About Me

Portrait of Kunal Bhayana

I work across software development, algorithmic trading, and teaching because all three are closely connected. Building systems, understanding markets, and teaching fundamentals are different expressions of the same core interest: structured problem-solving and clear thinking.

Algorithmic Trading & Finance

I work at the intersection of programming and financial markets, building system-based trading approaches rather than discretionary methods. Trading ideas are translated into code with clear logic, measurable outcomes, and controlled risk.

Strategy Development

Translating trading ideas into executable code with clear entry, exit, and risk management logic.

Market Data Handling

Working with historical and live market data. Cleaning, structuring, and analyzing data for decision-making.

Backtesting & Evaluation

Testing strategies on historical data to measure performance and identify weaknesses before deployment.

Risk & Position Management

Implementing position sizing, drawdown control, and avoiding over-optimization to maintain system integrity.

Automation & Tooling

Building Python-based systems for automated analysis, execution monitoring, and continuous iteration.

Approach

Data-driven decisions, controlled risk, and continuous iteration. Avoiding emotional or manual bias through systematic processes.

Teaching & Mentorship

Teaching focuses on building strong foundations in programming, web development, and data handling, with content adapted to the student's level. The emphasis is on understanding core logic, building real projects, and learning how systems work end-to-end.

Programming Foundations

Python, Java, C / C++, C#

Core logic, problem solving, and writing clean, understandable code.

Web Development

HTML, CSS, JavaScript, React, Next.js

Building complete applications and understanding how frontend connects to backend.

Databases & Backend

SQL, PostgreSQL, APIs

How real applications store and use data, understanding data flow.

Advanced Topics

DSA, Machine Learning, AI fundamentals

When and why to use them, focusing on practical application.

Beginners & School-Level

Scratch (ages 12–13), Robotics basics

Logical thinking, curiosity, and building foundations.

Competitive & Academic

CEMC/CCC, USACO, Boards: IGCSE, IB, CBSE, ICSE

Structured preparation and concept clarity.