US and India, one terminal
Say what you want your money to do and we draft the plan. See how it would have done against its benchmark, then run it on paper with real market prices, a desk of AI analysts on it, a bull and a bear arguing any name, and a grade on the book from Sarathi. Every trade waits for you.
Research tooling, not investment advice. Backtests are simulations; nothing here is a recommendation.
Over its own daily marks, the book doesn't follow the S&P 500 closely enough to judge it against it: its daily moves correlate 0.50 with it, under the 0.70 I need and it strays from it by 13.6% a year, over the 10% I allow. I have no other index to offer in its place, so I leave results out of the grade.
27 of your 30 scored holdings rank in the top half of the names your portfolio configuration chooses from.
The whole book, cash included, moves about 18% a year (the shares alone 19%), inside the 5% to 20% range for a balanced profile.
Every holding is in the latest scoring run.
Your largest 5 holdings are 33% of the book. Health Care is 65% of the book, over the 35% ceiling for one sector in a balanced profile. Your portfolio configuration picks only 2 sectors, so the book cannot sit under the 35% ceiling; it needs at least 3.
Your portfolio configuration sets no sector targets, so there is nothing to drift from.
Cash is 6.8% of the book against a 5.0% reserve for a balanced profile. That is within policy: up to 2 points over it is tolerated.
Since 2026-09-12: 7 calls right, 6 wrong, 0 about even. The book is up 3.6%, SPY flat.
Wrong: sell MRK on 2026-10-07. It’s up 3.1% since, SPY down 1.7%.
Wrong: sell AMGN on 2026-10-07. It’s up 8.3% since, SPY down 1.7%.
Wrong: buy KEYS on 2026-10-04. It’s down 19.0% since, SPY down 0.7%.
The platform’s own review, retrieved on 22 Oct 2026, 22:49 UTC. Sign in and the same desk grades your book.
Strategy Lab
Two demo portfolio configurations, one on each market, run under every strategy engine over the same history. The lab exists to say which strategies beat the index on that configuration and which did not, before a rupee or a dollar moves. What it found is below, as it is stored.
| Engine | Rank | CAGR | Sharpe | Max DD | vs index |
|---|---|---|---|---|---|
| Trend Regime | 1 | 17.1% | 1.06 | -8.0% | beat |
| Momentum‑Trend | 2 | 17.3% | 1.06 | -10.6% | beat |
| Engine 3 | 3 | 17.3% | 1.06 | -10.6% | beat |
| Engine 4 | 4 | 17.7% | 1.05 | -8.9% | beat |
| Engine 5 | 5 | 17.7% | 1.05 | -8.9% | beat |
| Engine 6 | 6 | 16.4% | 1.02 | -10.6% | beat |
| Engine 7 | 7 | 15.4% | 0.96 | -11.1% | beat |
| Engine 8 | 8 | 13.9% | 0.92 | -12.4% | beat |
| Engine 9 | 9 | 14.0% | 0.90 | -10.1% | beat |
| Engine 10 | 10 | 9.6% | 0.83 | -11.1% | lagged |
| Engine 11 | 11 | 7.4% | 0.75 | -9.8% | lagged |
| Engine 12 | 12 | 4.8% | 0.51 | -10.1% | lagged |
| Engine | Rank | CAGR | Sharpe | Max DD | vs index |
|---|---|---|---|---|---|
| India Volume Reversal | 1 | 18.4% | 1.55 | -7.9% | beat |
| Sector Rotation | 2 | 18.7% | 1.53 | -9.0% | beat |
| Engine 3 | 3 | 15.0% | 1.45 | -8.2% | beat |
| Engine 4 | 4 | 11.5% | 1.41 | -9.8% | beat |
| Engine 5 | 5 | 17.4% | 1.40 | -8.8% | beat |
| Engine 6 | 6 | 16.3% | 1.40 | -8.7% | beat |
| Engine 7 | 7 | 16.8% | 1.40 | -8.7% | beat |
| Engine 8 | 8 | 16.8% | 1.40 | -8.7% | beat |
| Engine 9 | 9 | 16.2% | 1.38 | -8.2% | beat |
| Engine 10 | 10 | 18.1% | 1.29 | -10.9% | beat |
| Engine 11 | 11 | 18.1% | 1.29 | -10.9% | beat |
| Engine 12 | 12 | 12.2% | 1.04 | -17.8% | beat |
Every curve and figure above is a stored run, retrieved from the platform on 22 Oct 2026, 22:49 UTC. Engines whose curves coincide on a portfolio configuration are shown as the lab stores them.
Say what you want your money to do. The AI drafts a plan: how much risk, how many stocks, any sectors you believe in. You can change all of it before anything runs.
See how the plan would have done over the last three years against its benchmark, with what a backtest cannot tell you said beside it. In the Strategy Lab you can run it under every strategy and compare.
Build it as a paper portfolio on real market prices. Rebalances arrive as proposals with a written reason per name, and nothing trades until you accept.
A desk of AI analysts, a bull and a bear on any holding, the Telegram buzz on your names, and Sarathi to ask about the whole book.
What it holds
From a portfolio config to a book that runs.
Universe, sectors, risk profile, position count and cash reserve, with a composition panel showing what you can actually buy.
One portfolio configuration under every engine at once, ranked on risk-adjusted return, curves stored.
Backtest your own stock list with every trade recorded, and save it.
Cash or funded paper books on live prices, in USD or INR, with rebalances proposed and explained on a schedule you set.
A grade on your book, what it would change and why, and a written letter you can act on.
Read a Zerodha or SnapTrade account beside your paper books. Nothing is placed for you.
The evidence under every decision.
A 24-factor read per name, its ownership (13F, fund holdings, mutual-fund schemes, promoter pledge and SAST), filings and a decision snapshot.
What-if from revenue through margin to EPS and multiple.
Who reports next, our forward EPS beside the street's, call sentiment, an AI read of the 8-K, and post-earnings drift.
An event in one company and the names it reaches, with the business linkage, not just the correlation.
Monte Carlo across size and sector: how many names actually diversify.
The strategy's target book and its stored, benchmark-relative history.
The session, as it happens.
The session that just closed: movers, breadth, earnings, news, and what wants a decision from you.
The realtime engine and its signals during market hours.
Market news mapped to tickers and scored, for the US and India.
What Telegram channels are saying, by ticker, with each call judged at the close and each channel graded.
S&P 500 to S&P 600, Dow 30, Nifty 50 to the total market, and sector slices of both.
Grounded in what the platform computed.
Opposing cases argued per security, then judged, so the weak side of a thesis is visible.
Agents on regime, macro, risk, concentration and news, all writing from one fact pack.
Ask about exposure, risk or a holding; the answer is computed from your positions.
Every screen answers questions about what it is showing, from the numbers on it.
Underneath
10-K, 10-Q and 8-K filings, XBRL facts, earnings releases, Forms 3/4/5, 13F, 13D/G and N-PORT fund holdings
Bhavcopy prices, corporate filings, Reg-31 shareholding, pledge and SAST disclosures, mutual-fund scheme portfolios
Daily bars for both markets, corporate-action adjusted, index membership, with a data-quality verdict per security
FRED macro panel, news mapped to tickers and scored, and Telegram channels read and graded on their calls
Counts as the platform reported them on 22 Oct 2026, 22:49 UTC.
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