DaxAlgo Terminal

Last updated: 2026-06-30

DaxAlgo Terminal is a desktop "cockpit" for watching markets and running trading strategies — a single, Bloomberg-style window that plugs into a dozen different brokers and data feeds, draws the charts, computes the math, and tells you when a strategy thinks something is happening. It does not place real orders. It is built for studying market microstructure, backtesting ideas, and generating signals — not for executing live trades.

🖼️ Screenshot: images/shell-main.png — the main window with the strategy catalog tiled and the activity-log drawer closed. (Capture pending — see docs/MEDIA-CHECKLIST.md.)

🎬 Video: images/video/shell-tour.mp4 — 2–3 min walkthrough: launch → connect → open a strategy → activity log. (Capture pending.)

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In plain terms — what is this, really?

Imagine a car dashboard, but for financial markets. Most trading screens show you a price going up and down. This one shows you the machinery underneath the price:

• The order book — the queue of people waiting to buy and sell, and how big each order is.
• The tape — every individual trade as it happens, and whether the buyer or the seller was the aggressor (who "crossed the spread" to get filled).
• Regimes — whether the market is calm or panicked, trending or stuck, risk-on or risk-off.
• Strategies — small programs that watch all of the above and raise a flag ("a signal") when their particular pattern shows up.

You connect it to a data source (some are free and need no account at all — the Binance crypto feed streams live with one click), pick the windows you care about, and optionally let strategies ping you on Telegram or Discord when they fire. Every number on screen is computed locally, in the app, so what you see in a chart, a backtest, and a live signal always agree.

You do not need to be a programmer, a mathematician, or a professional trader to use it. The documentation explains every feature and every formula from the ground up — see Documentation.

⛔ No live order execution

This build is data and signals only. There is no code path that sends a real order to a real broker. Strategies describe what they would do (enter/exit, long/short); they never do it with real money. This is a deliberate safety boundary, not a missing feature.

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Contents

• What ships
• Two builds: Windows and Linux
• The menus at a glance
• System at a glance — architecture diagram
• Quick start
• Screenshots & media
• Documentation
• Project graph
• License

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What ships

• 9 live strategies behind one plug-in seam. From simple to advanced: a cumulative-delta scalper, a four-window 3D regime-cube family (Order-Flow Cube, Order-Flow Surface Spike, Imbalance Heat Front, Index K-Score Surface), an index regime graph, a multi-stock order-flow pressure map, a research-paper strategy (Filtered Order-Flow Imbalance), and the flagship Σ⁻¹·IC Order-Flow Optimizer — a tape-primary composite that fuses twelve microstructure signals with mean-variance optimal weights. Full catalog: docs/strategies.md.
• 12 broker / data backends behind one IBrokerClient seam — Interactive Brokers (TWS API), NinjaTrader 8 (NTDirect), cTrader (Open API), Alpaca (REST + WebSocket), Ironbeam futures, London Strategic Edge (free multi-asset L1 + history), Upstox (Indian markets), and the keyless public crypto feeds Binance / Coinbase / Bybit / Kraken / OKX — plus an always-available offline Simulated broker so the app runs end-to-end with no account at all. docs/brokers.md.
• Charts & order-flow windows — TradingView-style charts (Windows), a live L2 order-book ladder, a bid/ask volume footprint with curve-fit POC predictors, and the combined Bookmap + VolBook liquidity-heatmap window. docs/charts.md.
• Strategy plugins (open-core) — install third-party strategies as code-signed plugins from the Plugins menu, or build your own against the DaxAlgo SDK. docs/plugins.md.
• Paper Lab — turn a research paper (e.g. an arXiv link) into a sandboxed reproduction that bridges into the backtest engine as a paper-tagged strategy. docs/paper-lab.md.
• Machine-Learning menu (Windows) — a stationarity & differencing lab (ADF/KPSS/ACF, fractional differencing), ARIMA + GARCH forecasting with confidence bands, and Kalman filters. docs/machine-learning.md.
• Market-regime suite — a 0–100 risk-on / risk-off composite blended from free public data, plus an 18-indicator × 8-timeframe Advanced regime board. docs/market-regime.md.
• Canonical market-data pipeline — a broker-neutral identity (InstrumentId), an Rx fan-out hub, tick-primary ingest, and a four-backend store (per-broker SQLite by default, single-file SQLite, PostgreSQL + TimescaleDB, or QuestDB), with an optional Telegram archive offloader. docs/market-data.md · docs/storage.md.
• Tick-level backtest engine + Backtest Studio — fee models, risk caps, an L1 fill model, a full statistics suite (Sharpe, Sortino, Calmar, Omega, Ulcer…), plus a headless CLI with run / sweep / walkforward / mc / tca / features. docs/backtesting.md.
• Notifications — fan signals out to Telegram and Discord, with an optional local-LLM (Ollama) commentary enricher. docs/notifications.md.
• AI Market Analyst — a four-agent Python sidecar (indicator → pattern → trend → decision) over loopback HTTP/JSON that annotates charts and gives a plain-language read. docs/ai-analyst.md.
• Bloomberg-style shell — black canvas, amber accent, monospace throughout. Every tool, strategy and chart opens as its own window; a live theme editor (Theme Studio) lets you recolour the whole app. docs/theme-studio.md.

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Two builds: Windows and Linux

The repository is split into two fully independent codebases so that work on the Linux port can never destabilise the Windows build. They share no project files — a fix that should apply to both is made twice, once per tree.

	Windows tree	Linux tree
Source root	src/windows/	src/linux/
Solution	TradingTerminal.Windows.slnx	TradingTerminal.Linux.slnx
Target framework	net9.0-windows7.0	net9.0
UI toolkit	WPF + MahApps Metro	Avalonia
Runs on	Windows 10/11	Linux, Raspberry Pi (ARM64), also Windows
Shell project	Shell/TradingTerminal.App	Shell/TradingTerminal.App.Avalonia

Both trees carry their own copy of the backend (Core, MarketData, Infrastructure, the backtest engine + CLI) and all 9 strategies, the order-flow tools, the regime board, the AI tool windows, the brokers, and the canonical pipeline. A handful of features are Windows-only because they depend on Windows-only components:

Feature	Windows	Linux	Why
9 strategies (incl. 3D regime cubes)	✅	✅	shared
Order Book · Volume Footprint · Bookmap + VolBook	✅	✅	shared
Correlation · Advanced regime · Recording · Backtest Studio	✅	✅	shared
AI tool windows (Analyst / Factor / ML / Backtest / Paper Lab)	✅	✅	shared
Brokers + canonical pipeline + backtest engine + CLI	✅	✅	shared
TradingView-style Charts	✅	❌	needs WebView2 (Windows)
Machine-Learning menu (Stationarity / ARIMA-GARCH / Kalman)	✅	❌	Windows-only windows
Strategy plugins + DaxAlgo SDK	✅	❌	plugin UI is WPF for now

Broker availability also depends on the OS — NinjaTrader's NTDirect.dll is Windows-only, for example. The full per-broker, per-OS matrix is in docs/brokers.md.

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The menus at a glance

Everything opens from the top menu bar. Here's the whole surface in one table (each item opens its own window unless noted):

Menu	Items
File	Reconnect to broker · Start QuestDB · Exit
View	Activity log (toggle) · Theme (Bloomberg Amber / Monochrome) · Customize theme… (Theme Studio)
Tools	Backtest Studio · Record live ticks · Advanced market regime · Correlation matrix · Live correlation matrix
Plugins	Manage strategy plugins…
LSE Tools	LSE backtester
Charts	Charts · Order book · Volume footprint · Bookmap + VolBook
Machine learning (Windows)	Stationarity & differencing · ARIMA & GARCH · Kalman filter
QuantConnect / LEAN	Backtest runner · Projects · Data sync · Settings & status
AI tools	Factor research · ML features · Backtest analysis · Market analyst · Paper Lab
Data	Market data archive · Archive history · Instant offload
Settings	Notifications · Research (Paper Lab)
Help	Support the developer · About

A guided tour of every one of these lives in docs/user-guide.md.

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System at a glance

The big idea: brokers are interchangeable, and everything downstream speaks one canonical language. A quote from Interactive Brokers and a quote from Binance become the same kind of record the moment they enter the app, so a strategy, a chart, or the database never has to care where the data came from.

flowchart TB
    subgraph Brokers["Data sources (external) — 12 + Simulated"]
        IB[Interactive Brokers]
        NT[NinjaTrader 8]
        CT[cTrader]
        AL[Alpaca]
        IR[Ironbeam]
        LSE[London Strategic Edge]
        UP[Upstox]
        CR[Binance · Coinbase · Bybit · Kraken · OKX]
        SIM[Simulated feed]
    end

    subgraph Seam["IBrokerClient seam — Infrastructure"]
        BS[BrokerSelector<br/>concurrent sessions · reconnect · API meter]
    end

    subgraph Pipeline["Canonical pipeline — MarketData"]
        ING[Ingest<br/>normalize · ref-count · stamp provenance]
        HUB[Hub<br/>Rx fan-out by InstrumentId]
        STORE[(Store<br/>SQLite / Postgres / QuestDB)]
        REG[InstrumentRegistry]
        ARCH[Archive offloader<br/>→ Telegram]
    end

    subgraph Consumers["Consumers — UI + engine projects"]
        STRAT[Live strategies ×12]
        TOOLS[Charts · OrderBook · Footprint · Bookmap]
        REGML[Regime · Correlation · Machine Learning]
        BT[Backtest engine + Studio + CLI]
        AI[AI analyst + Paper Lab sidecar]
        NOTIF[Notifications: Telegram · Discord]
    end

    Brokers --> BS --> ING
    ING --> HUB
    ING --> STORE
    STORE --> ARCH
    REG -.identity.-> ING
    HUB --> STRAT
    HUB --> TOOLS
    STORE --> REGML
    STORE --> BT
    STRAT --> NOTIF
    STRAT --> AI

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See docs/architecture.md for the full design rationale, the threading model, and the component + dependency diagrams.

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Quick start

You need the .NET 9 SDK and Git. No broker account is required to build or run — the Simulated broker serves a synthetic feed offline, and the Binance tile streams real live crypto data (bars, L1, L2 depth, trades) with no API key and no account.

Windows (WPF)

git clone https://github.com/dhruuvsharma/DaxAlgo-Terminal.git
cd "DaxAlgo Terminal"
dotnet build TradingTerminal.Windows.slnx
dotnet run --project src/windows/Shell/TradingTerminal.App.Intermediate

The Windows terminal ships as three editions — three fully independent shell exes with no shared shell code (each carries its own complete copy, so lower tiers physically exclude the higher-tier feature DLLs):

Edition	Run	What you get
Basic	dotnet run --project src/windows/Shell/TradingTerminal.App.Basic	Keyless brokers only (crypto + Simulated), full strategies catalog, core charts & tools
Intermediate	dotnet run --project src/windows/Shell/TradingTerminal.App.Intermediate	All 12 brokers with the full credentialed login; same tools as Basic
Professional	closed source	Everything — adds Machine Learning, AI tools (Paper Lab + sidecar), LSE Tools, QuantConnect / LEAN, 3D Surface Lab, experimental charts. Developed in a private overlay repo on top of this one; distributed as a binary release.

Basic and Intermediate are fully open source in this repo. The Professional edition's exclusive surfaces live in a private repo that consumes this one as a git submodule.

Linux / Raspberry Pi (Avalonia)

git clone https://github.com/dhruuvsharma/DaxAlgo-Terminal.git
cd "DaxAlgo Terminal"
dotnet build TradingTerminal.Linux.slnx
dotnet run --project src/linux/Shell/TradingTerminal.App.Avalonia

There is no bare dotnet build with no argument — two solutions exist, so always name one. The helper scripts build-and-test.ps1 (Windows) and linux/build-and-test.sh / linux/Dockerfile (Linux) wrap each tree.

Want to skip the login screen while developing? The Windows shell ships dev launch profiles (Dev: Simulated (offline), Dev: Replay (local DB), Dev: Live (no login)) that auto-connect and go straight to the main window. See docs/getting-started.md.

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Screenshots & media

📌 All screenshots and videos are being (re)captured. Until then you'll see clean 🖼️ _coming soon_ / 🎬 _coming soon_ placeholders throughout the docs — every one is reserved with an exact target filename in docs/MEDIA-CHECKLIST.md, so nothing renders as a broken image.

Slot	Shows
images/shell-main.png	The shell — strategy catalog + menus
images/login-window.png	Multi-broker login
images/strategy-sigmaicflow-window.png	Σ⁻¹·IC Order-Flow Optimizer
images/chart-bookmap.png	Bookmap + VolBook liquidity heatmap
images/chart-footprint.png	Volume footprint
images/tool-backteststudio.png	Backtest Studio
images/ai-marketanalyst.png	AI Market Analyst
images/tool-advancedregime.png	Advanced market-regime board

The full list (every strategy, tool, chart and window) is in docs/MEDIA-CHECKLIST.md.

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Documentation

All documentation lives in docs/ and is written for two readers at once: a plain-English explanation first (with analogies and worked examples), then the technical and mathematical depth below it. Quick links:

Audience	Start here
Brand-new user	getting-started.md, user-guide.md
Setting up a broker	brokers.md, ib-tws-setup.md
Understanding the strategies	strategies.md
The actual math (from scratch)	math-reference.md
Charts & order-flow windows	charts.md
Backtesting	backtesting.md
Plugins & the SDK	plugins.md
Paper Lab (reproduce a paper)	paper-lab.md
Storage & databases	storage.md, market-data.md
Tuning configuration	configuration.md
Architecture & contributing	architecture.md, contributing.md
Something broken	troubleshooting.md

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Project graph

Each box is a project; arrows mean "depends on". The shape is deliberately a layered fan: a dependency-free Core at the bottom, the data pipeline above it, then everything user-facing on top. Adding a broker or a strategy is a new leaf + one registration line — the shell never changes.

flowchart TD
    App --> Core & MarketData & Infrastructure & UI & Login & Ai
    App --> Strategies["Strategies.* ×12"]
    App --> ToolWins["Tool / chart / ML / AI windows<br/>Charts · OrderBook · VolumeFootprint · Heatmap ·<br/>Correlation · AdvancedMarketRegime · BacktestStudio ·<br/>Recording · Ml.* · Ai.* · QuantConnect · LseBacktest"]
    App --> Plugins["Plugins (DaxAlgo SDK)"]
    Login --> Core & UI & Infrastructure
    Ai --> Core & UI & Infrastructure & MarketData
    Strategies --> Infrastructure & UI & Core
    ToolWins --> Infrastructure & UI & Core & MarketData
    Plugins --> SDK[DaxAlgo.Sdk] --> Core
    Infrastructure --> MarketData & Core
    MarketData --> Core
    UI --> Core
    Core --> Nothing([no dependencies])

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Core has zero dependencies on UI, WPF/Avalonia, or any broker SDK. MarketData (the canonical pipeline) sits just above it. Adding a broker = one IBrokerClient implementation in Infrastructure/<Broker>/ + one DI block. Adding a strategy = one TradingTerminal.Strategies.<Name> project + one DI line. The same structure holds in both the Windows and Linux trees.

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License

AGPL-3.0 — see LICENSE. You can use, modify, and redistribute this code freely, but derivative works (including network services built on it) must be published under the same license. Two carve-outs:

• Plugin SDK (src/windows/Sdk/ — DaxAlgo.Sdk, DaxAlgo.Sdk.Wpf) stays MIT (see src/windows/Sdk/LICENSE), so third-party plugins built against the SDK are not bound by the AGPL.
• The Professional edition is proprietary, developed in a private repo, and not covered by this license.

Code published before 2026-07-09 was released under MIT and remains available under those terms in the repo history. Built by Dhruv Sharma. If the project is useful to you, the Help → Support the developer menu explains how to say thanks.