Quantitative finance worked out in full, for Indian markets. Option structures, portfolio construction, risk measurement and machine learning applied to NSE data.
9 posts across 9 categories
How butterfly option structures actually work: the payoff shape, why iron and long butterflies are the same trade, and the honest risk in a broken wing.
How credit spreads and iron condors work, what the premium compensates you for, the margin reality, and the payoff shape that catches option sellers out.
Applying machine learning to equity selection: why cross-validation breaks on time series, where data leakage hides, and when a linear model is better.
How to hedge an equity portfolio with index options: sizing the hedge, what protective puts and collars actually cost, and when not to bother at all.
Why drawdowns are harder to recover than they look, what Value at Risk does and does not tell you, and how to size positions so a bad month stays survivable.
How diversification actually creates value, what the efficient frontier shows, and why mean-variance optimisation produces portfolios nobody should hold.
How quantitative analysis works: handling market data properly, the statistics that earn their place, factor models, and the four ways a backtest lies to you.
Technical analysis explained honestly: what the charts actually show, which claims survive testing, and how to check whether an indicator works at all.
Fundamental analysis in practice: which financial statement to trust, what the ratios really answer, and the governance red flags that precede most failures.