Raymonk Surya O
Systems & Stochastic Modeling
Exploring systematic trading at the intersection of markets and mathematics.
I'm drawn to trading algorithms, market microstructure, applied mathematics, and puzzle-like problems where data, code, and risk all intersect.
- Cumulative GPA
- 4.11 / 4.3
- Favorite Sport
- Tennis
- Codeforces Rating
- 1447
Quantitative modeling playground
Exploring systematic strategies
It is fascinating how behavior, events, and positioning can be translated into alphas. With data and algorithms, those signals can be tested as simple rules to see how they shape an equity curve.
Play around: Adjust the parameters, or generate a new market to test the same rules on a different path.
*The market is randomly generated for illustration purposes only.
- CAGR--
- Sharpe--
- Sortino--
- Max Drawdown--
Synthetic regime-switching GBM dataset (seeded), covering ~3 years of daily observations. Trades are executed with a one-day lag and assume zero transaction costs. In mean-reversion mode, the bands directly indicate the z-score entry thresholds. It's a controlled simulation, fun for testing ideas without the messiness of real world data
Featured builds
Selected projects & case studies
Quant research, data engineering, and visual storytelling for decision-grade insights.
Experience
Quant roles that shaped my perspective
From data engineering to systematic research and market access infrastructure, I've worked across the stack where code, markets, and production systems meet.
Professional milestones
Certifications & credentials
Validated expertise across cloud engineering and capital markets.
Life beyond the terminal
Hobbies & pursuits
Where I reset, compete, and sharpen complementary skills.
Profile
Math enthusiast exploring trading systems
I studied computer engineering with a focus on quantitative finance. I'm motivated by both the search for alpha and the challenge of building the systems that support it, whether that's designing pairs trading strategies, refining trading signals, or developing market data infrastructure for analysis.
- Languages: Python, C++, Bash, Kdb+/q, Go, Java, SQL, VBA
- Frameworks: PyTorch, Tensorflow, pandas, NumPy, Django, Flask, FastAPI
- Databases: PostgreSQL, MongoDB, BigQuery, QuestDB, kdb+, DB2
- DevOps & Messaging: Docker, k8s, Jenkins, Terraform, Prometheus, Ansible, ELK Stack, Kafka, AMPS, QpidD, MAMAGW
Low-latency engineering
I focus on systems programming and performance for real-time workloads, from multithreaded data fetchers with throttling to optimized database access and log pipelines on Linux.
Market access & tooling
Exposure to market access flows, pre-trade checks, and production monitoring, using ELK, Prometheus, and internal scripts to keep activity observable and supportable.
Quantitative modelling toolbox
Exploring time-series models, factor and cross-sectional signals, Markov and regime-switching ideas, and risk measures like drawdown and Sharpe in small strategy experiments.
Let's connect!
Say hello, I'd love to hear from you
Whether you're exploring a new idea or just want to chat, feel free to reach out anytime.
