Tutorial 00 - Decomposition-first quant trading roadmap
Executed tutorial notebook. This page is generated from
examples/notebooks/quant_trading/00_decomposition_first_quant_trading_roadmap.ipynb and includes markdown cells, code cells, stdout, tables, and captured figures from the committed notebook.
Tutorial Navigation
| Track | Tutorial notebook |
|---|---|
| Roadmap | Tutorial 00 - Roadmap |
| Strategy Lab | 01 Trend-Following Lab |
| Tutorial Sequence | 01 Real Market Data and Feature Factory |
| Tutorial Sequence | 02 Decomposition-aware MA and MACD |
| Strategy Lab | 02 Oscillation-Reversion Lab |
| Strategy Expansion | 03 Method-Specific Variants |
| Tutorial Sequence | 03 Residual Mean Reversion |
| Strategy Expansion | 04 Component Pair Trading |
| Tutorial Sequence | 04 Donchian Breakout |
| Tutorial Sequence | 05 Pair-Spread Stat-Arb |
| Tutorial Sequence | 06 Cross-Sectional Rotation |
| Native SSA Replay | 07 Native SSA High-Return / Low-Drawdown |
Executed Notebook
The revised tutorial is built around one idea: classic technical strategies are mostly rough filters for trend, cycle, residual deviation, and participation. DeTime makes those pieces explicit before the strategy layer.
Implemented in this update:
- Market data and decomposition feature factory.
- Decomposition-aware moving average and MACD strategies.
- Residual mean reversion, RSI, Bollinger and APO rewrites.
- Turtle/Donchian breakout with trend, cycle, residual and volume gates.
- Pair spread decomposition and stat-arb.
- Cross-sectional rotation and portfolio construction.
- Native SSA high-return / low-drawdown strategy replay for selected FX and crypto examples.
Additional strategy labs:
- two concrete strategy families: trend following and oscillation / residual reversion;
- method-specific strategy variants across STL, SSA and STD;
- component-level pair trading with decomposition and cointegration diagnostics;
- native SSA dual-trend mean-reversion replay with buy/sell analysis, equity-vs-buy-hold comparison, drawdown curves, and monthly tables.
In [1]
from pathlib import Path
[p.name for p in sorted(Path("examples/notebooks/quant_trading").glob("*.ipynb"))]
text/plain
['00_decomposition_first_quant_trading_roadmap.ipynb',
'01_detime_trend_following_strategy_lab.ipynb',
'01_market_data_and_decomposition_feature_factory.ipynb',
'02_decomposition_aware_moving_average_macd.ipynb',
'02_detime_oscillation_reversion_strategy_lab.ipynb',
'03_detime_method_specific_strategy_variants.ipynb',
'03_residual_mean_reversion_rsi_bollinger.ipynb',
'04_detime_component_pair_trading_cointegration.ipynb',
'04_turtle_donchian_breakout_volume_confirmation.ipynb',
'05_pairs_spread_decomposition_stat_arb.ipynb',
'06_cross_sectional_rotation_portfolio.ipynb',
'07_native_ssa_high_return_low_drawdown_tutorial.ipynb']