didn’t just provide information but allowed me to apply what I learned to my own style of trading."
Creating a Learning Journey: Starting with Quantra
Peter began his journey with Quantra’s self-paced courses, which provided an accessible entry point into algorithmic trading. These courses allowed him to explore critical concepts like portfolio optimization, position sizing, and alpha mining at his own pace.
"Quantra gave me the flexibility to build a strong foundation. Courses like portfolio optimization and mean-reversion strategies helped me understand the basics and gave me the confidence to tackle more advanced topics."
Peter found Quantra’s approach particularly helpful in translating theoretical concepts into actionable insights, a skill that proved invaluable as he progressed.
Structured Growth: Mentorship Through EPAT
Building on his initial exploration, Peter enrolled in the Executive Programme in Algorithmic Trading (EPAT) to gain advanced skills and mentorship. This decision marked a turning point in his journey, providing structured guidance tailored to his unique needs.
"The mentorship program was a game-changer. It wasn’t just about learning concepts; it was about applying them to my own challenges with the help of experienced practitioners."
Key areas of growth during EPAT included:
- Options Trading:
"Before EPAT, my understanding of options was mostly theoretical. The program helped me apply strategies like straddles and spreads, teaching me when and how to use them effectively." - Trade Execution and Transaction Costs:
"Learning to build transaction cost models and minimize market impact was a completely new and invaluable skill for me." - Data Architecture and AWS Management:
"The lessons on system design and infrastructure taught me how to build a scalable, reusable framework for my trading systems."
Peter also highlighted the importance of collaboration within EPAT’s global community.
"Trading can be isolating, but connecting with peers and mentors showed me that others faced similar challenges. The sense of shared learning made a huge difference."
A Unique Approach for Every Trader
Peter’s experience emphasizes that there is no one-size-fits-all path in algorithmic trading. His journey combined self-paced learning, structured mentorship, and practical application—all tailored to his specific goals.
"What worked for me might not work for someone else. The key is finding a program that respects your unique challenges and helps you address them in a way that makes sense for you."
Through personalised guidance, EPAT helped Peter transition from manual trading to building and scaling his own automated systems.
Lessons from Peter’s Journey
Peter’s story demonstrates the value of mentorship, flexibility, and a supportive community in achieving trading goals. His advice to other traders is simple:
"Take the time to understand your own challenges and find a program that aligns with your needs. The right mentorship and resources can make a world of difference."
Next Steps: Start Your Own Algorithmic Trading Journey
Peter’s journey highlights how personalised guidance and practical learning can transform trading aspirations into reality.
Do you aspire to learn Algorithmic Trading? Do you want to start trading on your own? Do you wish to enhance your existing skill set? Then you have the opportunity to learn various aspects of Algorithmic trading with the Executive Programme in Algorithmic Trading (EPAT)!
If you’re just starting out, explore Quantra’s self-paced courses to gain foundational skills at your own pace.
Your trading journey is your own—take the first step today!
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 a student or alumni from QuantInsti’s EPAT® programme. Case studies are for illustrative purposes only and are not meant to be used for investment purposes. The results achieved post-completion of the EPAT® programme may not be uniform for all individuals.
