Documentation

Everything you need to run it,
in the order you need it

Start with the quickstart, which gets a strategy backtesting in about ten minutes. The concepts section explains the vocabulary the rest of the platform uses, and the guides cover the things people actually get stuck on.

Quickstart

Install the client, authenticate, and run a backtest. This does not touch an exchange and cannot place an order.

1 · install

pip install tradelogx-nexus

2 · authenticate

export NEXUS_API_KEY="nxs_live_..."   # from Settings → API keys

3 · backtest

from nexus import Client

client = Client()               # reads NEXUS_API_KEY

result = client.backtest(
    strategy="structure-v4",
    symbol="BTC/USDT",
    timeframe="15m",
    start="2025-01-01",
    end="2026-01-01",
    risk_per_trade=0.005,       # 0.5% of equity
)

print(result.expectancy)        # 0.31R
print(result.max_drawdown)      # -0.082
print(result.trades[0].rationale)

Before you go live

A backtest that looks good is a hypothesis, not a result. Run the same strategy in paper mode against the live feed for a full month before committing capital — it costs nothing and produces an identical journal. The risk disclosure covers why this matters more than it sounds.

Guides

Task-shaped, not feature-shaped. Each one ends with something working.

5 min

Connect an exchange

Create a trade-only key, allowlist our egress addresses, and attach it. Keys carrying withdrawal permission are refused at connection time.

10 min

Run your first backtest

Point a strategy at a symbol and a date range. The Lab runs the same engine and risk path as live, so the result is a rehearsal rather than a different program.

8 min

Set a risk envelope

Daily and weekly loss budgets, exposure ceiling, correlation limits and per-strategy regime allowlists. Nothing trades outside them.

3 min

Promote paper to live

Paper mode consumes the live feed and produces identical journal output. Promotion is a flag, not a rewrite — and it is reversible.

Concepts

The vocabulary the API, the dashboard and the journal all assume. Worth ten minutes before the reference.

Conviction score: A weighted 0–100 across nine qualifications. The score is the output; the breakdown is always visible alongside it.
Regime: Volatility state and directional persistence, classified on three horizons. Strategies declare which regimes they may operate in.
Feature vector: The fixed-shape input the models score, stored verbatim so a decision is replayable months later with the exact inputs it saw.
Risk envelope: The thirteen checks an order intent must clear. A separate service with veto power; it fails closed.
Analogue recall: Previous trades in similar conditions, consulted at decision time. How the system stops repeating a mistake it has paid for.
Order intent: A sized decision that has not yet been through risk. Intents become orders only after the envelope clears.

Where to go next

The reference is exhaustive; these three pages are the ones people need first.

API referenceEvery endpoint, with request and response shapes SDKsPython, TypeScript, Go and Rust clients How it worksThe seven stages a trade passes through

Something missing or wrong here is a documentation bug and worth reporting the same way as any other — through the support center.

Quickstart#

Guides#