Changelog

v0.1.3 — 2026-04-30

Add Time-Series Momentum (TSMOM) strategy engine (1d5c374)
- time_series_momentum — trend-following by sign of trailing return, following Moskowitz, Ooi & Pedersen (2012)
- Optional skip_period implements the classic 12-1 momentum convention (Asness, Moskowitz & Pedersen, 2013) to neutralise short-horizon reversal contamination
- Confidence scales linearly with the magnitude of the trailing return, saturating at a 10 % move
- Structurally complementary to the mean-reversion engines: profits in persistent directional regimes where mean-reversion bleeds

Add behavioural test suite covering all 7 strategy engines (3705270)
- Property-based pattern fixtures (linear trend, divergence, regime mix, VSA stopping volume, breakout, pullback, reversal at support)
- Verifies signal direction, confidence range, and metadata invariants on canonical inputs

Add narrative strategy guide for time-series momentum and wire it into the Sphinx API reference (698d498)
Fill remaining doc gaps (541aa50)
- Add size_by_risk automodule to backtest API reference
- Add narrative guide for pairs_mean_reversion
- New dedicated indicators reference page (moved out of strategies API page, with a five-family overview)
- Refresh getting_started Available Strategies list with the four engines added since v0.1.0
- Rename misspelled reversial_support.md → reversal_support.md

Add exit rules (stop-loss, take-profit, trailing stop) to backtest engine (4ad641f)
- ExitReason enum: SIGNAL, STOP_LOSS, TAKE_PROFIT, TRAILING_STOP, END_OF_DATA
- ExitRules frozen dataclass with percentage-based global rules
- Per-trade metadata overrides for absolute price levels
- Exit checks run each bar before strategy.compute() using high/low prices
- Pessimistic priority: stop-loss > trailing stop > take-profit
- Fill at trigger price level, not bar close
- Fully backward-compatible (all defaults disabled)
Add risk-based position sizing utility size_by_risk() (4ad641f)
Add get_parameter_schema() to all strategies missing it (a8748bb)
- MeanReversionStrategy, BreakoutConsolidationStrategy, PullbackTrendStrategy, ReversalSupportStrategy, PairsMeanReversionStrategy
Add breakout, pullback, and reversal strategies with indicators (aa72385)
- breakout_consolidation — breakout from low-volatility consolidation
- pullback_trend — trend continuation on pullback to short-term MA
- reversal_support — counter-trend reversal at support with RSI confirmation
- 20+ pure-NumPy technical indicators in quaver.strategies.indicators

Initial release of pyquaver (import quaver).

Implement quaver library with 4 strategy engines, backtest engine, and test suite (ae334e4)
- mean_reversion — dual moving-average mean reversion
- regime_mean_reversion — regime-based probabilistic mean reversion
- vsa_stopping_volume — VSA stopping-volume reversal pattern
- pairs_mean_reversion — statistical arbitrage pairs trading
- Single-asset and multi-asset walk-forward backtest engines
- Portfolio tracker with long/short support
- BacktestResult with equity curve, Sharpe, drawdown, profit factor
PyPI release setup: LICENSE, README, project.urls, optional dependency groups (289077b)
Add example Jupyter notebook with yfinance-backed end-to-end backtests

Set up Sphinx project with autodoc, rST docstrings, and Read the Docs theme (130650b)
Getting started guide with PyPI install instructions

GitHub Actions workflows for CI (lint + test), Sphinx docs deploy to GitHub Pages, and PyPI publishing via trusted publisher (b3ac757)
Dev builds auto-published to TestPyPI on push to develop