> ## Documentation Index > Fetch the complete documentation index at: https://docs.reportify.cn/llms.txt > Use this file to discover all available pages before exploring further. # 策略回测 > 运行量化策略回测并获取绩效分析 ## 运行策略回测执行策略回测，返回绩效指标和交易记录。 ```bash theme={null} POST /v1/quant/backtest ``` ```bash cURL theme={null} curl -X POST https://api.reportify.cn/v1/quant/backtest \ -H "Authorization: Bearer " \ -H "Content-Type: application/json" \ -d '{ "start_date": "2024-01-01", "end_date": "2025-01-01", "market": "cn", "symbols": ["000001"], "entry_formula": "CROSS(MA(CLOSE, 5), MA(CLOSE, 10))", "exit_formula": "CROSS(MA(CLOSE, 10), MA(CLOSE, 5))", "initial_cash": 100000, "benchmark": { "symbol": "000905", "market": "cn", "stock_type": "index" }, "commission": 0.0003, "position_size": 0.2, "max_positions": 5, "min_volume": 100 }' ``` ```python Python theme={null} import requests response = requests.post( "https://api.reportify.cn/v1/quant/backtest", headers={"Authorization": "Bearer "}, json={ "start_date": "2024-01-01", "end_date": "2025-01-01", "market": "cn", "symbols": ["000001"], "entry_formula": "CROSS(MA(CLOSE, 5), MA(CLOSE, 10))", "exit_formula": "CROSS(MA(CLOSE, 10), MA(CLOSE, 5))", "initial_cash": 100000, "benchmark": { "symbol": "000905", "market": "cn", "stock_type": "index" }, "commission": 0.0003, "position_size": 0.2, "max_positions": 5, "min_volume": 100 } ) print(response.json()) ``` ```typescript TypeScript theme={null} const response = await fetch('https://api.reportify.cn/v1/quant/backtest', { method: 'POST', headers: { 'Authorization': 'Bearer ', 'Content-Type': 'application/json' }, body: JSON.stringify({ start_date: '2024-01-01', end_date: '2025-01-01', market: 'cn', symbols: ['000001'], entry_formula: 'CROSS(MA(CLOSE, 5), MA(CLOSE, 10))', exit_formula: 'CROSS(MA(CLOSE, 10), MA(CLOSE, 5))', initial_cash: 100000, benchmark: { symbol: '000905', market: 'cn', stock_type: 'index' }, commission: 0.0003, position_size: 0.2, max_positions: 5, min_volume: 100 }) }); const data = await response.json(); ``` ### 请求参数回测开始日期，格式：`YYYY-MM-DD` 回测结束日期，格式：`YYYY-MM-DD` 股票市场：`cn`（A股）, `hk`（港股）, `us`（美股）回测股票代码列表。如果不提供，则默认回测当前所选市场（如A股、美股或港股）。当前市场回测时建议配合 `filter_formula` 过滤不符合条件的股票。股票池预筛选公式。在执行每日回测逻辑前，系统会先用此公式对当前市场的股票进行过滤，结果大于 0（即为 True）的股票才会保留在当日的可用股票池中，参与后续的行情数据加载和买卖信号计算。通常用于当前市场范围选股时过滤掉 ST 股、停牌股或不符合基本面要求的股票。 * `NOT(IS_ST())` - 过滤 ST 股票 * `(PE_TTM() > 0) & (PE_TTM() < 30)` - 过滤亏损股且要求 PE 小于 30 * `NOT(IS_ST()) & (ROE() > 10)` - 过滤 ST 股票且要求 ROE 大于 10% 买入/开仓公式，结果大于 0 时触发买入（如不提供则必须提供 `strategy_code`）。支持技术指标与基本面因子。 * `CROSS(MA(CLOSE, 5), MA(CLOSE, 10))` - 均线金叉买入 * `RSI(14) < 30` - RSI 超卖买入 * `CLOSE > BOLL(20, 2).upper` - 突破布林带上轨买入 * `(RSI(14) < 30) & (CLOSE > MA(CLOSE, 20))` - 组合条件 * `(PE_TTM() < 20) & (ROE() > 15)` - 基本面因子选股卖出/平仓公式，结果大于 0 时触发卖出（可选） * `CROSS(MA(CLOSE, 10), MA(CLOSE, 5))` - 均线死叉卖出 * `RSI(14) > 70` - RSI 超买卖出 * `CLOSE < BOLL(20, 2).lower` - 跌破布林带下轨卖出自定义回测策略的 Python 源码代码。若提供，将执行自定义策略而非公式策略。 **注意：** 策略代码必须定义一个名为 `handle_data(context, datas)` 的函数作为回测引擎的入口点。初始资金（元）佣金费率，买卖通用（如 0.0003 表示万三）。若同时设置 `buy_commission` / `sell_commission`，则以后者为准买入手续费率，优先于 `commission`（如 0.0003 表示万三）卖出手续费率，优先于 `commission`（如 0.0013 表示万三佣金 + 千一印花税）单笔最低手续费金额（元），如 5.0 表示每笔至少收 5 元手续费滑点比例（如 0.001 表示千一），买入价上浮、卖出价下浮，模拟真实成交价差单只股票最大仓位比例，例如 0.2 表示单只股票占用总资金的 20%。默认 `null`（不限制）最大持仓股票数量。默认 `null`（不限制）最小买入股数（如A股的 1 手即 100 股）是否在回测结束时自动平仓是否在 T 日信号生成后的 T 日开盘执行交易。默认 `false` 为 T+1 开盘执行预计算因子字典，用于 `strategy_code` 模式下提前计算买卖所需的指标，或在回测中返回额外的值（可选）。可通过 `factors` 接口获取可用因子列表。 ```json theme={null} { "ma5": "MA(CLOSE, 5)", "ma10": "MA(CLOSE, 10)", "rsi": "RSI(14)", "pe": "PE_TTM()", "roe": "ROE()" } ``` 回测对比基准配置。`benchmark` 必须是对象，不能直接传字符串代码。 ```json theme={null} { "symbol": "000905", "market": "cn", "stock_type": "index" } ``` 常见用法： * `{"symbol": "000905", "market": "cn", "stock_type": "index"}` - 中证500 * `{"symbol": "000300", "market": "cn", "stock_type": "index"}` - 沪深300 * `{"symbol": "510500", "market": "cn", "stock_type": "etf"}` - ETF 基准错误示例： * `"000905"` - 错误，接口期望 object，不是 string ### 响应参数回测是否成功初始资金最终资金总收益（元）总收益率（如 0.156 表示 15.6%）最大回撤（如 -0.082 表示 -8.2%）盈利因子（总盈利 / 总亏损）胜率（如 0.65 表示 65%）总交易次数盈利交易次数亏损交易次数交易详情列表 * `id`: 交易 ID * `symbol`: 股票代码 * `type`: 交易类型（`Long` 或 `Short`） * `entry_date`: 开仓日期 * `exit_date`: 平仓日期 * `entry_price`: 开仓价格 * `exit_price`: 平仓价格 * `size`: 交易数量 * `net_pnl`: 净盈亏 * `return_pct`: 收益率百分比 * `cumulative_pnl`: 累计盈亏每日账户净值序列，用于绘制资产走势图。键为日期，值为净值。基准每日净值序列（按初始资金等比例折算），用于与策略净值对比。基准总收益率（如 0.154 表示 15.4%）年化收益率（如 0.15 表示 15%，按 252 交易日折算）夏普比率（年化，无风险利率按 0 计算） Alpha（年化，CAPM Jensen's Alpha） Beta（策略相对基准的系统性风险暴露）最大回撤起始日期（峰值日）最大回撤结束日期（谷值日）日收益率序列（键为日期，值为日收益率小数），用于日收益率柱状图。每日回撤序列（键为日期，值为回撤比例小数），用于回撤阴影图。错误信息，仅当 success 为 false 时非空 ### 响应示例 ```json theme={null} { "success": true, "initial_cash": 100000, "commission": 0.0003, "final_cash": 115600, "total_return": 15600, "total_return_pct": 0.156, "max_drawdown": -0.082, "profit_factor": 2.35, "win_rate": 0.65, "total_trades": 12, "winning_trades": 8, "losing_trades": 4, "trades": [ { "id": 1, "symbol": "000001", "type": "Long", "entry_date": "2024-01-15", "exit_date": "2024-02-20", "entry_price": 11.25, "exit_price": 12.50, "size": 8800, "net_pnl": 10937.3, "return_pct": 0.111, "cumulative_pnl": 10937.3 } ], "portfolio_value": { "2024-01-15": 100000.0, "2024-01-16": 101200.5, "2024-02-20": 110937.3 }, "benchmark_value": { "2024-01-15": 100000.0, "2024-01-16": 100850.1, "2024-02-20": 108430.6 }, "benchmark_return_pct": 0.0843, "annualized_return_pct": 0.172, "sharpe_ratio": 1.18, "alpha": 0.041, "beta": 0.92, "max_drawdown_start": "2024-03-11", "max_drawdown_end": "2024-04-18", "daily_returns": { "2024-01-16": 0.0120, "2024-01-17": -0.0041 }, "drawdown_series": { "2024-03-11": 0.0000, "2024-04-18": 0.0820 } } ``` *** ## 策略公式示例 ### 均线金叉死叉策略 5 日均线上穿 10 日均线时买入，下穿时卖出： ```json theme={null} { "entry_formula": "CROSS(MA(CLOSE, 5), MA(CLOSE, 10))", "exit_formula": "CROSS(MA(CLOSE, 10), MA(CLOSE, 5))", "symbols": ["000001"], "start_date": "2024-01-01", "end_date": "2025-01-01" } ``` ### RSI 超买超卖策略 RSI 低于 30 时买入，高于 70 时卖出： ```json theme={null} { "entry_formula": "RSI(14) < 30", "exit_formula": "RSI(14) > 70", "symbols": ["600519"], "start_date": "2024-01-01", "end_date": "2025-01-01" } ``` ### MACD 金叉死叉策略 MACD DIF 上穿 DEA 时买入，下穿时卖出： ```json theme={null} { "entry_formula": "CROSS(MACD().dif, MACD().dea)", "exit_formula": "CROSS(MACD().dea, MACD().dif)", "symbols": ["000002"], "start_date": "2024-01-01", "end_date": "2025-01-01" } ``` ### 布林带突破策略价格突破布林带上轨时买入，跌破下轨时卖出： ```json theme={null} { "entry_formula": "CLOSE > BOLL(20, 2).upper", "exit_formula": "CLOSE < BOLL(20, 2).lower", "symbols": ["000001"], "start_date": "2024-01-01", "end_date": "2025-01-01" } ``` ### 组合条件策略 RSI 超卖且价格在 20 日均线上方买入，RSI 超买或价格跌破均线卖出： ```json theme={null} { "entry_formula": "(RSI(14) < 30) & (CLOSE > MA(CLOSE, 20))", "exit_formula": "(RSI(14) > 70) | (CLOSE < MA(CLOSE, 20))", "symbols": ["600036"], "start_date": "2024-01-01", "end_date": "2025-01-01", "commission": 0.0003, "position_size": 0.8 } ``` ### 当前市场选股与过滤策略如果不指定 `symbols`，系统将在当前市场（由 `market` 字段决定，默认为A股 `cn`）执行回测。可以利用 `filter_formula` 在当前市场范围内进行过滤筛选，排除不满足基本面或状态要求的股票： ```json theme={null} { "start_date": "2024-01-01", "end_date": "2025-01-01", "filter_formula": "NOT(IS_ST()) & (PE_TTM() < 20) & (ROE() > 15)", "entry_formula": "CROSS(MA(CLOSE, 5), MA(CLOSE, 20))", "exit_formula": "CROSS(MA(CLOSE, 20), MA(CLOSE, 5))", "position_size": 0.1, "max_positions": 10 } ``` ### 带 signal\_factors 和自定义策略的回测使用 `signal_factors` 预计算因子并在自定义策略 `strategy_code` 中调用： ```json theme={null} { "symbols": ["000001"], "start_date": "2024-01-01", "end_date": "2025-01-01", "signal_factors": { "ma5": "MA(CLOSE, 5)", "ma10": "MA(CLOSE, 10)", "rsi": "RSI(14)", "macd_dif": "MACD().dif", "pe": "PE_TTM()" }, "strategy_code": "def handle_data(context, datas):\n for data in datas:\n symbol = data.name\n position = context.portfolio.get_position(symbol)\n if not position:\n if data.ma5 > data.ma10 and data.pe < 20:\n context.order_target_percent(symbol, 0.2)\n elif data.rsi > 70:\n context.order_target_percent(symbol, 0)" } ``` *** ## 参数说明 ### 佣金设置 | 参数 | 值 | 描述 | | ----------------------- | -------- | -------------------- | | `commission` | `0` | 不计算佣金 | | `commission` | `0.0003` | 买卖统一万三（0.03%） | | `buy_commission` | `0.0003` | 买入万三 | | `sell_commission` | `0.0013` | 卖出万三佣金 + 千一印花税（A股推荐） | | `min_commission_amount` | `5` | 每笔最低 5 元手续费 | ### 滑点设置 | 值 | 描述 | | ------- | --------------------------- | | `0` | 不考虑滑点 | | `0.001` | 千一滑点（买入价上浮 0.1%，卖出价下浮 0.1%） | | `0.002` | 千二滑点 | ### 止损设置 | 值 | 描述 | | ------ | ------ | | `0` | 不设止损 | | `0.05` | 5% 止损 | | `0.1` | 10% 止损 | ### 仓位设置 | 值 | 描述 | | ------ | --------------------- | | `0.99` | 使用 99% 资金（预留部分应对价格波动） | | `0.5` | 使用 50% 资金（半仓操作） | | `0.3` | 使用 30% 资金（轻仓试探） | *** ## 上传 Excel 文件进行回测上传包含 OHLCV 数据的 Excel 文件进行回测，无需依赖系统内置数据源，使用自有行情数据执行策略回测。 ```bash theme={null} POST /v1/quant/backtest/upload ``` 该接口使用 `multipart/form-data` 格式上传，不支持 JSON body。 ```bash cURL theme={null} curl -X POST https://api.reportify.cn/v1/quant/backtest/upload \ -H "Authorization: Bearer " \ -F "file=@backtest_data.xlsx" \ -F 'params={"entry_formula": "CROSS(MA(CLOSE, 5), MA(CLOSE, 10))", "exit_formula": "CROSS(MA(CLOSE, 10), MA(CLOSE, 5))", "initial_cash": 100000, "commission": 0.0003}' ``` ```python Python theme={null} import requests response = requests.post( "https://api.reportify.cn/v1/quant/backtest/upload", headers={"Authorization": "Bearer "}, files={"file": open("backtest_data.xlsx", "rb")}, data={ "params": '{"entry_formula": "CROSS(MA(CLOSE, 5), MA(CLOSE, 10))", "exit_formula": "CROSS(MA(CLOSE, 10), MA(CLOSE, 5))", "initial_cash": 100000, "commission": 0.0003}' } ) print(response.json()) ``` ```typescript TypeScript theme={null} const formData = new FormData(); formData.append('file', fileInput.files[0]); formData.append('params', JSON.stringify({ entry_formula: 'CROSS(MA(CLOSE, 5), MA(CLOSE, 10))', exit_formula: 'CROSS(MA(CLOSE, 10), MA(CLOSE, 5))', initial_cash: 100000, commission: 0.0003 })); const response = await fetch('https://api.reportify.cn/v1/quant/backtest/upload', { method: 'POST', headers: { 'Authorization': 'Bearer ' }, body: formData }); const data = await response.json(); ``` ### Excel 文件格式要求 Excel 文件（`.xlsx` 或 `.xls` 格式），包含回测所需的行情数据。 **必须包含的列：** | 列名 | 类型 | 说明 | | ------- | -- | ---- | | `date` | 日期 | 交易日期 | | `open` | 数字 | 开盘价 | | `high` | 数字 | 最高价 | | `low` | 数字 | 最低价 | | `close` | 数字 | 收盘价 | **可选列：** | 列名 | 类型 | 说明 | | -------- | --- | ----------------------------------- | | `symbol` | 字符串 | 股票代码（多标的回测时必须提供，单标的时缺省为 `"UPLOAD"`） | | `volume` | 数字 | 成交量 | | `amount` | 数字 | 成交额 | **自定义字段：** 支持任意英文字段名（仅字母、数字、下划线，不能以数字开头），值为数字类型。例如 `pe`、`market_cap`、`pb_ratio` 等。这些字段可在公式中直接引用。 **中文列名支持：** 系统会自动将常见的中文列名映射为对应的英文列名： | 中文列名 | 映射到 | | -------------------- | -------- | | 日期 / 时间 / 交易日期 / 交易日 | `date` | | 开盘 / 开盘价 | `open` | | 最高 / 最高价 | `high` | | 最低 / 最低价 | `low` | | 收盘 / 收盘价 | `close` | | 成交量 / 交易量 | `volume` | | 成交额 / 交易额 | `amount` | | 代码 / 股票代码 / 证券代码 | `symbol` | 自定义字段列名仍须为 ASCII 字符（英文字母、数字、下划线）。 ### 请求参数 (params) `params` 为表单字段，值为 JSON 字符串，支持以下参数（与标准回测接口一致，但不含 `market`/`symbols`/`filter_formula`/`start_date`/`end_date`）：买入/开仓公式，结果大于 0 时触发买入（如不提供则必须提供 `strategy_code`）卖出/平仓公式，结果大于 0 时触发卖出自定义回测策略的 Python 源码代码，与 `entry_formula` 互斥初始资金（元）佣金费率（如 0.0003 表示万三）是否在回测结束时自动平仓指标与因子字典，用于预计算买卖信号或自定义字段 ```json theme={null} { "ma5": "MA(CLOSE, 5)", "ma10": "MA(CLOSE, 10)", "rsi": "RSI(14)" } ``` 单只股票最大仓位比例最大持仓股票数量最小买入股数 ### 响应参数响应格式与标准回测接口完全一致，参见上方 [响应参数](#响应参数) 章节。 ### Excel 上传回测示例 #### 单标的回测 Excel 文件包含单只股票数据（无需 `symbol` 列）： | date | open | high | low | close | volume | | ---------- | ----- | ----- | ----- | ----- | ------- | | 2024-01-02 | 10.50 | 10.80 | 10.40 | 10.75 | 5000000 | | 2024-01-03 | 10.70 | 10.90 | 10.60 | 10.85 | 4500000 | ```json theme={null} { "entry_formula": "CROSS(MA(CLOSE, 5), MA(CLOSE, 10))", "exit_formula": "CROSS(MA(CLOSE, 10), MA(CLOSE, 5))", "initial_cash": 100000, "commission": 0.0003 } ``` #### 多标的回测 Excel 文件包含多只股票数据（必须有 `symbol` 列）： | date | symbol | open | high | low | close | volume | | ---------- | ------ | ----- | ----- | ----- | ----- | ------- | | 2024-01-02 | 000001 | 10.50 | 10.80 | 10.40 | 10.75 | 5000000 | | 2024-01-02 | 600519 | 1800 | 1815 | 1790 | 1810 | 2000000 | ```json theme={null} { "entry_formula": "RSI(14) < 30", "exit_formula": "RSI(14) > 70", "position_size": 0.3, "max_positions": 2 } ``` #### 带自定义字段的回测 Excel 文件包含自定义基本面字段（如 `pe`、`pb`）： | date | symbol | open | high | low | close | volume | pe | pb | | ---------- | ------ | ----- | ----- | ----- | ----- | ------- | ---- | --- | | 2024-01-02 | 000001 | 10.50 | 10.80 | 10.40 | 10.75 | 5000000 | 15.2 | 1.3 | 可在公式中直接引用自定义字段名： ```json theme={null} { "entry_formula": "(CLOSE > MA(CLOSE, 20)) & (pe < 20)", "exit_formula": "CLOSE < MA(CLOSE, 20)", "initial_cash": 100000 } ``` *** ## 注意事项 * 回测结果仅供参考，历史收益不代表未来表现 * 可通过 `slippage` 参数模拟滑点，`buy_commission` / `sell_commission` 分别设置买卖手续费以更贴近真实交易成本 * 建议使用合理的佣金和止损参数以更接近真实交易 * 如果不设置 `exit_formula`，则只有买入信号，卖出依赖止损或 `auto_close` ## OpenAPI ````yaml POST /v1/quant/backtest openapi: 3.1.0 info: title: Reportify API version: 1.0.0 description: API documentation for Reportify's document management and search services. servers: - url: https://api.reportify.cn description: Production server security: - BearerAuth: [] paths: /v1/quant/backtest: post: tags: - openapi-quant summary: Run strategy backtest description: > Execute strategy backtest with the given parameters. **Variables vs Functions:** - Variables (no parentheses): `CLOSE`, `OPEN`, `HIGH`, `LOW`, `VOLUME`, `AMOUNT` - Functions (with parentheses): `MA(CLOSE, 20)`, `RSI(14)`, `PE()`, `ROE()`, etc. **Input Parameters:** - `start_date`: Backtest start date (required) - `end_date`: Backtest end date (required) - `market`: Stock market (cn, hk, us), default: cn - `symbols`: List of stock codes (optional if filter_formula is provided) - `filter_formula`: Pre-filter formula, e.g., 'NOT(IS_ST)' - `entry_formula`: Buy/entry formula, triggers buy when result > 0 (required if strategy_code is not provided) - `exit_formula`: Sell/exit formula, triggers sell when result > 0 (optional) - `strategy_code`: Custom backtest strategy Python code (optional) - `initial_cash`: Initial capital, default: 100000.0 - `commission`: Commission rate, default: 0.0 - `position_size`: Max position size ratio per stock, default: 0.2 - `max_positions`: Max number of holding stocks, default: 5 - `min_volume`: Minimum trading volume, default: 100 - `auto_close`: Auto close position at end, default: true - `indicator`: Indicator dictionary for custom strategy pre-computation or returning values **Formula Examples:** - `CROSS(MA(CLOSE, 5), MA(CLOSE, 20))` - Golden cross signal - `RSI(14) < 30` - RSI oversold - `MA(CLOSE, 5) > MA(CLOSE, 20)` - State-based uptrend - `CLOSE > REF(CLOSE, 1) * 1.05` - Up more than 5% - `(PE() < 20) & (ROE() > 0.1)` - Fundamental screening **Output:** Returns backtest results including: - Performance metrics (return, drawdown, win rate, etc.) - Trade list with entry/exit details - Daily portfolio values operationId: quant_backtest requestBody: content: application/json: schema: $ref: '#/components/schemas/BacktestInput' required: true responses: '200': description: Successful Response content: application/json: schema: $ref: '#/components/schemas/BacktestOutput' '422': description: Validation Error content: application/json: schema: $ref: '#/components/schemas/HTTPValidationError' security: - BearerAuth: [] components: schemas: BacktestInput: properties: start_date: type: string format: date title: Start Date description: Backtest start date (required) end_date: type: string format: date title: End Date description: Backtest end date (required) market: $ref: '#/components/schemas/StockMarket' description: Stock market (cn, hk, us), default cn default: cn symbols: anyOf: - type: array items: type: string - type: 'null' title: Symbols description: >- List of stock codes. If empty, defaults to full market (must provide filter_formula) filter_formula: anyOf: - type: string - type: 'null' title: Filter Formula description: Pre-filter formula, e.g., 'NOT(IS_ST)' entry_formula: anyOf: - type: string - type: 'null' title: Entry Formula description: Buy/entry formula, triggers buy when result > 0 exit_formula: anyOf: - type: string - type: 'null' title: Exit Formula description: Sell/exit formula, triggers sell when result > 0 (optional) strategy_code: anyOf: - type: string - type: 'null' title: Strategy Code description: Backtest strategy python code initial_cash: type: number title: Initial Cash description: Initial capital, default 100000.0 default: 100000 commission: type: number title: Commission description: Commission rate, default 0.0 default: 0 buy_commission: type: number title: Buy Commission description: >- Buy commission rate, takes priority over commission (e.g., 0.0003 for 0.03%) default: 0 sell_commission: type: number title: Sell Commission description: >- Sell commission rate, takes priority over commission (e.g., 0.0013 for A-share sell including stamp duty) default: 0 min_commission_amount: type: number title: Min Commission Amount description: >- Minimum commission per trade in CNY (e.g., 5.0 means at least 5 yuan per trade) default: 0 slippage: type: number title: Slippage description: Slippage ratio (e.g., 0.001 for 0.1%, buy price up, sell price down) default: 0 auto_close: type: boolean title: Auto Close description: Auto close position at end, default true default: true signal_factors: anyOf: - type: object additionalProperties: true - type: 'null' title: Signal Factors description: Signal factors dictionary for custom strategy pre-computation position_size: type: number title: Position Size description: Max position size ratio per stock, default 0.2 default: 0.2 max_positions: type: integer title: Max Positions description: Max number of holding stocks, default 5 default: 5 min_volume: type: integer title: Min Volume description: Minimum trading volume (e.g., 100 for A-shares), default 100 default: 100 type: object required: - start_date - end_date title: BacktestInput description: Backtest input parameters for strategy execution. BacktestOutput: type: object properties: success: type: boolean title: Success description: Whether backtest completed successfully default: true initial_cash: type: number title: Initial Cash description: Initial capital default: 100000 commission: type: number title: Commission description: Commission rate default: 0 final_cash: type: number title: Final Cash description: Final capital after backtest default: 100000 total_return: type: number title: Total Return description: Total profit/loss amount default: 0 total_return_pct: type: number title: Total Return Pct description: Total return percentage default: 0 max_drawdown: type: number title: Max Drawdown description: Maximum drawdown percentage default: 0 profit_factor: type: number title: Profit Factor description: Gross profit / Gross loss ratio default: 0 win_rate: type: number title: Win Rate description: Winning trades percentage default: 0 total_trades: type: integer title: Total Trades description: Total number of completed trades default: 0 winning_trades: type: integer title: Winning Trades description: Number of profitable trades default: 0 losing_trades: type: integer title: Losing Trades description: Number of losing trades default: 0 trades: type: array title: Trades description: List of trade details items: $ref: '#/components/schemas/TradeItem' default: [] portfolio_value: type: object additionalProperties: type: number title: Portfolio Value description: Daily portfolio values (for equity curve) default: {} benchmark_value: type: object additionalProperties: type: number title: Benchmark Value description: Daily benchmark values scaled to initial capital default: {} benchmark_return_pct: type: number title: Benchmark Return Pct description: Benchmark total return percentage default: 0 sharpe_ratio: type: number title: Sharpe Ratio description: Annualized Sharpe ratio with risk-free rate = 0 default: 0 alpha: type: number title: Alpha description: Annualized CAPM Jensen's Alpha with risk-free rate = 0 default: 0 beta: type: number title: Beta description: Strategy beta relative to benchmark default: 0 max_drawdown_start: anyOf: - type: string - type: 'null' title: Max Drawdown Start description: Start date of maximum drawdown period (peak date) max_drawdown_end: anyOf: - type: string - type: 'null' title: Max Drawdown End description: End date of maximum drawdown period (trough date) daily_returns: type: object additionalProperties: type: number title: Daily Returns description: Daily return series (decimal values) default: {} drawdown_series: type: object additionalProperties: type: number title: Drawdown Series description: Daily drawdown series (positive decimal values) default: {} error_msg: anyOf: - type: string - type: 'null' title: Error Msg description: Error message when success is false title: BacktestOutput description: Backtest result containing performance metrics and trade details. HTTPValidationError: properties: detail: items: $ref: '#/components/schemas/ValidationError' type: array title: Detail type: object title: HTTPValidationError StockMarket: type: string enum: - cn - hk - us - global title: StockMarket description: Stock market identifier TradeItem: type: object required: - id - type - entry_date - exit_date - entry_price - exit_price - size - net_pnl - return_pct - cumulative_pnl properties: id: type: integer title: Id description: Trade ID symbol: anyOf: - type: string - type: 'null' title: Symbol description: Stock code (optional for multi-symbol backtest) type: type: string title: Type description: Trade type, "Long" for long position, "Short" for short position entry_date: type: string title: Entry Date description: Entry date (YYYY-MM-DD) exit_date: type: string title: Exit Date description: Exit date (YYYY-MM-DD) entry_price: type: number title: Entry Price description: Entry price exit_price: type: number title: Exit Price description: Exit price size: type: integer title: Size description: Trade size (number of shares) net_pnl: type: number title: Net Pnl description: Net profit/loss return_pct: type: number title: Return Pct description: Return percentage cumulative_pnl: type: number title: Cumulative Pnl description: Cumulative profit/loss after this trade title: TradeItem description: Single trade details from entry to exit. ValidationError: properties: loc: items: anyOf: - type: string - type: integer type: array title: Location msg: type: string title: Message type: type: string title: Error Type type: object required: - loc - msg - type title: ValidationError securitySchemes: BearerAuth: type: http scheme: bearer bearerFormat: JWT description: Enter your Bearer token ````