seasonal.py gets a frame-based entry (analyse_frame) and a reusable
report() so the identical statistics - circular-rotation family-wise
null, max-|t| bar, split-half - can run on instruments whose book is
synthesised from M1 bars. breadth_seasonal.py runs it on the five
SQX-decoded instruments (FTSE100, UK100, WTI x2 feeds, USDCAD) that
share no data path with the four originals; the duplicate-market pairs
(FTSE100/UK100, WTI_d/WTI_5) double as replication checks. Caveats
stated in the module docstring: synthesised flat spread (move/spread
is approximate, no intraday spread shape) and file-time clock labels;
drift/t columns are spread-free and unaffected.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
- Implemented sqx_audit.py to audit StrategyQuant X trade lists, focusing on performance metrics and cost analysis.
- Created sqx_portfolio.py to evaluate portfolio performance based on uncorrelated components and their impact on risk and return.
- Developed swing.py to analyze cost ratios across different holding periods and assess swing trading structures.
- Introduced test_management.py to investigate the effectiveness of exit rules on random entries and their impact on expectancy.
