Risk management research divides into measurement and mechanism. The measurement literature — VaR and expected shortfall estimation, extreme value theory, drawdown analysis — asks how to quantify what can go wrong in a portfolio. The mechanism literature — systemic risk, contagion networks, stress testing — asks how losses propagate between institutions and markets.
The practical test for measurement papers is backtesting honesty: a VaR model is only as good as its violation rate and the independence of its violations, and papers that report Kupiec or Christoffersen tests on out-of-sample data outrank those that stop at in-sample fit. For tail-risk work specifically, be wary of estimators tuned to one crisis; the ranking below rewards papers validated across multiple stress regimes. This is also where regulation (Basel’s shift from VaR to expected shortfall) keeps the academic work unusually connected to practice.
Related hubs: Volatility Modeling, Portfolio Optimization, Fixed Income & Rates.
Explainers from the corpus: risk measures beyond VaR →
Artificial intelligence (AI) can undermine financial stability because of malicious use, misinformation, misalignment, and the AI analytics market structure. The low frequency and uniqueness of financial crises, coupled with mutable and unclear objectives, frustrate machine learning. Even if the aut
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Enron Board’s Finance Sub-Committee’s approval of the first bankrupting Raptor transaction, Talon, is examined in as much detail as published documents allow.
Spanish Abstract: Esta nota recoge los10 errores más habituales con los que los autores se han encontrado al tratar con abogados en pleitos, en arbitraje
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