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| <li class="nav-item" data-bs-level="2"><a href="#1-why-different-decomposition-methods-create-different-strategies" class="nav-link">1. Why different decomposition methods create different strategies</a> |
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| <h1 id="detime-method-specific-strategy-expansion">DeTime Method-Specific Strategy Expansion</h1> |
| <p>This tutorial layer extends the two core strategy families already implemented in the strategy lab:</p> |
| <ol> |
| <li><strong>Trend following</strong>: trade when the decomposed trend is strong enough to define a directional regime.</li> |
| <li><strong>Oscillation reversion</strong>: trade when the decomposed trend is weak and the residual becomes the tradable deviation.</li> |
| </ol> |
| <p>The new point is that the decomposition method and decomposition horizon are not neutral implementation details. They create different trend, cycle, and residual estimates, and therefore create different strategies.</p> |
| <h2 id="1-why-different-decomposition-methods-create-different-strategies">1. Why different decomposition methods create different strategies</h2> |
| <p>A raw moving-average strategy changes when the moving-average length changes. A decomposition strategy changes when any of these choices change:</p> |
| <ul> |
| <li>the decomposition method: STL, SSA, STD, Wavelet, EMD, VMD, etc.;</li> |
| <li>the decomposition period: short cycle, medium cycle, long cycle;</li> |
| <li>the walk-forward training window;</li> |
| <li>the recomputation step;</li> |
| <li>the residual z-score window;</li> |
| <li>volume decomposition and liquidity filters.</li> |
| </ul> |
| <p>The same trading rule can be held fixed:</p> |
| <pre><code class="language-text">enter long if trend_slope > 0 and trend_strength is high |
| enter reversion if residual_z is too negative in a weak-trend regime |
| </code></pre> |
| <p>but if STL and SSA extract different trends and cycles, then the entry dates, exits, position sizes, and backtest results are different. The tutorial therefore treats each method-horizon combination as a separate strategy variant.</p> |
| <h2 id="2-method-selection-guide">2. Method selection guide</h2> |
| <table> |
| <thead> |
| <tr> |
| <th>Method</th> |
| <th>Trading interpretation</th> |
| <th>Useful default</th> |
| <th>Main risk</th> |
| </tr> |
| </thead> |
| <tbody> |
| <tr> |
| <td>STL</td> |
| <td>fixed-period seasonal-trend split</td> |
| <td>stable daily/weekly/monthly rhythm</td> |
| <td>phase errors when the cycle drifts</td> |
| </tr> |
| <tr> |
| <td>SSA</td> |
| <td>low-rank Hankel subspace split</td> |
| <td>smoother quasi-periodic financial cycles</td> |
| <td>leakage under abrupt breaks</td> |
| </tr> |
| <tr> |
| <td>STD</td> |
| <td>seasonal-trend-dispersion split</td> |
| <td>when volatility/dispersion matters</td> |
| <td>may be conservative on entry signals</td> |
| </tr> |
| <tr> |
| <td>Wavelet</td> |
| <td>multi-scale local split</td> |
| <td>local regime changes and multi-scale cycles</td> |
| <td>requires PyWavelets and scale tuning</td> |
| </tr> |
| <tr> |
| <td>EMD/CEEMDAN</td> |
| <td>adaptive intrinsic oscillatory modes</td> |
| <td>non-stationary amplitude/frequency cycles</td> |
| <td>mode mixing</td> |
| </tr> |
| <tr> |
| <td>VMD</td> |
| <td>narrow-band spectral modes</td> |
| <td>compact frequency bands</td> |
| <td>sensitive to K and alpha</td> |
| </tr> |
| </tbody> |
| </table> |
| <h2 id="3-parameter-tuning-logic">3. Parameter tuning logic</h2> |
| <p>The tutorial avoids blind optimization first. It uses interpretable grids:</p> |
| <table> |
| <thead> |
| <tr> |
| <th>Market idea</th> |
| <th>DeTime parameter</th> |
| <th>Example</th> |
| </tr> |
| </thead> |
| <tbody> |
| <tr> |
| <td>short trading rhythm</td> |
| <td>period</td> |
| <td>21 bars</td> |
| </tr> |
| <tr> |
| <td>medium swing rhythm</td> |
| <td>period</td> |
| <td>42 or 63 bars</td> |
| </tr> |
| <tr> |
| <td>long trend structure</td> |
| <td>train_window</td> |
| <td>252 bars</td> |
| </tr> |
| <tr> |
| <td>fast adaptation</td> |
| <td>step</td> |
| <td>5 or 21 bars</td> |
| </tr> |
| <tr> |
| <td>low turnover</td> |
| <td>step</td> |
| <td>63 or 126 bars</td> |
| </tr> |
| <tr> |
| <td>residual band sensitivity</td> |
| <td>z_window</td> |
| <td>42, 63, 126 bars</td> |
| </tr> |
| </tbody> |
| </table> |
| <p>A practical workflow is:</p> |
| <ol> |
| <li>Start with <code>STL</code>, <code>SSA</code>, and <code>STD</code> on periods <code>21</code>, <code>42</code>, and <code>63</code>.</li> |
| <li>Compare strategy families, not only decomposition plots.</li> |
| <li>Check orders, round-trip trades, drawdown, turnover, and exposure.</li> |
| <li>Add Wavelet only after installing PyWavelets.</li> |
| <li>Treat the best variant as a hypothesis, not as proof of alpha.</li> |
| </ol> |
| <h2 id="4-strategy-variants-now-implemented">4. Strategy variants now implemented</h2> |
| <p>The module <code>examples/quant_trading/strategy_method_variants.py</code> implements:</p> |
| <ul> |
| <li><code>decomposition_trend_following_signals</code></li> |
| <li><code>decomposition_oscillation_reversion_signals</code></li> |
| <li><code>decomposition_residual_bollinger_signals</code></li> |
| <li><code>decomposition_macd_trend_signals</code></li> |
| <li><code>decomposition_trend_crossover_signals</code></li> |
| <li><code>run_method_variant_grid</code></li> |
| </ul> |
| <p>The residual Bollinger strategy replaces raw-price bands with residual bands around <code>trend + cycle</code> fair value. The trend MACD strategy computes MACD on the decomposed trend instead of raw price. The trend crossover strategy computes fast/slow EMAs on the decomposed trend.</p> |
| <h2 id="5-component-level-pair-trading">5. Component-level pair trading</h2> |
| <p>The module <code>examples/quant_trading/strategy_component_pairs.py</code> implements decomposition-first pair trading.</p> |
| <p>The logic is:</p> |
| <pre><code class="language-text">1. Decompose both assets. |
| 2. Check whether their trends are similar. |
| 3. Check whether their cycles are similar. |
| 4. Use Engle-Granger and ADF diagnostics on raw price, fair value, and spread residuals. |
| 5. Trade the residual gap or the deviation from the trend+cycle relationship. |
| </code></pre> |
| <p>Implemented pair strategies:</p> |
| <ul> |
| <li><code>classic_pair_spread_zscore</code></li> |
| <li><code>detime_<method>_component_residual_gap</code></li> |
| <li><code>detime_<method>_fair_spread_deviation</code></li> |
| <li><code>detime_<method>_cointegration_filtered_residual_gap</code></li> |
| </ul> |
| <p>The pair-trading tutorial is not only about whether two raw prices are cointegrated. It also asks whether the decomposed components support the pair hypothesis:</p> |
| <pre><code class="language-text">trend_left ~ trend_right |
| cycle_left ~ cycle_right |
| residual_left - residual_right is the traded gap |
| </code></pre> |
| <h2 id="6-commands">6. Commands</h2> |
| <p>Offline real-data smoke run:</p> |
| <pre><code class="language-bash">make strategy-expansion |
| </code></pre> |
| <p>Live Yahoo Finance run:</p> |
| <pre><code class="language-bash">make strategy-expansion-live |
| </code></pre> |
| <p>Direct custom run:</p> |
| <pre><code class="language-bash">python examples/quant_trading/scripts/run_strategy_expansion.py \ |
| --use-bundled-sample \ |
| --variant-grid custom \ |
| --methods STL SSA STD \ |
| --periods 21 42 63 \ |
| --train-window 180 \ |
| --step 21 \ |
| --pair-method STL \ |
| --pair-period 42 |
| </code></pre> |
| <h2 id="7-output-files">7. Output files</h2> |
| <p>The script writes:</p> |
| <pre><code class="language-text">examples/quant_trading/reports/strategy_expansion/method_variant_strategy_stats.csv |
| examples/quant_trading/reports/strategy_expansion/method_variant_orders.csv |
| examples/quant_trading/reports/strategy_expansion/method_variant_trades.csv |
| examples/quant_trading/reports/strategy_expansion/method_variant_spec_grid.csv |
| examples/quant_trading/reports/strategy_expansion/method_variant_feature_coverage.csv |
| examples/quant_trading/reports/strategy_expansion/method_variant_failed_methods.csv |
| examples/quant_trading/reports/strategy_expansion/component_pair_strategy_stats.csv |
| examples/quant_trading/reports/strategy_expansion/component_pair_diagnostics.csv |
| examples/quant_trading/reports/strategy_expansion/component_pair_orders.csv |
| examples/quant_trading/reports/strategy_expansion/component_pair_trades.csv |
| examples/quant_trading/reports/strategy_expansion/strategy_expansion_run_manifest.json |
| </code></pre> |
| <p>Smoke outputs are tutorial evidence that the pipeline runs. They are not production trading claims.</p></div> |
| </div> |
| </div> |
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