Intermediate
Practice Drills: Coding a Momentum Strategy From Scratch
A drill-based course for quant analyst aspirants, prop trading applicants and traders who want to systematize their process. Each lesson is one tightly scoped coding task with a spec, starter code, a worked solution and checks you can score yourself on. You will build a momentum strategy piece by piece in pandas: validating an NSE price panel, coding time-series and cross-sectional momentum scores, turning ranks into positions without look-ahead bias, charging realistic Indian costs, and scoring the result. The course ends with a bug hunt, an honest parameter sweep and a timed rebuild from a blank notebook. This is a coding skill course, not a recommendation to trade any strategy.
Momentum InvestingPython for TradingPandasBacktestingCross-Sectional MomentumNSE DataTransaction CostsAlgorithmic Trading
MODULES
5
DURATION
4 Hours
TRACK
Algorithmic Trading
What You'll Master
Load, validate and align an NSE price panel in pandas before any signal touches it
Code time-series momentum, the 12-1 lookback and volatility-adjusted momentum scores
Rank a stock universe cross-sectionally and turn ranks into top-N equal-weight positions
Apply the shift(1) rule and rebalance calendars so no future data leaks into a signal
Control turnover with holding buffers and add a simple market regime filter
Compute portfolio returns from a weights matrix and charge STT, brokerage, stamp duty and impact cost at each rebalance
Score a backtest with CAGR, volatility, Sharpe ratio and max drawdown against Nifty 500 TRI
Find look-ahead, survivorship and off-by-one bugs, and run parameter sweeps without overfitting
Access Level
LEARNER
Everything included
Full Text Playbooks
Actionable Exercises
Mobile Reading Mode
Lifetime Updates