- 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>
- 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>
- 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>
- 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>
- 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>
- 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>
Fix find_bis() greedy algorithm terminating early when dense alternating
fractals cause gap=0 for every opposite-type fractal. The root cause was
blindly replacing start_fx with more extreme same-type fractals, pushing
right_kline_index forward and making subsequent gaps permanently 0.
Solution: add pending_opposite guard — when an opposite-type fractal fails
the gap check, freeze start_fx replacement until a valid bi is formed.
- Affects: sustained up/down trends with dense fractals (e.g. high-price stocks)
- 600519: 114 bi (ending 04-28) -> 142 bi (ending 05-27)
- 601088: 131 bi -> 147 bi (end date unchanged)
- New regression test: test_fractal_trap_regression
- Bump version to 1.7.1
Integrate MyTT library to provide 30 technical indicators (MACD, KDJ, RSI,
BOLL, DMI, ATR, etc.) accessible via API and CLI with automatic EMA warm-up.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
- Add MacClient/AsyncMacClient with full MAC protocol support (quotes, kline
with adjustment, tick charts, transactions, boards, capital flow, auction,
unusual, symbol info, server info)
- Add MacExClient/AsyncMacExClient for extended markets (HK, US, futures)
- Add UnifiedTdxClient auto-routing between A-share and extended markets
- Add `easy-tdx` CLI tool with JSON default output, Agent-friendly
- Add field bitmap protocol for custom quote field selection
- Fix quote-list missing fields (default to BASIC+VOLUME preset)
- Add config.py with centralized host management and auto-discovery
- Add 50+ examples covering all APIs (01-20)
- Rewrite README with CLI-first, Agent-friendly documentation
- Bump version to 1.1.0
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
- K-line: daily+ periods output 'date' only, minute periods output 'datetime'
- Transactions (tick-by-tick): combine date param + hour/minute into 'datetime'
- XdxrRecord, HistoricalFundFlow: year/month/day merged to 'date'
- MinuteBar: rename unknown_1 to _unknown_1 (hidden from DataFrame)
- MinuteBar: add datetime column computed from bar index (A-share 240-bar pattern)
- get_minute_time_data: use history endpoint only (current-day endpoint broken in pytdx too)
- Update all examples to reflect new DataFrame column names
Add CALC_HOSTS, financial file list/record parsing (codec/financial.py),
new client methods (get_financial_file_list, get_financial_file,
get_financial_records) with async counterparts, and example 09 demo.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
