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- Implemented `generate_bridge_csv.py` to generate reports for strategy winners from the Strategy Tester notebook. - Added `smoke_test_explorer.py` to perform smoke tests on the Explorer notebook integration, validating core logic and data processing.
40 lines
1008 B
JSON
40 lines
1008 B
JSON
{
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"tf": "M15",
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"n_states": 3,
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"taxonomy": "TREND/MEAN_REVERSION/VOLATILITY_SHOCK",
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"states": {
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"raw_state_0": {
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"label": "TREND",
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"raw_id": 0,
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"canonical_id": 0,
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"persistence": 0.980975,
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"entropy_bits": 0.14093,
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"vol_mean_scaled": -0.573979,
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"return_mean_scaled": 0.002087,
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"return_dispersion": 0.39388,
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"tradeable": true
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},
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"raw_state_1": {
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"label": "VOLATILITY_SHOCK",
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"raw_id": 1,
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"canonical_id": 2,
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"persistence": 0.968925,
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"entropy_bits": 0.228487,
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"vol_mean_scaled": 0.025243,
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"return_mean_scaled": 0.037496,
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"return_dispersion": 0.770531,
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"tradeable": true
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},
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"raw_state_2": {
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"label": "VOLATILITY_SHOCK",
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"raw_id": 2,
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"canonical_id": 2,
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"persistence": 0.971048,
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"entropy_bits": 0.190025,
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"vol_mean_scaled": 1.499342,
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"return_mean_scaled": -0.100202,
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"return_dispersion": 2.076334,
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"tradeable": true
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}
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}
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} |