CK.
Book a call

Stock market

Real capital, in the open

Live Dhan (rule-based algo) and Stocky (AI, verified): the same book I run, shown for transparency.

Dhan, the live book

Dhan · livealgorithmic

Rule-based algo. No LLM. Rebuilt daily from the Dhan trade book.

+14.8%
Return
gross ₹147,546 · net ₹114,702
2.46
Sharpe
−₹64,253
Max drawdown
51%
Win days
43
Active days
2026-10-01
As of

Account metrics · refreshed daily

Window: 1 Aug 2026 onward. The book traded before that date; those days are excluded here.

Cumulative return · % of capital · since 1 Aug 20262026-10-01
+14.8%
low +2.6%
best day +5.6%
+16%
0
-4%
Aug
Sep
Oct
44 trading days
₹1,000,000 base · gross
Daily P&L · grossgreen profit / red loss
Click a day for its trades.
3.93
Sortino
10.46
Calmar
1.55
Profit factor
₹2,667
Expectancy / day
67.2%
Ann. return
27.4%
Ann. volatility
6d
Win streak
6d
Loss streak
1.79
Recovery factor

Risk-adjusted ratios · per active day · N=43 days (small sample)

Disclaimer. An illustrative record of my own personal trading account, shown for transparency and educational purposes only. Not investment advice, a research recommendation, or a solicitation to buy, sell or copy any trade. Past performance is not indicative of future results; derivatives carry substantial risk of loss. I am not a SEBI-registered investment adviser.

Method: reconstructed from my Dhan trade book by FIFO. Headline, calendar and curve show gross realized P&L (matching the Dhan app); the net-of-charges figure (after brokerage/STT) is shown alongside, and each day's drill-down lists both. Risk-adjusted ratios are computed on the net series. The current day is mark-to-market (provisional). Stats use settled days only; open-day figures are excluded. Sharpe is per-active-day, annualized by root-252 (no-position days excluded, so not calendar-annualized), risk-free = 0. Drawdown-% is on a declared capital base. Ratios come from a small sample (43 active days) and will move materially as the record grows. Single account, single regime, no benchmark.

Stocky, the AI run

Stocky · ZerodhaAI · retired

fine-tuned Claude Haiku placed every trade itself. Indian F&O and commodities · Jun 2025 – May 2026 · now retired.

Zerodha · return % · 2025-06-02 → 2026-05-19verified ↗
+117%
+59%
+0%
Jun ’25
Jul ’25
Sep ’25
Nov ’25
Jan ’26
Mar ’26
May ’26
₹15L → ₹31.57L (+110% net)₹16.57L net verified ↗73% winSharpe 2.29

Realized P&L · % of ₹15L · holding-period-smoothed.

Jun 2025₹15L capital

Stocky goes live

Claude MCP + Haiku · ₹15L · Bank Nifty / Nifty / Sensex weeklies.

Jun–Sep 2025+₹3.6L · 51 days · 0 losses

Four months, zero losses

₹3.6L by September · ~₹90k/mo auto-pilot · 51 days · 0 losses.

Stocky · F&O · calendar · Jun–Sep (all green)
F&O · calendar · Jun–Sep (all green)
Stocky · F&O · P&L · Jun–Sep 2025
F&O · P&L · Jun–Sep 2025
29 Sep 20251st loss day

First loss

Over-traded volatile names (Eternal, Asian Paints, Tata Motors, BSE) · tightened the universe · net +2.87L after the red day.

Stocky · F&O · calendar · to 29 Sep (1st red day)
F&O · calendar · to 29 Sep (1st red day)
Stocky · F&O · P&L · after first loss (+2.87L net)
F&O · P&L · after first loss (+2.87L net)
Oct 2025

Adapt & rebound

Bank Nifty weekly → monthly · explored Deepseek · October rebounded hard.

Nov 20252nd loss day

Second loss

Second loss day of the run · net +3.94L through 24 Nov (two red days on the calendar).

Stocky · F&O · calendar · to 24 Nov (2nd red day)
F&O · calendar · to 24 Nov (2nd red day)
Stocky · F&O · P&L · after second loss (+3.94L net)
F&O · P&L · after second loss (+3.94L net)
Dec 2025₹5.32L · 2 loss days

Six months in

₹5.32L PnL · 212 profitable days · only 2 loss days.

Stocky · F&O · calendar · Jun–Dec (2 red days)
F&O · calendar · Jun–Dec (2 red days)
Stocky · F&O · P&L · Jun–Dec 2025
F&O · P&L · Jun–Dec 2025
Year one₹16.57L profit · verified

₹15L → ₹31.57L

Commodities ₹14.2L + F&O ₹2.37L = ₹16.57L profit · 73% win · Sharpe 2.29 · externally verified.

Stocky · F&O · overall
F&O · overall
Stocky · Commodity · overall
Commodity · overall
Full story →

Want to run this yourself? Mirror this book on your own account ↗