Dependence Structure and Extreme Comovements in International Equity and Bond Markets
Bibliographic record
Abstract
Common negative extreme variations in returns are prevalent in international equity markets. This has been widely documented with statistical tools such as exceedance correlation, extreme value theory, and Gaussian bivariate GARCH or regime-switching models. We point to limits of these tools to characterize extreme dependence and propose an alternative regime-switching copula model that includes one normal regime in which dependence is symmetric and a second regime characterized by asymmetric dependence. Moreover, to fully appreciate the potential effects of this asymmetric dependence in terms of portfolio diversification, we apply this model to international equity and bond markets, to allow for inter-market movements. Empirically, we find that dependence between international assets of the same type is strong in both regimes, especially in the asymmetric one, but weak between equities and bonds, even in the same country. We study analytically how and when asymmetric dependence may amplify empirically documented phenomena such as flight to safety and home bias in portfolio allocation. Les écarts de rendement négatifs extrêmes communs existent dans les marchés boursiers internationaux. Ce phénomène a été largement démontré par des outils statistiques, tels que la corrélation des dépassements, la théorie des valeurs extrêmes et les modèles GARCH bivarié en langage Gauss ou avec changement de régime. Nous signalons les limites de ces outils pour caractériser la dépendance extrême et proposons un modèle de copules avec changement de régime, comprenant un régime normal dans lequel la dépendance est symétrique et un second régime caractérisé par une dépendance asymétrique. De plus, afin de saisir pleinement l'incidence potentielle de cette dépendance asymétrique en termes de diversification du portefeuille, nous appliquons ce modèle aux marchés internationaux des actions et des obligations, afin de permettre les mouvements entre les marchés. D'un point de vue empirique, nous constatons une forte dépendance entre les actifs internationaux de même type dans les deux régimes, surtout dans le régime asymétrique, et une faible dépendance entre les actions et les obligations, bien qu'il soit question d'un même pays. Nous procédons à un examen analytique afin de déterminer quand et comment la dépendance asymétrique peut, lors de la répartition du portefeuille, amplifier les phénomènes suivants établis empiriquement : fuite vers la sécurité et surinvestissement dans des sociétés proches du domicile.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".