# tsquant

**Repository Path**: liebin/tsquant

## Basic Information

- **Project Name**: tsquant
- **Description**: TsQuant（天时量化） —— 基于江恩理论第七章「一套实用的交易模式」的完整工程化实现。

系统将江恩历经十余年实盘验证的七大交易原则转化为可量化、可回测、可执行的策略规则与资金管理体系，帮助投资者排除主观臆断和猜测，严格遵循交易规则，实现长期稳定盈利。

核心理念：跟随主要趋势，永不对抗主要趋势。
- **Primary Language**: Java
- **License**: AGPL-3.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 1
- **Forks**: 0
- **Created**: 2026-07-25
- **Last Updated**: 2026-07-26

## Categories & Tags

**Categories**: Uncategorized

**Tags**: 江恩理论, 量化交易, Java, SpringBoot, ctp

## README

# TsQuant (Timing Quant) — An Engineering Implementation of Gann Theory Chapter 7

This system is a **complete engineering implementation** of **Chapter 7 "A Practical Trading System"** from **W.D. Gann's** classic work *"The Forecasting Method of W.D. Gann"*. It transforms Gann's **seven trading principles**, which were verified through over a decade of real‑world trading, into quantifiable, backtestable, and executable strategy rules and a capital management system. It helps traders **eliminate subjective judgments and guesswork**, strictly follow trading rules, and achieve consistent long‑term profitability.

> **Core Philosophy:** *"Human weaknesses defeat the majority of traders, not the market itself. While trading, we must eliminate subjective judgments and guesswork, and we must not trade based on hope or fear."* — This is exactly the design starting point of TsQuant.


## 🚀 Project Overview

TsQuant (Timing Quant Trading Platform) is a **zero‑programming** quantitative trading assistant tool designed for professional users such as small and medium‑sized proprietary trading teams. The system **engineers** classical trading theories such as Gann's, using a **multi‑rule weighted scoring system** for trend identification, combined with **dynamic profit/loss stops and intelligent position sizing**, to provide a **complete quantitative trading loop** from market data collection and strategy signal generation to investment plan execution and trading report analysis.

**Core Philosophy:** *Follow the major trend, never fight it; eliminate subjective judgments and guesswork, strictly adhere to trading rules.*


## 📸 Feature Preview

Below are screenshots of the TsQuant platform's core interfaces, showcasing the complete trading management workflow.

| Screenshot | Description |
|------------|-------------|
| ![Login Page](img/功能截图1.png) | **Login Page**: Platform entry with account/password and CAPTCHA authentication, multi‑tenant architecture |
| ![Investment Plan Management](img/功能截图2.png) | **Investment Plan Management (Main Dashboard)**: Core trading monitoring interface displaying all open positions with net value, profit/loss ratio, trend status (up/down/consolidation), direction, and Gann key levels (3H/3L/KH/KL), supporting operations like open, close, add, reduce, and mute |
| ![Strategy Order & Position Details](img/功能截图3.png) | **Strategy Order & Position Details**: Complete data chain for each position including entry price, latest price, stop‑loss, take‑profit, volume, floating P&L, and yield, with fine‑grained operations for closing, adding, and reducing |
| ![Investment Performance Analysis](img/功能截图4.png) | **Investment Performance Analysis**: Aggregated performance metrics by investment plan including win rate, net profit, yield, total profit/loss, and commission, with multi‑dimensional filtering and data export |
| ![Account Management](img/功能截图5.png) | **Account Management**: Unified management of multiple trading accounts, displaying dynamic equity, capital usage rate, available funds, position principal, and P&L for each account, supporting add, modify, and delete operations for centralized multi‑account monitoring and risk control |


## 📖 Trading Principles & Technical Implementation

> 📄 For complete trading principles and technical implementation details, please refer to [docs/交易原则与技术实现.md](docs/交易原则与技术实现.md)

This document elaborates on:
- Complete mapping to Gann Theory Chapter 7 (7 trading principles → code implementation mapping table)
- Built‑in trading rules explained (first‑position cap, dynamic position scaling, pyramiding, max single‑trade loss, trend reversal, dynamic stop‑loss, blow‑up protection)
- Engineering details of the seven trading principles (original quotes + complete technical implementation for Principles 1–7)


## 🏗️ Multi‑Rule Weighted Scoring System

The system's core innovation is the **multi‑rule weighted scoring** mechanism: multiple trend‑judging rules run independently in parallel. Each rule outputs a direction (long/short/wait) and a weight score, and the final combined trend direction is derived from the weighted sum.

```
SuperJeTradeRule(weight 3.0) ──┐
SuperMaTradeRule(weight 3.0) ──┤
MaXTradeRule ──────────────────┤
Trend01Rule(weight 3.0) ───────┤
Je01TradeRule ─────────────────┼──→ Weighted sum → Combined direction (B/S/W)
Kf02TradeRule ─────────────────┤
Kf03TradeRule ─────────────────┤
Ma01TradeRule(+2, veto) ───────┤
Ma02TradeRule(+1, veto) ───────┤
Je02TradeRule(+2, veto) ───────┤
Kf01TradeRule(weight 6.0, veto)─┘
```

- Non‑veto rules: give a direction and a weight, participate in the weighted calculation.
- Veto rules: have higher weights (e.g., Kf01 with weight 6.0) and can override the combined result of other rules.
- **Note**: When the strategy is JE00/JE01, only SuperJeTradeRule is used for direction judgment.


## 🧩 Strategy Rule Interface

All strategy rules implement the `BaseStrategyRule` interface. Core methods:

| Method | Description |
|--------|-------------|
| `needToOpen()` | Determines whether the current price satisfies opening conditions |
| `needToClose()` | Determines whether the current position should be closed (take profit / stop loss / reversal) |
| `getMainDirection()` | Returns the main trend direction |
| `getStopPrice()` | Calculates the stop‑loss price |
| `getPriceLines()` | Calculates the upper and lower price bands (buy/sell lines) |

New strategies only need to implement this interface and register in `StrategyRuleMap` – no framework changes required.


## 🏢 Business Architecture

```
┌─────────────────────────────────────────────────────────────────┐
│                    Frontend (Vue3 + ElementPlus)                │
├─────────────────────────────────────────────────────────────────┤
│  Gateway  │  System Management  │  Invest (Trading Core)        │
├───────────┼─────────────────────┼───────────────────────────────┤
│           │                     │  Strategy Engine │ Backtest    │
│           │                     │  Signal Processor│ Report Gen │
├───────────┴─────────────────────┴───────────────────────────────┤
│                     Foundation Layer (tsquant-base)              │
│  ┌─────────┬─────────┬─────────┬─────────┬─────────┬─────────┐ │
│  │  Rule   │  Data   │  Util   │  CTP    │  Core   │  Model  │ │
│  └─────────┴─────────┴─────────┴─────────┴─────────┴─────────┘ │
├─────────────────────────────────────────────────────────────────┤
│                     Data Storage Layer                          │
│  ┌──────────────┐  ┌──────────┐  ┌──────────┐                  │
│  │ MariaDB/MySQL│  │  Redis   │  │ CSV files│                  │
│  └──────────────┘  └──────────┘  └──────────┘                  │
├─────────────────────────────────────────────────────────────────┤
│                     External Data Sources                       │
│  ┌──────────┐  ┌──────────┐  ┌──────────┐  ┌──────────┐       │
│  │ CTP       │  │ TqSdk    │  │ EastMoney│  │ Sina/Sohu│       │
│  └──────────┘  └──────────┘  └──────────┘  └──────────┘       │
└─────────────────────────────────────────────────────────────────┘
```


## 🧰 Functional Modules

### 1. Strategy Engine (tsquant-base-rule)

Multi‑strategy, multi‑factor trend‑judging system built on Gann theory. Registered strategies:

| Strategy ID | Name | Type | Description |
|-------------|------|------|-------------|
| TS00 | Timing 00 | Timing Series | Default strategy, Dual‑Thrust variant |
| JE00 | Gann Theory (Legacy) | Gann Theory | Legacy Gann theory implementation |
| JE01 | Gann Theory 01 | Gann Theory | Trend following based on Gann, manual entry, dynamic stop |
| JT01 | Sakata Rules 01 | Sakata Rules | Trading strategy based on Sakata rules |
| DM01 | Dual MA 01 | Classic | MA5/MA10 crossover + price confirmation |
| RB01 | R‑Breaker | Intraday | Follows intraday price, breakout buy / reversal sell |
| DT01 | Dual‑Thrust | Intraday | Calculates upper/lower bands based on N‑day high/low close, breakout entry |
| FF01 | Furui Four‑Price | Intraday | Uses yesterday's high/low as bands, breakout entry, exit on re‑crossing open |

**Trend‑judging rule set (BaseDirectionRule):**

| Rule Class | Name | Weight | Veto | Description |
|------------|------|--------|------|-------------|
| SuperJeTradeRule | Gann Super Rule | 3.0 | No | Based on Gann's 7 principles, using weekly highs/lows and volatility |
| SuperMaTradeRule | Super MA Rule | 3.0 | No | Based on MA5~MA60 multi‑period alignment and candlestick patterns |
| MaXTradeRule | MA X Rule | - | No | Based on MA crossovers |
| Trend01Rule | Trend 01 | 3.0 | No | Based on trend state (up/down/topping/bottoming) and risk/reward |
| Je01TradeRule | Gann 01 Rule | - | No | Gann theory direction judgment auxiliary rule |
| Kf01TradeRule | Candlestick 01 | 6.0 | Yes | Identifies one‑candle piercing two MAs at extremes |
| Kf02TradeRule | Candlestick 02 | - | No | Auxiliary candlestick pattern judgment |
| Kf03TradeRule | Candlestick 03 | - | No | Auxiliary candlestick pattern judgment |
| Ma01TradeRule | MA 01 | +2 | Yes | Auxiliary MA trend judgment |
| Ma02TradeRule | MA 02 | +1 | Yes | Auxiliary MA trend judgment |
| Je02TradeRule | Gann 02 Rule | +2 | Yes | Gann theory trend reversal judgment |

### 2. Market Data Layer (tsquant-base-data)

- **Multi‑source data collection:** supports CTP, EastMoney, Sina, Sohu, etc.
- **K‑line data management:** supports stocks, futures, options, indices, etc.
- **K‑line Image (KlineImage):** computes key levels (support/resistance), moving averages, volatility, and other technical indicators.
- **Main contract management:** automatic identification and rollover for futures.

### 3. Backtesting Engine (tsquant-base-util)

- **Event‑driven backtesting engine (BackTestEngine):** supports tick‑by‑tick or bar‑by‑bar backtesting.
- **Dynamic position sizing:** supports fixed or dynamic (auto‑increase with net value).
- **Dynamic stop/take‑profit tracking.**
- **Commission calculation:** supports both fixed‑amount and percentage‑based.
- **Rollover handling:** automatic contract rollover.
- **Backtest report generation:** automatically generates backtest reports including win rate, profit/loss ratio, max drawdown, etc.

### 4. Trading Execution Layer

- **CTP integration** (tsquant-base-ctp): full encapsulation of CTP futures trading API, including authentication, login, order placement, cancellation, and query.
- **TqSdk integration** (tsquant-base-tqsdk): integrates Tianqin quantitative SDK, supports both simulation and live trading.
- **Conditional order management:** supports stop‑loss, take‑profit, and other conditional orders.
- **Position management:** real‑time position monitoring and P&L calculation.
- **Capital management:** account balance query, risk monitoring, dynamic capital usage ratio.

### 5. Investment Plan Management

- **Investment Plan (InvestPlan):** defines trading instrument, strategy rules, capital, max loss ratio, etc.
- **Investment Strategy (InvestStrategy):** combination of strategy rules and factors.
- **Investment Solution (InvestSolution):** multi‑plan portfolio management.
- **Execution monitoring:** real‑time status tracking, supports pause/quiet modes.

### 6. Report & Analysis

- **Investment report:** detailed reports by instrument and time dimension.
- **Strategy KPIs:** win rate, profit/loss ratio, max drawdown, etc.
- **Account report:** comprehensive analysis by account.


## 🛠️ Technical Architecture

### Technology Stack

| Category | Technology |
|----------|------------|
| Language | Java 17 |
| Framework | Spring Boot 3.5 |
| Frontend | Vue3 + ElementPlus (RuoYi‑Vue‑Plus framework) |
| Database | MariaDB / MySQL |
| Cache | Redis (Redisson) |
| Message Queue | LMAX Disruptor (in‑process high‑performance queue) |
| Technical Indicators | TA‑Lib (C library) |
| CTP Interface | JCTP (Java CTP wrapper) |
| Quant SDK | TqSdk (Tianqin) |
| Build Tool | Maven |
| Serialization | Fastjson2 |
| HTTP Client | OkHttp3 |
| HTML Parser | Jsoup |

### Core Design Patterns

1. **Strategy Pattern:** Strategy rules are defined via the unified `BaseStrategyRule` interface; `StrategyRuleMap` manages all strategy instances.
2. **Observer Pattern:** Uses LMAX Disruptor for publish‑subscribe processing of market events.
3. **Default Method Pattern:** `BaseStrategyRule` provides default methods for common open/close flows; specific strategies override for custom logic.
4. **Factory Pattern:** `StrategyRuleMap` serves as a factory to create strategy instances by name.
5. **Singleton Pattern:** Core utility classes are static singletons.

### Data Flow Architecture

```
Market Data Source → MarketDataHandler → InvestPlanHandler → Strategy Engine → Trading Orders
       ↓                    ↓                    ↓                  ↓              ↓
  Data Collection      Signal Filtering    Open/Close Check    Trend Judge    CTP/TqSdk
       ↓                    ↓                    ↓                  ↓              ↓
  K‑line Storage      Latency Statistics   Position Calculation  Stop/Take     Execution
```


## 🔄 Complete Quantitative Trading Flow

> 📄 For complete flow details, please refer to [docs/量化交易完整流程.md](docs/量化交易完整流程.md)

### Business Flow System

TsQuant platform includes the following main business flows:

| Flow | Description |
|------|-------------|
| **Core Trading Flow** | 11‑stage real‑time trading execution for simulation and live strategies (system core) |
| **Backtesting Flow** | Historical data backtesting, independent analysis function |
| **Reporting Flow** | Multi‑dimensional reports at account and investment plan levels (daily/weekly/monthly) |
| **Data Pipeline Flow** | K‑line data download, parsing, and cache management |
| **Quotation Subscription Flow** | Dynamic management of market data subscriptions |
| **Account Maintenance Flow** | Account connection keep‑alive and equity synchronization |
| **Factor & Direction Recalculation Flow** | Periodic recalculation of strategy parameters |
| **Manual Intervention Flow** | User manual open/close, add/reduce position operations |

### Core Quantitative Trading Flow (11 Stages)

The system runs a multi‑stage pipeline during trading hours, connected by queues and Disruptor ring buffers:

```
┌─────────────────────────────────────────────────────────────────────────┐
│                   Core Quantitative Trading Flow (11 Stages)            │
├─────────────────────────────────────────────────────────────────────────┤
│                                                                         │
│  ┌──────────┐    ┌──────────┐    ┌──────────┐    ┌──────────┐         │
│  │ Stage 1  │───→│ Stage 2  │───→│ Stage 3  │───→│ Stage 4  │         │
│  │ Market   │    │ Signal   │    │ Strategy │    │ Order    │         │
│  │ Data     │    │ Filter   │    │ Evaluate │    │ Generate │         │
│  │ 1/sec    │    │Disruptor │    │Disruptor │    │ 5ms      │         │
│  └──────────┘    └──────────┘    └──────────┘    └──────────┘         │
│                                                                         │
│  ┌──────────┐    ┌──────────┐    ┌──────────┐    ┌──────────┐         │
│  │ Stage 5  │───→│ Stage 6  │───→│ Stage 7  │───→│ Stage 8  │         │
│  │ Exchange │    │ Status   │    │ Fill     │    │ Cancel & │         │
│  │ Submit   │    │ Track    │    │ Monitor  │    │ Retry    │         │
│  │ 10ms     │    │ 1/sec    │    │ 1/sec    │    │ 30sec    │         │
│  └──────────┘    └──────────┘    └──────────┘    └──────────┘         │
│                                                                         │
│  ┌──────────┐    ┌──────────┐    ┌──────────┐                         │
│  │ Stage 9  │───→│ Stage 10 │───→│ Stage 11 │                         │
│  │ Order    │    │ Dynamic  │    │ Post‑    │                         │
│  │ Recon    │    │ P&L      │    │ Cleanup  │                         │
│  │ 5min     │    │ 30min    │    │ 19:30    │                         │
│  └──────────┘    └──────────┘    └──────────┘                         │
│                                                                         │
└─────────────────────────────────────────────────────────────────────────┘
```

**Stage Descriptions**:

| Stage | Name | Execution Class | Schedule |
|-------|------|-----------------|----------|
| 1 | Market Data Acquisition | `QuotationServiceTask` | Every 1 second |
| 2 | Market Data Filtering | `MarketDataHandler` | Disruptor event‑driven |
| 3 | Strategy Evaluation & Order Trigger | `InvestPlanHandler` | Disruptor event‑driven |
| 4 | Trade Order Generation | `TradeOrderTask` | Every 5 milliseconds |
| 5 | Exchange Submission | `TradeServiceTask` | Every 10 milliseconds |
| 6 | Order Status Tracking | `TradeServiceTask` | Every 1 second |
| 7 | Fill Monitoring | `TradeServiceTask` | Every 1 second |
| 8 | Cancellation & Retry | `TradeServiceTask` | Every 30 seconds |
| 9 | Investment Order Reconciliation | `TradeOrderTask` | Every 5 minutes |
| 10 | Dynamic P&L Update | `TradeOrderTask` | Every 30 minutes |
| 11 | Post‑Cleanup | `TradeOrderTask` + `InvestPlanTask` | Scheduled (19:15‑19:39) |


## 📁 Module Structure

```
tsquant/
├── tsquant-base/                    # Foundation layer
│   ├── tsquant-base-model/          # Data models (Entity/VO)
│   ├── tsquant-base-core/           # Core enums, constants, utilities
│   ├── tsquant-base-rule/           # Strategy rule engine (Gann, etc.)
│   ├── tsquant-base-data/           # Market data processing (K‑line calculation, multi‑source)
│   ├── tsquant-base-util/           # Utilities (backtest engine, TA‑Lib wrapper, trading tools)
│   ├── tsquant-base-ctp/            # CTP futures API wrapper
│   ├── tsquant-base-tqsdk/          # Tianqin quant SDK integration
│   ├── tsquant-base-security/       # Security & authentication
│   └── tsquant-base-api/            # External API interfaces
├── tsquant-client/                  # Client application layer
│   ├── tsquant-client-gateway/      # Gateway service (API routing, local gateway)
│   ├── tsquant-client-system/       # System management (users, permissions, dictionaries, monitoring)
│   ├── tsquant-client-invest/       # Investment trading core (strategy execution, backtest, reporting)
│   ├── tsquant-client-ui/           # PC frontend (Vue3 + ElementPlus)
│   ├── tsquant-client-base/         # Client base module
│   ├── tsquant-client-local/        # Third‑party trading interface integration
│   └── tsquant-client-vip/          # VIP quantitative analysis service (WeChat public account)
├── docs/                            # Theory documentation (Gann theory, trading system)
├── sql/                             # Database scripts
├── python/                          # Python helper scripts
├── sh/                              # Core service start/stop scripts
├── data/                            # Runtime data directory
└── uml/                             # UML design diagrams
```


## 📊 Data Models

### Core Business Entities

| Entity | Description |
|--------|-------------|
| `User` | User information |
| `Broker` | Brokerage institution |
| `Account` | Trading account |
| `InvestPlan` | Investment plan |
| `InvestStrategy` | Investment strategy |
| `InvestSolution` | Investment solution (portfolio of plans) |
| `Order` | Order/entrustment |
| `Holding` | Real‑time position |
| `HoldingLog` | Position change log |
| `TradeLog` | Trade record |
| `Condition` | Conditional order (stop‑loss, take‑profit) |
| `Kline` / `KlineImage` | K‑line data / K‑line image (technical indicators) |
| `Quotation` | Real‑time quote |
| `Future` / `Stock` / `Fund` | Basic instrument information |
| `InvestReport` / `VarietyReport` | Investment / instrument‑specific reports |

### Key Fields of KlineImage

KlineImage is the core data structure, computed from raw K‑line data:

- **Daily MAs:** MA5, MA10, MA20, MA30, MA40, MA60 (including current and previous 1‑4 days)
- **Weekly MAs:** WMA5, WMA10, WMA20 (including previous 1‑2 weeks)
- **Monthly MAs:** MMA5, MMA10, MMA20
- **Key levels:** Hh3/Ll3 (3‑day high/low), Hh5/Ll5 (5‑day high/low), Hh6/Ll6 (6‑day high/low), historical highest/lowest
- **Trend state:** main direction (up/down/topping/bottoming)
- **Volatility:** daily range, 12‑day average range, volatility value
- **Risk/reward indicators:** buy/sell win rates, max loss value (**N**)
- **Extreme levels:** last 24‑day high/low, previous 12‑day high/low

**N‑value (price change corresponding to max loss) calculation:**
```
lossProfitRatio (max profit loss ratio) = 10% (fixed, corresponding to "never risk more than 10% of capital")
maxLossRatio (max price loss ratio) = lossProfitRatio ÷ (contract multiplier × capital usage)
N = entry price × maxLossRatio
```

**Example (coking coal futures):**
- Contract multiplier: 60 tons/lot
- Capital usage (maxUsedRatio): 10%
- Entry price: 1300 RMB/ton
- `actual leverage = 60 × 10% = 6`
- `maxLossRatio = 10% ÷ 6 = 1.6667%`
- `N = 1300 × 1.6667% ≈ 21.67 points`
- That is, when price drops about 21.67 points, the loss reaches 10% of principal, triggering a stop‑loss.


## ⚡ Quick Start

### Requirements

- JDK 17+
- Maven 3.8+
- MariaDB / MySQL 8.0+
- Redis 6.0+
- Node.js 16+ (for frontend build)

### Database Initialization

```bash
# Create databases
mysql -u root -p < sql/tssystem.sql
mysql -u root -p < sql/tsclient.sql
# Import latest system data (choose the most recent file)
mysql -u root -p < sql/db_data/sys_export_YYYYMMDDHHMI.sql
```

### Backend Startup

```bash
# Build the project
mvn clean install -DskipTests

# Start gateway service
cd tsquant-client/tsquant-client-gateway
mvn spring-boot:run

# Start system management service
cd tsquant-client/tsquant-client-system
mvn spring-boot:run

# Start investment trading service
cd tsquant-client/tsquant-client-invest
mvn spring-boot:run
```

### Frontend Startup

```bash
cd tsquant-client/tsquant-client-ui
npm install
npm run dev
```


## 🎯 Demo Environment

We provide an online demo environment for you to quickly experience the system features.

| Item | Information |
|------|-------------|
| **Demo URL** | https://47.113.224.221:8001/ |
| **Demo Account** | demo1 (read‑only) |
| **Demo Password** | 123456 |

> **Note**: The demo account has read‑only permissions and can only view system features, not perform trading operations.

---

## 🔌 Data Source Access

The system supports the following data sources:

| Source | Type | Description |
|--------|------|-------------|
| CTP | Real‑time / Trading | Futures real‑time data and trading |
| TqSdk | Simulation / Live | Tianqin quant SDK |
| EastMoney | Historical | Stock/futures historical K‑line |
| Sina Finance | Real‑time | Stock real‑time quotes |
| Sohu Finance | Historical | Stock historical K‑line |
| AKShare | Historical | Python financial data interface |


## 📄 License

TsQuant is distributed under a **Dual Licensing** model:

1. **Open Source License**:
   This project is default licensed under the **GNU Affero General Public License v3.0 (AGPL-3.0)**.
   - Suitable for personal learning, open‑source projects, and commercial use that complies with AGPL-3.0 terms.
   - For full terms, see the [LICENSE](LICENSE) file in the project root.

2. **Commercial License**:
   If you need to integrate TsQuant into a proprietary product or service, or if your corporate policies prevent compliance with AGPL-3.0, **you must obtain a Commercial License**.
   - A Commercial License allows closed‑source integration, private modifications, and waives AGPL's "copyleft" open‑source requirements.
   - **How to obtain**: Please email **lebin_zheng@foxmail.com** for inquiries and negotiation.

> **Important Notice**: Any use of TsQuant in closed‑source commercial products without explicit permission is strictly prohibited. For any questions, feel free to contact us via email.


## 🧑‍💻 Technical Support & Services

TsQuant is not only an open‑source quantitative trading system, but also a proven engineering implementation of a tested trading methodology. We provide full‑chain technical support from **strategy research, system deployment, to custom development**, helping proprietary trading teams and institutional firms transform classical theories like Gann's into automated, sustainable profit‑generating trading capabilities.


### 🎯 Quantitative Technical Services

| Service Category | Specific Content | Target Audience |
|------------------|------------------|-----------------|
| **Quantitative strategy custom development** | Tailor‑made strategies based on your logic (Gann, MAs, breakout, grid, etc.), integrated into TsQuant framework with backtesting and live support | Proprietary trading teams |
| **System deployment & operations** | Private deployment of full TsQuant stack (including CTP access, data source configuration, high‑availability architecture), daily maintenance and emergency response | Proprietary trading teams, asset managers |
| **Technical training & enablement** | Systematic training courses: in‑depth Gann theory interpretation, TsQuant framework development, strategy coding and backtesting analysis (online/offline) | Proprietary trading teams, corporate tech departments |
| **AI & large model enablement** | Apply LLMs to sentiment analysis, research report interpretation, intelligent Q&A, etc., to support investment decisions and improve research efficiency | Financial institutions, research teams |
| **System secondary development & integration** | Extend TsQuant's base framework, integrate with internal systems (risk control, OA, finance, etc.) to achieve a full digital closed‑loop | Medium‑to‑large enterprises, brokerages |


### 🏢 Enterprise Digital Services

The author's team has extensive experience in enterprise‑grade software architecture and digital transformation, offering:

| Service Category | Specific Content | Typical Scenarios |
|------------------|------------------|-------------------|
| **Enterprise digital solutions** | Consulting and implementation of digital/intelligent transformation for various industries, **benchmarked against Kingdee Cloud StarHarmony and StarPark industry solutions**, covering full‑cycle delivery from strategic planning to system integration | Traditional enterprise digital transformation, business process optimization, data‑driven decision systems |
| **Software architecture design & consulting** | **High‑concurrency, high‑availability, low‑latency** distributed system design, **microservices** splitting and governance, **Xinchuang** (localization) environment adaptation, **legacy‑new system integration** and upgrade support | Large‑scale platform construction, legacy system modernization, Xinchuang migration, technical debt management |
| **AI & large model technical support** | **AI foundation platform** building, **intelligent Q&A**, **model fine‑tuning**, **Prompt engineering**, **RAG systems**, empowering enterprises with AI‑driven upgrades | Corporate knowledge base, intelligent Q&A, automated report generation, risk model optimization |
| **ERP/MES software suite** | **Secondary development**, **system integration**, and **intelligent retrofitting** of core manufacturing systems: ERP, MES, **PLM**, **WMS**, **QMS**, **APS**; bridging **PLC**, **SCADA** and business layers to achieve a closed‑loop digital workshop | Digital workshop construction for discrete/process manufacturing (equipment, electronics assembly, food processing, etc.) |
| **Quantitative technical support** | **Custom quantitative strategy development**, **live futures/stock API integration** (CTP, TqSdk, broker APIs, etc.), **deployment and operations** full‑stack support | Quant team strategy implementation, live trading system setup |


### 🤝 Flexible Collaboration Models

- **Project‑based custom development:** clearly defined scope, one‑time delivery – suitable for specific strategies or feature modules.
- **Annual technical maintenance:** long‑term service contract including system upgrades, bug fixes, strategy optimization advice, and periodic consulting.
- **Technology equity / joint operation:** for high‑quality strategies or deep partners, explore equity or profit‑sharing models.
- **Training services:** per‑person or per‑session pricing, customisable course outlines.

> 💡 **First consultation is free:** Whether you are new to quantitative trading, have existing strategies, or face challenges in enterprise digital transformation, we offer one free initial needs assessment and technical feasibility analysis to help you clarify your direction.


### 📞 Contact & Consultation

- **Project homepage:** https://gitee.com/liebin/tsquant
- **Issue reporting:** Submit bugs or suggestions via Gitee Issues
- **Author email:** lebin_zheng@foxmail.com (please mention "TsQuant" or "Enterprise Digital" in subject)
- **WeChat:** Scan the QR code below to add the author (Mr. Zheng), with note "Quant Cooperation", "Technical Support", or "Digital Consulting" for faster approval.

We commit to responding to technical issues **within 4 hours** during working hours (Mon‑Fri 9:00‑21:00, weekends/holidays by appointment), and providing initial solutions **within 24 hours**.

### 📱 WeChat QR Code

<img src="img/author_qrcode.jpg" alt="Author WeChat QR Code" width="200" />


**Choose TsQuant – empower your investment journey with classic trading theories through modern technology. We look forward to working with you to create steady returns.**