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Working Paper
Fed-Driven Systemic Tail Risk: High-Frequency Measurement, Evidence and Implications
Yang, Xiye; Neely, Christopher J.; Erdemlioglu, Deniz (2025-05-27)
We develop a framework to measure market-wide (systemic) tail risk in the cross-section of asset returns. Using high-frequency data on individual U.S. stocks and sector-specific ETF portfolios, we estimate time-varying jump intensities and multi-asset tail risk around Fed policy announcements. While most FOMC announcements generate systemic left-tail risk, there is no evidence that macro announcements have a similar effect. The magnitude of the tail risk induced by Fed policy announcements varies over the business cycle, peaks during the global financial crisis and remains high during phases ...
Working Papers , Paper 2023-016

Report
Equity Volatility Term Premia
Van Tassel, Peter (2018-09-01)
This paper estimates the term-structure of volatility risk premia for the stock market. Realized variance term premia are increasing in systematic risk and predict variance swap returns. Implied volatility term premia are decreasing in risk initially, but then increase at a lag, predicting VIX futures returns. By modeling the logarithm of realized variance, the paper derives a closed-form relationship between the prices of variance swaps and VIX futures. The model provides accurate pricing and highlights periods of dislocation between the index options and VIX futures markets. Term premia ...
Staff Reports , Paper 867

Working Paper
Systemic Tail Risk: High-Frequency Measurement, Evidence and Implications
Yang, Xiye; Neely, Christopher J.; Erdemlioglu, Deniz (2023-07-20)
We develop a new framework to measure market-wide (systemic) tail risk in the cross-section of high-frequency stock returns. We estimate the time-varying jump intensities of asset prices and introduce a testing approach that identifies multi-asset tail risk based on the release times of scheduled news announcements. Using high-frequency data on individual U.S. stocks and sector-specific ETF portfolios, we find that most of the FOMC announcements create systemic left tail risk, but there is no evidence that macro announcements do so. The magnitude of the tail risk induced by Fed news varies ...
Working Papers , Paper 2023-016

Working Paper
Dynamic Factor Copula Models with Estimated Cluster Assignments
Oh, Dong Hwan; Patton, Andrew J. (2022-05-06)
This paper proposes a dynamic multi-factor copula for use in high dimensional time series applications. A novel feature of our model is that the assignment of individual variables to groups is estimated from the data, rather than being pre-assigned using SIC industry codes, market capitalization ranks, or other ad hoc methods. We adapt the k-means clustering algorithm for use in our application and show that it has excellent finite-sample properties. Applying the new model to returns on 110 US equities, we find around 20 clusters to be optimal. In out-of-sample forecasts, we find that a model ...
Finance and Economics Discussion Series , Paper 2021-029r1

Working Paper
The dynamic factor network model with an application to global credit risk
Bräuning, Falk; Koopman, Siem Jan (2016-10-31)
We introduce a dynamic network model with probabilistic link functions that depend on stochastically time-varying parameters. We adopt the widely used blockmodel framework and allow the high-dimensional vector of link probabilities to be a function of a low-dimensional set of dynamic factors. The resulting dynamic factor network model is straightforward and transparent by nature. However, parameter estimation, signal extraction of the dynamic factors, and the econometric analysis generally are intricate tasks for which simulation-based methods are needed. We provide feasible and practical ...
Working Papers , Paper 16-13

Working Paper
Measuring Interest Rate Risk Management by Financial Institutions
Brunetti, Celso; Foley-Fisher, Nathan; Verani, Stéphane (2023-10-12)
Financial intermediaries manage myriad interest rate risk exposures. We propose a new method to measure financial intermediaries' residual interest rate risk using high-frequency financial market data. Our method exploits all available high-frequency information and is valid under extremely weak assumptions. Applying the method to U.S. life insurers, we find their interest rate risk management strategies are generally effective. However, life insurers are more sensitive to changes in long-term interest rates than property and casualty insurers. We show that the term premium helps to explain ...
Finance and Economics Discussion Series , Paper 2023-067

Working Paper
Skill and Efficiency in the U.S. Mutual Fund Industry
Oh, Dong Hwan; Patton, Andrew J. (2026-03-25)
We propose a new measure of mutual fund manager ability: "efficiency" is the ability to accrue the risk premium associated with a risk factor. The familiar abnormal return, or alpha, is shown to be the sum of two distinct measures of ability: "aggregate efficiency" which is the beta-weighted sum of the fund's (in)efficiencies across risk factors, and "skill," the component that is unrelated to factor exposures. Using a panel of U.S. equity mutual fund returns from 1999-2023, we document significant heterogeneity in mutual fund manager skill and efficiency. We employ regression trees and their ...
Finance and Economics Discussion Series , Paper 2026-032

Working Paper
Fed-Driven Systemic Tail Risk: High-Frequency Measurement, Evidence and Implications
Yang, Xiye; Neely, Christopher J.; Erdemlioglu, Deniz (2025-03-30)
We develop a framework to measure market-wide (systemic) tail risk in the cross-section of asset returns. Using high-frequency data on individual U.S. stocks and sector-specific ETF portfolios, we estimate time-varying jump intensities and multi-asset tail risk around Fed policy announcements. While most FOMC announcements generate systemic left-tail risk, there is no evidence that macro announcements have a similar effect. The magnitude of the tail risk induced by Fed policy announcements varies over the business cycle, peaks during the global financial crisis and remains high during phases ...
Working Papers , Paper 2023-016

Working Paper
High-Dimensional Copula-Based Distributions with Mixed Frequency Data
Patton, Andrew J.; Oh, Dong Hwan (2015-05-19)
This paper proposes a new model for high-dimensional distributions of asset returns that utilizes mixed frequency data and copulas. The dependence between returns is decomposed into linear and nonlinear components, enabling the use of high frequency data to accurately forecast linear dependence, and a new class of copulas designed to capture nonlinear dependence among the resulting uncorrelated, low frequency, residuals. Estimation of the new class of copulas is conducted using composite likelihood, facilitating applications involving hundreds of variables. In- and out-of-sample tests confirm ...
Finance and Economics Discussion Series , Paper 2015-50

Working Paper
CONSUMER LENDING EFFICIENCY:COMMERCIAL BANKS VERSUS A FINTECH LENDER
Jagtiani, Julapa; Hughes, Joseph P.; Moon, Choon-Geol (2019-04-02)
We compare the performance of unsecured personal installment loans made by traditional bank lenders with that of LendingClub, using a stochastic frontier estimation technique to decompose the observed nonperforming loans into three components. The first is the best-practice minimum ratio that a lender could achieve if it were fully efficient at credit-risk evaluation and loan management. The second is a ratio that reflects the difference between the observed ratio (adjusted for noise) and the minimum ratio that gauges the lender?s relative proficiency at credit analysis and loan monitoring. ...
Working Papers , Paper 19-22

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