Visual Rule Editor

Build strategies by combining indicators with entry/exit rules. No coding required.

• Entry rules — all conditions must pass (AND logic). Add compare, near, or grouped conditions.
• Exit rules — ordered list, first trigger wins. Each can optionally skip min hold period.
• Add-ons — average down into existing positions when conditions are met.
• Config — min/max hold days, ATR stop multiplier, exit buffer.

Available Indicators (37)

AI Strategy Chat

Describe a strategy in plain English and the AI builds the rules for you. Example: "Buy when RSI drops below 30 and price is above the 200-day SMA, exit when RSI crosses above 50."

AI chat is available on the Pro plan.

Templates

Clone built-in templates as a starting point:

• V1 Momentum — price above SMA(20), RSI < 70
• V3 Dip Buyer — RSI < 45, near SMA(20), uptrend intact
• V4 Alpha Dip — RSI < 55, optimized from 1700-config parameter search

What Makes Our Backtester Different

• Survivorship-bias-free — uses historical NIFTY 50/100 composition from 2006, not today's stock list
• Capital constraints — real position sizing, sector caps, slippage (0.05% per side)
• Day-by-day simulation — V2 event loop processes each trading day sequentially, matching live behavior
• Dynamic composition — stocks entering/leaving indices trigger forced exits
• Dynamic position sizing — position size adjusts as capital grows/shrinks (10% threshold)

Universes

Results

Each backtest shows: CAGR, win rate, profit factor, max drawdown, yearly breakdown, exit reason analysis, per-symbol stats, equity curve, capital utilization chart, and Monte Carlo validation.

The agent runs on your machine and executes signals from the cloud. Your Kite credentials never leave your device.

Setup

1. Install: pip install kiteconnect
2. Generate API key: Settings → Trading Agent → Generate Key
3. Get Kite credentials from Zerodha Developer Console
4. Add redirect URL: http://127.0.0.1:5678/callback
5. Configure: python kite_agent.py configure
6. Run: python kite_agent.py run

Features

• Auto/manual signal execution
• GTT stop-loss placement after entries
• F&O support (auto product detection, lot size rounding)
• Margin pre-check before orders
• Position reconciliation (Kite vs cloud)
• Browser-based daily Kite login (one click)
• Obfuscated portfolio sync to cloud

Commands

Full documentation on GitHub

Setup

1. Find the bot: @ztrade_algo_bot
2. Send /start — the bot tells you your Chat ID
3. Go to Settings → Telegram → enter your Chat ID

Notifications

• Entry/exit signals generated
• Order executed or failed
• Daily portfolio summary
• Risk alerts (loss limits, sector caps)
• Kite session expiry

Bot Commands

What stays on your machine

• Kite API key and secret
• Kite access token
• Obfuscation factor
• Real position sizes, capital, P&L

What the cloud sees

• Strategy definitions (entry/exit rules)
• Obfuscated quantities and amounts (scaled by your factor)
• Trading patterns (symbols, dates, timing)
• Backtest results (derived analytics)

Obfuscation

All tradebook uploads scale quantities by a secret random factor stored locally. Prices stay real (public data). The cloud sees your trading patterns but not your actual capital size.

Display Privacy

An additional noise layer (±0-10%) on displayed values prevents screenshot-based reverse engineering. Control it in Settings → Display Privacy.

CAS / Tradebook Upload

NSDL CAS PDFs are parsed locally by the agent. PAN, folio numbers, and investor name are masked before upload. MF units and amounts are scaled by your obfuscation factor.

The SEBI static IP mandate (2026) applies only to order placement/modification, not to data access.

The agent can run in sync-only mode (no order placement) from any IP. Order execution requires a static IP from your ISP or a VPS proxy.