Returns-driven macro regimes and characteristic lead-lag behaviour between asset classes
We define data-driven macroeconomic regimes by clustering the relative performance in time of indices belonging to different asset classes. We then investigate lead-lag relationships within the regimes identified. Our study unravels market features characteristic of different windows in time and lev...
| 主要な著者: | , |
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| フォーマット: | Conference item |
| 言語: | English |
| 出版事項: |
Association for Computing Machinery
2022
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| 要約: | We define data-driven macroeconomic regimes by clustering the relative
performance in time of indices belonging to different asset classes. We then
investigate lead-lag relationships within the regimes identified. Our study
unravels market features characteristic of different windows in time and
leverages on this knowledge to highlight market trends or risks that can be
informative with respect to recurrent market developments. The framework
developed also lays the foundations for multiple possible extensions. |
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