Nexus Journal Guide
Dhan Trade Journal
Nexus Journal supports Dhan workflows for traders who want broker-connected journaling, charge-aware analytics, and structured review of Indian market trades.
Reviewed 2026-07-15 by Nexus Journal product team.
Dhan sync and historical imports
Dhan data can be used to populate trading records, charges, taxes, and trade history depending on the available import or sync mode.
The goal is to reduce manual entry while preserving enough detail for serious review.
Charges and taxes
A trade can look profitable before costs and materially different after brokerage, exchange charges, GST, STT, stamp duty, SEBI charges, MTF interest, and other charges.
Nexus tax analytics is designed to keep gross and net views visible so traders do not confuse headline P&L with real retained P&L.
Real-time context
Where enabled, real-time price ticks help open-position metrics such as unrealized P&L, capital at risk, profit risk, and profit protected stay closer to market context.
This turns the journal into a live review surface rather than a static post-trade sheet.
Dhan India and US workflows
Dhan has CSV and connection-oriented import paths. The connected importer supports paginated historical tradebook retrieval, retry and rate-limit handling, and separate India and US flows; US records use broker security identity data to resolve symbols where available.
Market mode matters: Indian trades use Indian charge terminology, while US trades keep US symbol, currency, commission, and fee assumptions separate.
Dhan ledger, MTF, and charge boundaries
Dhan can fetch ledger and trade-charge data for selected date ranges. Its ingestion paths retain overlap and replay metadata, distinguish broker-sourced charges from user-entered adjustments, and handle supported MTF and DP-charge categories without assuming every ledger debit is a tax.
Reconcile fetched trade count, date range, symbols, gross result, ledger totals, and known DP or MTF charges. The Dhan ledger API may not expose every charge category at the same granularity.