Know why your P&L looks the way it does.
Most platforms show you what happened. Kautilya shows you why. Factor regression isolates your alpha from market tilts. Rolling curves track your risk through time. The root-cause engine dissects every losing trade — sizing, timing, emotions, plan adherence — so you stop repeating the same mistakes.
Your return, decomposed.
You made 25% last year. How much was the market? How much was your value tilt? How much was actual alpha? Most retail investors can't answer. Kautilya runs a Fama-French 5-factor + momentum regression on your portfolio — weekly returns, 2-year window, India-calibrated — and breaks your return into six factor betas plus a residual alpha.
If R² is 0.91, factor loadings explain 91% of your return variation. The remaining 9% is your genuine stock-picking edge (or lack of it). Every beta comes with a t-statistic — green means statistically significant at 95%. This is the same decomposition institutional allocators run on their PMS mandates.
Risk isn't static. Watch it move.
A single-number beta is a snapshot. A rolling beta is a movie. Kautilya computes 30-day, 90-day, and 180-day rolling windows for beta, Sharpe, volatility, alpha, and inter-holding correlations — updated daily. When your 30-day beta spikes from 0.85 to 1.3, you see it before the next drawdown proves it.
The sparklines below are the same rolling curves compressed to glanceable thumbnails. In the workstation, each is an interactive chart with hover crosshairs, regime shading, and the ability to overlay any two metrics.
Stop losing the same way twice.
The journal tells you what happened. The root-cause engine tells you why. It categorises every losing trade into a mistake taxonomy — sizing, timing, symbol selection, hold duration, Greeks underestimation — and quantifies the damage. Then it correlates your behavioral flags (revenge, FOMO, no plan, broken SL) with actual P&L outcomes.
The result: specific, actionable insights. Not "you lost money in March" but "your revenge trades lose 4× more than average, and 80% happen in ELEVATED vol regimes on Tuesdays after 11 AM."
Your revenge trades lose 4× more than average. 12 trades, ₹57K lost — equivalent to 3 months of alpha.
Hold duration is your #1 loss driver. You hold losers 2.4× longer than winners — classic disposition effect costing ₹48K.
You trade well in STABLE vol regimes (62% WR, +₹3.2K avg). Your edge disappears in ELEVATED and inverts in DANGER.
When you set a stop loss AND follow it, your average loss is ₹2.1K vs ₹8.4K when you don't. The math is clear.
Every assumption, traced to source.
Kautilya's DCF doesn't pull inputs from thin air. Revenue CAGR comes from the annual report. EBITDA margin from 3-year historical average. WACC uses Damodaran's India ERP (11.14%) + CRP (4.12%) + 10-yr G-Sec as risk-free. Every number has a provenance badge — green for annual report, blue for historical, amber for Damodaran default.
The sensitivity matrix lets you stress any two inputs (WACC × terminal growth) and see how fair value shifts. Eight valuation methods — DCF, Reverse DCF, Scenario DCF, RIM, EVA, APV, SOTP, Comps — stacked in a football field. This is the same depth a sell-side analyst delivers, automated for every NSE 500 name.
Your P&L has a story. Read it.
Factor decomposition. Rolling risk. Behavioral root-cause. One workstation, zero guesswork.