RN TradeLab for students

Free for your project. Yours to keep learning.

If you're doing a school or college project on trading, data analysis, or Python, RN TradeLab is free for the length of your course - no catch, no watered-down version. Pick your level below.

12th grade

Informatics Practices / CS

Use Python and pandas on real NSE data for your board practical project - on-syllabus, guided, no trading knowledge assumed.
Undergraduate

Computer Science

A real research platform for a final-year or course project - write strategies, backtest properly, and say something true about whether they work.
MBA

Finance electives

Build and evaluate a rule-based portfolio - Sharpe, drawdown, risk-adjusted return - without needing to write code yourself.

Not sure which fits? Email me and tell me your course and deadline - I'll suggest one.

Project briefs

12th grade · Informatics Practices / CS

Analysing NSE stock data with Python and pandas

A CBSE-aligned practical project: download real market data, run a simple backtest, and write up what you find. Uses only the Download and Backtest tabs - no trading knowledge required.

What you'll build

  • A dataset of NSE stock prices, downloaded and cleaned
  • A simple strategy tested on that data (a ready-made one works fine)
  • Charts and a results table for your project report

What you'll learn

  • Working with real-world tabular data in pandas
  • Reading and interpreting a results table
  • Writing a short technical report with evidence
2-3 weeks · no coding beyond basic Python
Undergraduate · Computer Science

Does parameter optimization actually improve results?

An empirical study using RN TradeLab's Optimize tab: tune a strategy's parameters on in-sample data, then check whether the improvement survives out-of-sample. A real answer to a real question in quantitative finance.

What you'll build

  • A parameter sweep across 2-3 strategies on a stock universe
  • A comparison of in-sample vs out-of-sample performance
  • A writeup on when (and whether) optimization helps

What you'll learn

  • Walk-forward testing and why it matters
  • Overfitting - recognising it, not just naming it
  • Reading Sharpe ratio, drawdown and profit factor honestly
4-6 weeks · comfortable with Python
Undergraduate · Computer Science

Momentum vs mean-reversion: a comparative backtest

Take two opposing trading ideas already in RN TradeLab's strategy library (Bollinger Breakout vs Bollinger Mean-Reversion) and test which one the Indian market actually rewards - and whether that answer changes across sectors.

What you'll build

  • Backtests of both strategies across multiple stocks/sectors
  • A comparison of risk-adjusted returns, not just raw returns
  • A conclusion grounded in out-of-sample evidence

What you'll learn

  • How the same indicator can support opposite strategies
  • Comparing strategies fairly (same data, same period)
  • Presenting a finding you can actually defend
3-5 weeks · comfortable with Python
MBA · Finance electives

Building a rule-based sector rotation portfolio

Use RN TradeLab's Portfolio and Performance tabs to construct a multi-stock portfolio and evaluate it the way a fund would - Sharpe ratio, max drawdown, and out-of-sample performance. No coding required.

What you'll build

  • A portfolio built from a ready-made strategy across a stock universe
  • A full performance evaluation (return, risk, drawdown)
  • A recommendation memo, as if presenting to an investment committee

What you'll learn

  • Risk-adjusted return vs raw return
  • Why correlation between holdings matters
  • Evaluating a strategy the way professionals actually do
2-4 weeks · no coding needed

Want guided help with your project?

Once I have 5-8 students interested in the same project type, I run a small guided group - a few sessions, hands-on, to make sure you actually understand what you built and can defend it in your viva or presentation. This is optional and separately priced; the app itself stays free either way.

I'm interested

New to the app? Start with the User Guide or just download RN TradeLab and explore.