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GitHub a7b14d3388 release: v1.20.12 — ex tick --date 修复（#56）：接受 YYYYMMDD 整数，对齐 A 股日期语义 2026-08-28 22:41:24 +08:00
GitHub 05db452cc0 release: v1.20.11 — 资金流口径标注（#55）：聚合逐笔成交额分档，实质为主动买卖总失衡 2026-08-28 20:14:41 +08:00
GitHub 1b7d8a5fff docs(client): 资金流口径标注——0x0fb5 逐笔为聚合记录、按成交额分档，与东财主力净额不可比（issue #55） 2026-08-28 20:14:41 +08:00
GitHub 31599a6e13 release: v1.20.10 — 板块列表涨速恒 0 修复（#53）：暴露 sort_column 排序键 2026-08-26 15:21:53 +08:00
GitHub fd53ec4c90 fix(mac): 板块列表涨速恒 0——值槽实为排序键列值，暴露 sort_column（issue #53） 
抓包+对值锚定确认：0x1231 响应中 price 与 pre_close 之间的 float 是
"当前排序列的值"（板块与领涨股各一份），并非固定涨速；此前硬编码
sort_column=0（涨跌幅，仅排序键、值槽恒 0），故该列永远全 0。

排序列映射（实测）：0=涨跌幅(值槽恒0) 1=涨速 2=3日 3=20日 4=60日
5=年初至今 6=5日 7=10日。

- 新增 BoardSortColumn 枚举并公开导出；get_board_list（sync/async）
  新增 sort_column 参数，取涨速传 SPEED，默认涨跌幅排序行为不变
- BoardInfo 字段更名 rise_speed→sort_value、symbol_rise_speed→
  symbol_sort_value（旧名语义错误且恒 0，属破坏性更名）
- Web /board-mac/list 新增 sort_column 参数；CLI board-list 新增 --sort
- 新增 9 个测试；README 示例更新
 2026-08-26 15:21:35 +08:00
GitHub 8c35a864e8 release: v1.20.9 — 历史资金流修复（#52）：当日主力净额盘中可取 + main_net_inflow 列 2026-08-26 15:01:50 +08:00
GitHub 574ffdd2a4 fix(client): 历史资金流当日行全零 + 主力净额列缺失（issue #52） 
三个根因（全部实测核实）：
1. Category 22 直连接口为虚构协议——52 台已知服务器中 46 台可达的
   全部仅回 2 字节空包，从未成功过；移除死代码与臆造解析格式。
2. 历史逐笔接口当日数据要收盘清算后才有，日 K 盘中已含当日 bar，
   故 start=0 的最新一行恒为全 0——当日 bar 改走当日实时逐笔接口。
3. main_net_inflow 此前仅为 dataclass property，asdict 静默丢弃，
   返回 DataFrame 无主力净额列——新增 _fund_flow_df_with_net 物化
   （history 紧随 date 列、当日快照放首列）。

sync + async 双客户端同步修改；更新示例与三份文档；重写/新增回归
测试（当日实时逐笔路径、主力净额列断言）。
 2026-08-26 15:00:53 +08:00
GitHub 7c9e19de93 release: v1.20.8 — 信号雷达：一键扫描全部已保存策略买卖信号 2026-08-21 16:57:16 +08:00
GitHub 9336273f17 feat(web): 信号雷达——一键扫描全部已保存策略的最近买卖信号 
新增导航页 /signals：把策略库 single/portfolio/multi 策略统一展开成
"策略×标的"子任务，按标的去重取最近 800 根 K 线，用与回测引擎同口径的
逐 bar 信号流程（含仓位跟踪）判断最近 N 根（窗口 1/3/5/10 可选，默认 5）
的买/卖信号，汇总卡片 + 筛选 tab + 明细表展示；上次结果缓存 localStorage。

- 后端 signal_scan.py（展开/去重取数/信号评估/汇总）+ POST /backtest/signal-scan/run/async
- 只扫信号不重跑回测，不改写策略库业绩快照；单行失败（未知策略/停牌/参数非法）不中断整批
- normalize_symbol 按代码段纠正历史错标市场前缀（与前端 detectMarket 同规则）
- 新增 20 个单测（含与回测引擎成交序列一致性对照），全套 1030 个单测通过
 2026-08-21 16:57:12 +08:00
GitHub 67a5e1d08a release: v1.20.7 — /bars MIN_1 时间修复（#49）+ 寻优参数语义约束（#39）+ 依赖安全升级 2026-08-19 19:06:59 +08:00
GitHub 1d3d45828d style: ruff format 调整新增测试换行 2026-08-19 19:00:42 +08:00
GitHub 3180ab3002 fix(backtest): 策略参数加跨语义约束，杜绝寻优选出快慢倒挂组合（issue #39） 
寻优器网格探索不区分语义：ma_cross 的 fast∈[5..60] × slow∈[10..250]
笛卡尔积包含 {"fast":30,"slow":20} 这类倒挂组合，倒挂的双均线交叉
本质是反向策略，回测成绩可能反而突出，从而被选为"最优参数"展示
（即 issue #39 截图中 {"fast":30,"slow":20} 的来源）。presets.py 的
注释"快线<慢线才有意义；去重无效组合"早已写下意图但从未实现。

根因是参数校验只有单参数 min/max，缺跨参数语义约束：

- ParametrizedStrategy 新增 param_constraints 类属性 [(a,b), ...]
  表示要求 a<b，在 __init__ 解析后统一校验，报错带中文标签；
  语义约束不受 skip_bounds 影响（寻优跳过的只是数值边界）
- 7 个策略声明约束：ma_cross/ema_cross（fast<slow）、macd
  （short<long）、triple_ma（short<mid<long）、rsi_reversal/cci/
  wr_reversal（oversold<overbought）
- 寻优器 build 阶段的 ValueError 降为 info 级跳过（无堆栈噪音），
  回测异常仍走 warning；预设网格 36 组合 → 有效 25 个
- 新增 10 个回归测试（旧代码全失败、新代码全通过）
 2026-08-19 18:55:48 +08:00
GitHub fc63873717 style: 拆行修复 ruff E501（test_web_api.py 超长行） 2026-08-19 18:22:49 +08:00
GitHub bcaee1404d fix(web): /bars MIN_1 被误判为日线，datetime 归一化为 date 00:00:00（issue #49） 
KlineCategory 枚举值不按周期长短排序（MIN_1=7、MIN_3=8 均大于 DAY=4），
/bars 的 MAC 路径用 int(cat) >= int(KlineCategory.DAY) 判定"日线及以上"，
把 1 分钟线误判为日线，_normalize_mac_df 因此将 datetime 截断为 00:00:00
并把列名改为 date。回退 TdxClient 路径与 MAC symbol_bar 均为显式判定，
仅此一处用整数比较，故只有 MAC 路径复现。

改为 _is_daily_plus() 查表判定（复用 _df._CATEGORY_MINUTES，与回退路径
同一判定源），保证两条路径 date/datetime 语义一致。新增表驱动单测 +
端点级回归测试（假 MAC 客户端，在未修复代码上失败、修复后通过）。
 2026-08-19 18:19:07 +08:00
GitHub 01a9823ed4 fix(web): 升级 postcss/nanoid 修复 Dependabot 安全告警（alerts #2 #3 #5） 
- postcss 8.5.16 -> 8.5.26：修复路径遍历读取任意 .map 文件（GHSA 高危）及后续不完整修复
- nanoid 3.3.15 -> 3.3.18：修复非安全生成器负数 size 死循环（高危）

均为 vite / @vue/compiler-sfc 的 semver 兼容间接依赖，仅更新 lockfile；
npm run build 验证通过。
 2026-08-14 17:30:13 +08:00
GitHub 5a3ad15477 feat(web): /bars 迁移到 MacClient + 支持复权（issue #43） 
Web 获取 K 线此前用 AsyncTdxClient.get_security_bars（标准协议不支持复权），
导致 REST API 无法取前复权/后复权数据。将 /bars（个股 K 线）迁移到
AsyncMacClient.get_stock_kline（MAC 协议，支持 NONE/QFQ/HFQ + QFQ 负价兜底），
保持旧输出契约不变（日线 date 列、分钟线 datetime 列、OHLC 顺序、无 float_shares），
新增 adjust 参数（默认 QFQ），MAC 主机不可用时自动回退标准 TdxClient。

⚠️ 半破坏性变更：/bars 默认复权从"不复权"改为 QFQ（前复权）。老调用方若需
不复权请显式传 ?adjust=NONE。输出 DataFrame 列名/顺序/字段与旧版完全一致
（_normalize_mac_df 规整），仅价格数值因复权变化。

改动：
- bars.py：/bars 改走 mac_client.get_stock_kline(adjust=...)，MAC 不可用回退
  get_security_bars（无复权 + warning）；新增 _normalize_mac_df 规整输出契约；
  新增 adjust 查询参数（默认 QFQ）。
- convert.py：period_times_from_category（KlineCategory→Period 映射，显式处理
  YEAR 9→YEARLY 11、SEASON→QUARTERLY）+ adjust_from_str。
- deps.py：get_mac_client_optional（未连接返回 None，供回退判断）。
- schemas.py：AdjustEnum（OpenAPI 文档用）。

测试：新增 7 个（period_times 映射全表 + 不可映射值、adjust 转换、_normalize_mac_df
日线/分钟线/空 df）。全套 996 passed；ruff format/check + mypy 改动文件零错误。

不在本次范围：/bars/index（指数 K 线，MAC 另一套接口）、/minute、/transaction*
（MacClient tick_chart 语义不同，暂不迁移）。
 2026-08-05 16:37:10 +08:00
GitHub 60bd0586f9 style(tests): ruff format 修复 patch.object 参数换行（CI ruff format --check 失败） 2026-08-05 15:58:00 +08:00
GitHub 0490f67a16 fix(client): get_history_fund_flow 加空数据故障转移（issue #41） 
用户反馈 get_history_fund_flow(SH, "600519") 返回空 DataFrame，日志显示
"K线响应为空（声称 800 条但首条即解析失败...）"。排查定位：当前 host 对
常见标的也返回 ret_count 撒谎的空 body，但资金流兼容回退路径（直连空 →
拉 K 线 + 历史逐笔重算）未接入 v1.20.4 的空数据故障转移，"服务器回包正常
但内容是假的空" 既非 TdxConnectionError 也不触发换台，用户卡在坏服务器上。

修复：get_history_fund_flow（sync+async）当前 host 直连与 K 线回退均空时，
按延迟顺序逐台实测找首台返回有效数据的服务器（与 get_security_bars/
get_index_bars 同源逻辑）。因资金流获取涉及多命令，无法用单 cmd 复用泛化版
_find_host_returning_data，故内联 _fund_flow_failover：每台候选上跑完整
_fetch_fund_flow_records（原直连+K线回退逻辑抽出成独立方法），返回首台非空
结果。全空返回空 DataFrame（不 raise，区分"真无历史数据"与"服务器缺数据"）。

测试：新增 6 个（4 sync + 2 async）。全套 989 passed；ruff/mypy 改动文件零错误。
 2026-08-05 15:53:49 +08:00
GitHub a8c035010e style(tests): ruff format 修复尾随空行（CI ruff format --check 失败） 2026-07-10 15:17:00 +08:00
GitHub d84a08b7f2 fix(backtest): v1.20.3 修复回测绩效统计两个 bug（issues #30 #31） 
#31: RebalanceEngine 缺失价格导致净值假崩塌
  已持仓标的当日缺 K 线（停牌/日历错位）时 prices.get(code,0)=0，
  持仓市值记 0 → 净值单日暴跌（159915 在 20210208 缺一天，持仓 ~93%，
  净值 1.1M→91,845，全期最大回撤 -92%）。
  修复：last_known_price forward-fill，缺失日沿用最近已知收盘价。
  附带：_compute_performance 最大回撤改正值口径（与 BacktestEngine 一致）。
  验证：真实 ETF 数据 max_drawdown 24.01%（backtrader 基准 27%），
  total_return 220.56% 不变。

#30: PortfolioTracker 交易静默漏单
  apply_trades 用 trade.datetime 作 dict key、df["datetime"].to_numpy()[i]
  查找；两端类型不一致（int vs datetime64）时永不命中，交易被静默丢弃，
  净值恒定（total_return=0 但 trades 表有 PnL）。
  修复：改为按"位置索引"匹配（归一化 datetime 后查位置），类型无关。
  验证：int-trade+datetime64-df 修复前净值=100000（恒定），修复后=100289。

测试：新增 4 回归测试（未修复代码上均失败，修复后通过）；
全套 936 passed；mypy 改动文件零错误；ruff 全绿。
 2026-07-10 15:12:47 +08:00
GitHub 06be298c92 ci(publish): 暂时关闭 attestations 规避 OIDC 503 故障 
GitHub OIDC → sigstore 服务连续 503 overflow（v1.20.2 两次 publish 失败），
非配置问题（v1.20.1 能发成功证明 trusted publishing 配置正确）。
attestations 是可选签名，关闭后上传正常进行；待服务稳定后改回 true。
 2026-07-09 22:12:20 +08:00
GitHub bc0ea064ba chore: retrigger CI (Actions queue stuck 20min) 2026-07-09 20:55:16 +08:00
GitHub a67e5588d0 fix(types): v1.20.2 修复 v1.20.1 引入的 CI mypy 失败 
v1.20.1 把 BacktestResult.performance 扩大为 dict[str, float | str]
（为塞 diagnostic_warning 字符串），破坏 6 处下游消费方类型契约，
CI mypy job 转红。重构为更干净的设计：

- 诊断信息走独立的 BacktestResult.diagnostic 字段（performance.py
  PerformanceAnalyzer.diagnostic 属性 → engine 透出 → to_dict 含该字段
  → CLI 显示），performance 字典回归 dict[str, float]（保留别名键）。
- optimizer.py 补 npt.NDArray 标注，消除 3 个既有 ndarray type-arg 错误。

测试：932 passed；mypy backtest/+portfolio/ 零错误；ruff 全绿。
 2026-07-09 20:34:23 +08:00
GitHub 00b8c6374a fix(backtest): v1.20.1 修复回测引擎 3 个 bug（issues #22 #23 #25） 
排查发现用户反馈的"回测统计数据缺失/异常"并非服务器连接问题，
而是回测引擎与组合优化器自身的代码缺陷：

#23: 首根 bar 访问 close[-1] 崩溃
  _SeriesAccessor 负向越界改返回 NaN（不抛 IndexError）；
  BacktestEngine 新增 warmup_bars 参数跳过指标预热期。

#25-A: FactorWeightedOptimizer 权重坍缩
  n_stocks=2 且得分接近时，减最小值把低分标的权重压到 ~6e-8，
  等于单股满仓、n_stocks 被无视，进而出现持仓1只/-99.98%回撤。
  新增 _apply_weight_floor 权重下限保证入选标的都有实质权重。

#25-B: RebalanceEngine total_trades 统计错误
  total_trades = len(equity_curve)（天数）改为 len(trades_df)（真实笔数）。

#22: 绩效别名键 + 数据异常诊断
  performance dict 新增 sharpe_ratio/start_cash/end_value 别名键；
  资金曲线异常时返回 diagnostic_warning 而非静默全 0，CLI 显示提示。

文档：README 加入回测手册导航；backtest_usage.md 补充 warmup 说明。
测试：新增 6 个回归测试，更新 3 个；932 passed。
 2026-07-09 20:16:12 +08:00
GitHub 052119e6ae feat(backtest): v4.2 新增 FSL 分水岭指标策略（单标的/组合/寻优） 
- MyTT.py: 新增 FSL(CLOSE, VOL, CAPITAL) 分水岭指标
  - SWL = (EMA(C,5)*7 + EMA(C,10)*3) / 10
  - SWS = DMA(EMA(C,12), MAX(1, 100*SUM(VOL,5)/(3*CAPITAL)))
    MIN(A,1.0) 模拟通达信 DMA(X,A) 内部钳制 A<=1 的语义
- MyTT.pyi: 补 FSL 类型 stub（CI mypy 用 .pyi 校验）
- strategies/builtin.py: 注册 FslStrategy（SWL/SWS 金叉死叉）
  capital 作为 Param 暴露流通股本输入
- strategies/presets.py: fsl 寻优网格（4 档 capital）
- tests: 注册表断言加 fsl，阈值 18→19
 2026-07-09 18:42:00 +08:00
GitHub d0d65d64b8 feat: v1.20.0 服务器失败自动 ping 切换（无需手动 easy-tdx ping） 
服务器连不上或返回空数据时，自动测速切到延迟最低的可用服务器再试，
Python API / CLI / Web API 三入口全部自动生效。

核心改动：
- _reconnect.py 新增 select_best_host_sync/async（连接失败 failover）
  和 find_working_host_sync/async（空数据逐台实测）
- 8 个 client 的 _execute 注入跨主机故障转移（复用 auto_reconnect 开关）
- get_market_stat 空数据时按延迟顺序逐台实测找返回数据的服务器
- 新增 _reconnect/_areconnect helper 收敛重建连接副本
- MacClient failover 用 save_best_mac_host（延续 v1.19.4 不污染 best_host）
- 顺手修复 test_commands_offline 未使用 import（main CI failure 根因）

测试：925 passed（新增 18 个 failover 测试），ruff/mypy 零新增错误。
 2026-07-08 18:07:37 +08:00
GitHub e3e8dd492e fix: K线响应截断容错 + 一键寻优并发默认8进程 
- security_bars: parse_response 遇末尾残缺记录时丢弃并返回前 N-1 条，
  避免 TDX 服务端截断响应导致整页 500（如 000408 count=800 日线）
- OptimizeView: 一键寻优并发默认 8 进程，用户选择持久化到 localStorage

bump version to 1.18.3
 2026-07-06 13:23:37 +08:00
GitHub 9245bb2ce9 chore(tests): 修复 ruff UP038 (isinstance 元组 -> int | float) 
test_web_backtest.py:556 的 isinstance(x, (int, float)) 触发 ruff UP038。
requires-python>=3.10 支持 PEP 604 的 int | float 运行时语法, 转换安全。
该报错会导致 GitHub Actions CI 失败。
 2026-07-03 15:42:24 +08:00
GitHub cc9c1e264d test(tick_charts): 补 partial-day 回归测试覆盖 PR #13 修复 
PR #13 修复了 start_date=None 且最新交易日数据不完整时
tail_offset 越界/读错位的 bug。原 3 个测试构造的都是完整数据
(total = days*page_size)，走 fallback 分支，未覆盖真正的 partial 分支。

新增 test_multi_tick_charts_partial_day: 构造 days=3, page_size=4,
total=6 的 body，验证 tick_counts 分配为 [2,4,0]、尾部元数据在
actual_total 反推的偏移处正确解析。已反向验证(回退旧 tail_offset
公式时该测试立即失败复现 '偏移 239 越界')，非空壳测试。
 2026-07-03 15:42:06 +08:00
GitHub 2067b80958 fix(ci): scipy 1.17 要求 Python>=3.11，CI 跑 3.10 装不上 
requirements-dev.txt 锁定的 scipy==1.17.0 与 pyproject 声明的
requires-python=>=3.10 冲突（scipy 1.16+ 起要求 Python>=3.11），
导致 CI 矩阵里 3.10 的 job（ubuntu + windows）pip install 失败。

修复：
- requirements-dev.txt: scipy 1.17.0 → 1.15.3（支持 >=3.10 的最新 scipy）
- pyproject.toml [dev]/[science]: scipy>=1.10 → >=1.10,<1.16
  （CI 第一步 pip install -e .[dev] 在 3.10 上也会拉到 1.17，加同上界）

附注：仅影响开发/CI 环境，运行时用户（pip install easy-tdx）不受影响。
本地 761 单测 + ruff + coverage(62%) 全过。requirements-dev.txt
头部加注释说明 3.10 兼容约束，防日后再次踩坑。
 2026-07-02 03:53:25 +08:00
GitHub 155328df8b release: v1.16.2 — 三轮审计质量加固（B6.9→A7.9） 
经三轮代码审计后的综合质量加固版本，覆盖协议核心层、数据正确性、
错误处理、测试真实度与可维护性。761 单测全绿（+58），ruff/mypy 全过。

主要修复：
- 离线 .day 写入原子化（fsync + _repair_tail + 读取校验，CQS 守住）
- 回测止损前视偏差（延迟下一根开盘 + 跳空保护）
- VWAP 权重索引 / bar_time fail-fast / 绩效除零保护
- 闭包绑定 / 路径穿越 / naive datetime 跨时区 / ruff UP038

重构：
- 抽 AsyncHeartbeatMixin 收敛 4 处心跳副本（12→1）
- 统一 _RETRY_DELAYS 退避序列 / scanner 失败可观测性

新增 5 个测试文件 + 公共 API 类型契约，CI 加 Windows 矩阵 +
trusted publishing 签名 + 锁文件。

详见 CHANGELOG.md
 2026-07-02 03:37:37 +08:00
GitHub bc83ffa4ac fix(tick_charts): 多日分时图 minutes>=1440 报 ValueError (Issue #10) 2026-07-01 16:22:57 +08:00
GitHub 615994ad72 feat(kline): 分钟级K线时间戳可选bar_time对齐Tushare (Discussion #7) 
通达信协议用bar开始时间打时间戳（5min线上午最后一根标11:25、下午第一根标13:00；午休11:30-13:00无bar），而Tushare/同花顺/聚宽用bar结束时间（标11:30/13:05）。新增bar_time参数让用户一键切换，避免自行+5分钟偏移。

- 全部3条K线路径覆盖：A股get_security_bars/get_index_bars、扩展行情get_instrument_bars、MAC get_stock_kline（含同步+异步、get_stock_kline_with_indicators）

- CLI kline新增--bar-time {start,end}选项；Web /bars、/bars/index新增bar_time查询参数

- bar_time=start（默认）保持完全向后兼容；bar_time=end仅对分钟级周期（1/5/15/30/60min）生效，自动按周期时长右移并处理跨小时/跨日边界

- 协议解码层零改动，偏移作为纯展示语义在client层后处理，单一工具函数_apply_bar_time_align_df/_apply_bar_time_align_bars复用于全部路径

- 新增27个单元测试（test_codec_datetime.py偏移逻辑 + test_kline_bar_time.py三路径覆盖），全量700单测通过

- bump 版本号至 1.16.0
 2026-06-30 15:02:27 +08:00
GitHub db83e7505d fix(security_quotes): 修复 ETF/指数实时行情价格被放大10倍 (Issue #8) 2026-06-29 22:15:28 +08:00
GitHubandClaude c54071e85e release: v1.14.1 — 高级回测 ExecutionModel 路径 3 个真实数据兼容 Bug 修复 
- datetime 类型分歧（致命）：Trade.datetime 转 int 与 PortfolioTracker 的 Timestamp key 失配，TWAP/VWAP/Limit 路径交易全部静默丢失、权益曲线恒定、收益归零
- volume 列名分歧：回测认 volume 而真实行情为 vol，滑点 volume 恒 0 退化百分比模式，VWAP 退化为等权
- date/datetime 列名分歧：日线返回 date 列引擎要 datetime，run() 入口由 date 派生下游无感兼容
新增 3 个回归测试（均红灯验证）。650 单测通过，backtest 模块 ruff + mypy strict 清洁。

Co-Authored-By: Claude <noreply@anthropic.com>
 2026-06-15 20:50:49 +08:00
GitHubandClaude a6ed0eac16 docs: add quantitative guide, update README + CHANGELOG, bump v1.11.1 
Co-Authored-By: Claude <noreply@anthropic.com>
 2026-06-12 22:12:19 +08:00
GitHubandClaude bfefadf70b feat(backtest): v1.15.0 — attribution analysis 
- AttributionReport dataclass with Brinson/factor/cost fields
- AttributionAnalyzer with 3 attribution modes:
  - Cost attribution (commission/slippage/stamp tax breakdown)
  - Brinson attribution (allocation + selection + interaction)
  - Factor attribution (factor contribution + specific return)
- Priority: factor > Brinson > cost in full_report()
- 556 tests passing (12 new)

Co-Authored-By: Claude <noreply@anthropic.com>
 2026-06-12 21:11:33 +08:00
GitHubandClaude 2eeb7f9806 chore: bump version to v1.15.0 
Co-Authored-By: Claude <noreply@anthropic.com>
 2026-06-12 21:11:23 +08:00
GitHubandClaude 06f2e1f1a2 feat(backtest): add AttributionAnalyzer with Brinson, factor, cost attribution 
Co-Authored-By: Claude <noreply@anthropic.com>
 2026-06-12 21:10:50 +08:00
GitHubandClaude 8c2c204002 feat(backtest): v1.14.0 — pluggable slippage models + execution simulation 
- SlippageModel ABC with 4 built-in models (Fixed, Percent, SquareRoot, Volume)
- ExecutionModel ABC with 4 built-in models (Immediate, TWAP, VWAP, Limit)
- OrderSimulator integration with SlippageModel
- BacktestEngine integration with SlippageModel + ExecutionModel
- Full backward compatibility (all existing code unchanged)
- 544 tests passing (46 new)

Co-Authored-By: Claude <noreply@anthropic.com>
 2026-06-12 21:06:15 +08:00
GitHubandClaude 8c4c4a6629 chore: bump version to v1.14.0 
Co-Authored-By: Claude <noreply@anthropic.com>
 2026-06-12 21:05:46 +08:00
GitHub 0945e47990 feat(backtest): integrate SlippageModel + ExecutionModel into BacktestEngine 2026-06-12 21:04:24 +08:00
GitHub d18af98855 feat(backtest): add LimitExecution 2026-06-12 20:59:59 +08:00
GitHub fe68d9da95 feat(backtest): add TWAPExecution + VWAPExecution 2026-06-12 20:56:57 +08:00
GitHub 0772666be3 feat(backtest): add ExecutionModel ABC + ImmediateExecution 2026-06-12 20:53:07 +08:00
GitHub 6414c2cc11 feat(backtest): integrate SlippageModel into OrderSimulator 2026-06-12 20:50:42 +08:00
GitHub d081eeb265 feat(backtest): add SquareRootSlippage + VolumeSlippage 2026-06-12 20:47:03 +08:00
GitHub 4098af02bf feat(backtest): add SlippageModel ABC + FixedSlippage + PercentSlippage 2026-06-12 20:44:28 +08:00
GitHub b7b72b10d1 feat(portfolio): add optimizer, risk model, rebalance engine, CLI pfactor command, bump v1.13.0 2026-06-12 20:25:50 +08:00
GitHubandClaude e6a69d51e4 feat(portfolio): add optimizer, risk model, and rebalance engine 
- WeightOptimizer base class with registry (equal, factor_weighted, risk_parity, mean_variance)
- RiskModel with shrinkage covariance estimation and portfolio risk metrics
- RebalanceEngine for multi-period backtesting with commission/slippage
- 20 unit tests covering all components

Co-Authored-By: Claude <noreply@anthropic.com>
 2026-06-12 20:22:31 +08:00
GitHub 6b6b7c66a0 docs: add v1.13.0 portfolio management implementation plan 2026-06-12 20:17:43 +08:00
GitHub 303964ea67 feat(factor): add analysis/transform exports, CLI analyze command, bump v1.12.0 2026-06-12 20:11:28 +08:00
GitHub 9d7bf84d5d feat(factor): add FactorAnalyzer with IC/quantile/turnover/decay analysis 2026-06-12 20:09:08 +08:00
GitHub c6f2580b73 feat(factor): add factor preprocessing pipeline (winsorize/zscore/rank/fill/orthogonalize) 2026-06-12 20:08:10 +08:00
GitHub 799a4da428 docs: add v1.12.0 factor analysis implementation plan 2026-06-12 20:05:24 +08:00
GitHubandClaude d5fa572a43 style: ruff format factor module 
Co-Authored-By: Claude <noreply@anthropic.com>
 2026-06-12 19:58:34 +08:00
GitHubandClaude d35b08ff85 chore: bump version to v1.11.0 
Co-Authored-By: Claude <noreply@anthropic.com>
 2026-06-12 19:58:28 +08:00
GitHubandClaude 54e06009d4 test(factor): add integration tests for FactorEngine with builtins 
Co-Authored-By: Claude <noreply@anthropic.com>
 2026-06-12 19:57:18 +08:00
GitHub f47a6df776 feat(cli): add 'easy-tdx factor list' command 2026-06-12 19:55:40 +08:00
GitHub d9bb37f750 feat(factor): wire up builtin factor auto-registration and export 2026-06-12 19:53:18 +08:00
GitHubandClaude c9be1f85d9 feat(factor): add 19 builtin factors (momentum/volatility/quality/volume/technical/chanlun/value) 
Co-Authored-By: Claude <noreply@anthropic.com>
 2026-06-12 19:50:05 +08:00
GitHubandClaude e766cace73 feat(factor): add FactorEngine with single/cross-section/forward-return compute 
Co-Authored-By: Claude <noreply@anthropic.com>
 2026-06-12 19:47:08 +08:00
GitHub 67d9963f20 feat(factor): add Factor base class and registry 2026-06-12 19:43:54 +08:00
GitHub 7d6607b0cf docs: add v1.11.0 factor engine implementation plan (13 tasks, TDD) 2026-06-12 19:35:16 +08:00
GitHub 64f8a5e8b6 docs: add quantitative factor engine + portfolio management design spec 2026-06-12 19:27:02 +08:00
GitHub e6ed6efcd4 chore: bump version to v1.10.5 + update changelog 2026-06-12 17:19:47 +08:00
GitHubandClaude de2b37e1e3 fix(web): use redoc@2.2.0 standalone bundle (v3 is ESM-only) 
Co-Authored-By: Claude <noreply@anthropic.com>
 2026-06-12 17:06:54 +08:00
GitHubandClaude 79c81cc3b6 fix(web): override redoc endpoint with pinned JS v3.0.0-rc.0 
FastAPI does not accept redoc_js_url as a constructor param — the old
approach silently ignored it, leaving the default redoc@next CDN URL
(which returns 404). Manually register /redoc with get_redoc_html()
using the fixed v3.0.0-rc.0 bundle URL.

Co-Authored-By: Claude <noreply@anthropic.com>
 2026-06-12 17:05:25 +08:00
GitHubandClaude 9848d754a8 fix(web): use redoc@3.0.0-rc.0 bundle 
Co-Authored-By: Claude <noreply@anthropic.com>
 2026-06-12 16:55:21 +08:00
GitHubandClaude 0d673f1972 fix(web): pin ReDoc JS to v2.1.3 (cdn redoc@next returns 404) 
Co-Authored-By: Claude <noreply@anthropic.com>
 2026-06-12 16:54:03 +08:00
GitHubandClaude 46c5d3cc05 fix(web): guard MAC client None + filter _raw bytes from Ex responses 
- get_mac_client() now raises TdxConnectionError (503) when MAC client
  is None, matching get_ex_client() behavior. Previously returned None
  causing AttributeError (500) on all 12 MAC endpoints.
- _records_to_df_resp() filters out internal _raw: bytes fields from
  Ex dataclass models. Previously asdict() included binary protocol
  data that is not JSON-serializable and would cause 500 errors.

Co-Authored-By: Claude <noreply@anthropic.com>
 2026-06-12 16:51:47 +08:00
GitHubandClaude d17895e92b feat(web): full Web API parity with CLI — 18 new endpoints (v1.10.2) 
- Board analysis: list/members/belong/summary/ranking/change-ranking (6)
- Capital flow, symbol info, server info (3)
- Quote list, auction, unusual (3)
- Extended market: bars/quote/minute/transaction (4)
- Technical indicators: list + compute (2)
- Multi-client DI: AsyncMacClient + AsyncExTdxClient lifecycle
- 6 MAC enum converters, DictResponse, ComputeIndicatorsRequest schemas
- Web API endpoints: 22 → 40

Co-Authored-By: Claude <noreply@anthropic.com>
 2026-06-12 16:46:48 +08:00
GitHubandClaude Opus 4.8 fd03e2a334 fix: ruff format compliance for CI 
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-06-11 22:56:23 +08:00
GitHubandClaude Opus 4.8 e290ea3f21 feat: add board N-day change ranking (v1.9.10) 
- Add get_board_change_ranking() to MacClient and AsyncMacClient
- Add 'board-change-ranking' CLI command (--type/--date/--days/--top/--asc)
- Calculate N-day price change from board index K-lines directly
- Default to listing all boards; --top N to truncate
- 12 unit tests covering calculation, edges, sorting

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-06-11 17:40:51 +08:00
GitHubandClaude Opus 4.8 b4f63c85a6 feat: add OBV trend strategy (v1.9.5) 
- New obv_trend.py strategy: OBV energy flow trend following
- Entry: OBV > MAOBV*1.02 buffer + MAOBV 20-bar uptrend confirmed
- Exit: OBV drops below MAOBV
- Tunable params: maobv_period(30), maobv_lookback(20), obv_buffer(0.02)
- Update README changelog and strategy table
- Bump version to 1.9.5

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-06-10 18:53:06 +08:00
GitHubandClaude Opus 4.8 79c6fcee0e fix: remove unused type: ignore comments in analyser.py 
Use 'row_any: Any = row' pattern to avoid arg-type mismatch between
local (pandas-stubs) and CI (bare pandas) environments.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-06-10 15:12:38 +08:00
GitHubandClaude Opus 4.8 4dfd18050e fix: resolve all CI mypy (265→0) and ruff (26→0) errors 
- pyproject.toml: add mypy overrides for pandas/tabulate/matplotlib stubs,
  disable strict checking for vendored MyTT library
- config.py: use cast() for dict[str, Any] .get() returns
- beichi.py: widen _calc_bi_force param to BI | XD, import XD
- backtest/cli.py: split combo/single strategy into separate typed variables
- backtest/combo.py: add bool_array() helper for numpy return types
- chanlun/analyser.py: type ignore for pandas row access, fix dict type arg
- unified.py: change fields param from object to Any
- ex/mac_client.py: add type args to list literals
- cli/cmd_offline.py: wrap int market as Market enum before API call
- cli/cmd_chanlun.py: fix dict type arg
- offline/write_*.py: explicit int() cast for struct.unpack returns
- MyTT.py: fix line-too-long comments, UP038 isinstance syntax
- tests: fix E712 (==False → ~mask), E741 (noqa), F841, import sorting
- ruff format applied across codebase

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-06-10 15:03:41 +08:00
GitHubandClaude Opus 4.8 7f1bc645c2 release: v1.8.2 - 5 new strategies, --show chart, 15 total 
- New strategies: dmi_trend, cci_breakout, mfi_volume, trix_cross, mtm_momentum
- run_all_strategies.py --show: dual-axis equity curve vs stock price chart
- zhuoyao_momentum strategy (from earlier commit)
- README: updated strategy table (9→15), changelog, demo screenshots
- Bump version to 1.8.2

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-06-09 23:17:04 +08:00
GitHubandClaude Opus 4.8 8fcedeb47a feat(strategies): add zhuoyao_momentum strategy + Maotai demo screenshot 
- New ZHUOYAO multi-timeframe momentum strategy (strategies/zhuoyao_momentum.py)
- Entry: SHORT>0 + TREND>0 + SHORT>MID (triple resonance)
- Exit: SHORT<0 or TREND<0 (conservative, any triggers sell)
- Add SH600519 Maotai demo screenshot (strategies/demo/4.png)
- Update README with 4th demo screenshot

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-06-09 22:59:19 +08:00
GitHub b57d8f4669 feat(backtest): add --show flag for best strategy equity curve chart 
- Add --show/--show-chart flag to run_all_strategies.py
- Display dual-axis chart: normalized stock price vs strategy equity curve
- Mark buy/sell points with green/orange triangles
- Auto-detect Chinese fonts (SimHei/YaHei on Windows, PingFang on macOS)
- Fetch stock name via get_stock_quotes for chart title
- Add 3 demo screenshots to README with disclaimer
- Update README with --show usage and visual examples
 2026-06-09 22:41:14 +08:00
GitHubandClaude Opus 4.8 b44636207b release: v1.8.1 - single-source version, batch backtest detail output 
- Consolidate version to pyproject.toml as single source of truth
- __init__.py, cli/__init__.py, docs/conf.py all read dynamically
- run_all_strategies.py now shows best strategy full trade details
- Update README changelog for 1.8.1

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-06-09 22:12:27 +08:00
GitHubandClaude Opus 4.8 b5b5d0dc5b release: v1.8.0 - backtest engine with batch strategy comparison 
- Add backtest section to README with CLI usage and run_all_strategies.py demo
- Update all version numbers to 1.8.0 (pyproject.toml, __init__.py, cli/__init__.py, docs/conf.py)
- Fix turtle_breakout strategy: TAQ returns 3 values (UP, MID, DOWN)
- Add run_all_strategies.py batch comparison script
- Update README intro to highlight backtest feature
- Add backtest to CLI command table and architecture tree

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-06-09 20:35:38 +08:00
GitHubandClaude Opus 4.8 70c69c8a66 fix(backtest): cli _print_table used wrong key 'sharpe_ratio' instead of 'sharpe' 
Performance dict outputs 'sharpe' but _print_table looked up 'sharpe_ratio',
so perf.get('sharpe_ratio', 0) always returned the default 0 regardless of
actual Sharpe value.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-06-09 20:02:20 +08:00
GitHubandClaude Opus 4.8 46298e68d7 fix(backtest): max drawdown now correctly measures peak-to-trough percentage 
Previous formula was: max(absolute_drawdown) / initial_capital, which
exceeds 100% when the portfolio grows then drops (e.g. from 600k to 300k
on a 100k initial = 300% drawdown, which is nonsensical).

Fixed to use drawdown_pct (drawdown / peak) which is always in [0, 1].
This correctly measures the maximum percentage drop from the highest
equity peak, matching the standard financial definition.

Also added regression test: test_max_drawdown_never_exceeds_100_pct.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-06-09 19:00:11 +08:00
GitHubandClaude Opus 4.8 5550702620 fix(strategies): unpack BIAS triple return value in bias_reversal 
MyTT.BIAS returns (BIAS6, BIAS12, BIAS24) but the strategy was assigning
all three to a single variable, causing 'array with more than one element'
ValueError when comparing to a scalar threshold.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-06-09 18:56:07 +08:00
GitHubandClaude Opus 4.8 6a6d75f5d5 fix(backtest): strategy position not tracked during signal generation 
Root cause: _generate_signals() iterated all bars calling strategy.next()
but never updated _position_size or _cash on the strategy. Strategies
that check self.position['size'] before buy/sell always saw 0, producing
only BUY signals with no SELL — exhausting cash and producing drawdowns
exceeding 100%.

Fix: add _update_strategy_position() that estimates position changes
after each bar's signals using close price. This gives the strategy an
accurate view of its holdings so it can correctly alternate buy/sell.

Regression tests added:
- test_position_aware_buy_sell_alternation: verifies BUY/SELL alternation
- test_position_aware_no_duplicate_buys: no suspicious tiny duplicate buys

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-06-09 18:50:13 +08:00
GitHubandClaude Opus 4.8 f7e1abd873 feat: add 9 demo strategy files for backtest engine 
Strategies included:
- ma_cross: MA5/MA20 dual moving average crossover
- expma_cross: EMA12/EMA50 crossover (more responsive)
- macd_cross: MACD golden/death cross
- bollinger_breakout: Bollinger band breakout
- rsi_reversal: RSI overbought/oversold reversal
- kdj_golden: KDJ low golden cross / high death cross
- turtle_breakout: Turtle trading (Donchian channel)
- bias_reversal: BIAS mean reversion
- volume_price: Volume-price confirmation

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-06-09 18:45:01 +08:00
GitHubandClaude Opus 4.8 00b7d75caa docs: add backtest engine usage manual 
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-06-09 18:37:58 +08:00
GitHubandClaude Opus 4.8 04c2be1d7f fix(backtest): resolve mypy and ruff lint issues 
- dsl.py: use NDArray type annotations, fix None narrowing
- cli.py: add type annotations, fix import sorting
- strategy.py: fix UP038 isinstance, add noqa for I() method name
- tests: fix E712 bool comparison assertions

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-06-09 18:21:25 +08:00
GitHubandClaude Opus 4.8 fc0777533e feat(backtest): add CLI command with auto data fetch and table output 
- Created src/easy_tdx/backtest/cli.py with backtest command
- Supports --strategy-file to load Python strategy classes
- Supports --indicators to precompute technical indicators
- Supports --cash, --commission, --execution, --period, --adjust, --count options
- Supports json/table/csv output formats
- Auto-loads K-line data via get_mac_client()
- Registered backtest command in src/easy_tdx/cli/__init__.py
- Added tests/unit/test_backtest_cli.py with basic CLI tests

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-06-09 18:15:37 +08:00
GitHubandClaude Opus 4.8 706f22ba5e feat(backtest): add DSL strategy skeleton and update __init__.py exports 
- Add dsl_strategy decorator in dsl.py (P1 skeleton implementation)
- Update __init__.py to export BacktestEngine, Strategy, and related types
- All 106 backtest unit tests pass

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-06-09 18:12:38 +08:00
GitHubandClaude Opus 4.8 371915a5f9 feat(backtest): add BacktestEngine with vectorized execution pipeline 
- Implement BacktestEngine orchestrator with 4-step pipeline:
  1. Signal generation (Strategy)
  2. Order simulation (OrderSimulator)
  3. Portfolio tracking (PortfolioTracker)
  4. Performance analysis (PerformanceAnalyzer)
- Support both strategy class and instance initialization
- Add PnL calculation for sell trades
- Add JSON serialization with numpy/timestamp support
- Include comprehensive test coverage (12 tests, all passing)

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-06-09 18:11:20 +08:00
GitHubandClaude Opus 4.8 94fabccef8 feat(backtest): add PerformanceAnalyzer with 19 metrics 
- Implement PerformanceAnalyzer class with compute() method
- Calculate 19 performance metrics: total_return, annual_return, max_drawdown,
  max_dd_duration, sharpe, sortino, calmar, trade statistics, and volatility
- Handle edge cases: empty data, no negative returns (sortino=999), no drawdown (calmar=999)
- Add 20 comprehensive unit tests covering all metrics
- Type annotations use NDArray pattern for mypy strict compliance
- All tests pass, mypy and ruff checks clean

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-06-09 18:05:33 +08:00
GitHubandClaude Opus 4.8 a2aa319803 feat(backtest): add PortfolioTracker with equity curve and drawdown 
- Pre-allocate numpy arrays for performance (cash, position, avg_price)
- apply_trades() processes buys/sells with commission and slippage
- equity_curve returns DataFrame with drawdown calculation
- positions returns DataFrame with market value and unrealized PnL
- 12 unit tests covering all scenarios

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-06-09 17:55:24 +08:00
GitHubandClaude Opus 4.8 16dc2e7da9 feat(backtest): add OrderSimulator with 5 execution modes and reject policy 
- Implement OrderSimulator class for order matching simulation
- Support 5 execution modes: next_open, next_close, this_close, worst, best
- Support 3 position modes: full, fixed, percent
- Support 2 reject policies: reduce (partial fill), skip (reject)
- Implement fee model: commission (min 5 CNY), stamp tax (0.1% sell only), slippage
- Add future_leak_warning flag for this_close mode
- Handle both int and datetime column types in DataFrame
- Add comprehensive test suite with 24 test cases covering all modes

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-06-09 17:52:31 +08:00
GitHubandClaude Opus 4.8 687851fc67 feat(backtest): add Strategy base class with DataProxy and crossover 
- Add _SeriesAccessor for relative indexed data access ([0] current, [-1] previous)
- Add StrategyDataProxy for efficient DataFrame column access via numpy arrays
- Add crossover() function for golden cross detection (fast line crosses above slow line)
- Add Strategy abstract base class with:
  - init() for indicator registration via self.I()
  - next() for signal generation via buy()/sell()
  - Internal engine hooks (_bind_data, _call_init, _set_bar_index, etc.)
- All code is mypy strict compliant with full type annotations
- 25 unit tests covering all components

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-06-09 16:53:57 +08:00
GitHubandClaude Opus 4.8 f37b75ea42 feat(backtest): add core data types (Signal/Trade/Position/BacktestResult) 
- Add Signal dataclass for trading signals with optional price/stop_loss/take_profit
- Add Trade dataclass for executed trades with commission/slippage/pnl/rejected
- Add Position dataclass for position snapshots (long/short/flat)
- Add BacktestResult dataclass with to_dict()/to_json()/summary() methods
- Add comprehensive unit tests (13 test cases, 100% pass)
- All code passes mypy strict, ruff lint+format checks

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-06-09 16:43:44 +08:00
GitHubandClaude Opus 4.8 5f14c44791 docs: add backtest engine implementation plan 
10 tasks, TDD approach, covering:
- Core data types (Signal/Trade/Position/BacktestResult)
- Strategy base class with DataProxy and crossover
- OrderSimulator (5 execution modes + reject policy)
- PortfolioTracker (equity curve + drawdown)
- PerformanceAnalyzer (18 metrics)
- BacktestEngine (vectorized execution pipeline)
- DSL skeleton (P1)
- CLI integration with auto data fetch

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-06-09 16:25:11 +08:00
GitHubandClaude Opus 4.8 28925063d4 docs: finalize backtest spec with minor clarifications (rev 2.1) 
- DSL identifier rules: letters/digits/underscores
- reduce mode: min(requested, max_affordable) formula
- Chanlun time alignment: nearest K-line <= timestamp
- GridResult/run_many return types documented

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-06-09 16:17:02 +08:00
GitHubandClaude Opus 4.8 480e635dcb docs: revise backtest spec per feasibility review (rev 2) 
- DSL requires explicit column references (close/open/high/low)
- Add order_reject_policy: reduce | skip
- Add future_leak_warning for this_close execution
- Add benchmark datetime alignment rules
- Support pre-computed indicator columns via StrategyDataProxy
- Add chanlun_result injection (P0 interface, v2 auto-integration)
- Adjust priorities: DSL→P1, run_many/run_grid→P1, chanlun→P1

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-06-09 16:14:05 +08:00