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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
The Term Structure and Inflation Uncertainty
D'Amico, Stefania; Orphanides, Athanasios; Breach , Tomas (2016-12-12)
This paper develops and estimates a Quadratic-Gaussian model of the U.S. term structure that can accommodate the rich dynamics of inflation risk premia over the 1983-2013 period by allowing for time-varying market prices of inflation risk and incorporating survey information on inflation uncertainty in the estimation. The model captures changes in premia over very diverse periods, from the inflation scare episodes of the 1980s, when perceived inflation uncertainty was high, to the more recent episodes of negative premia, when perceived inflation uncertainty has been considerably smaller. A ...
Working Paper Series , Paper WP-2016-22

Working Paper
Mildly Explosive Dynamics in U.S. Fixed Income Markets
Contessi, Silvio; De Pace, Pierangelo; Guidolin, Massimo (2017-08-01)
We use a recently developed right-tail variation of the Augmented Dickey-Fuller unit root test to identify and date-stamp periods of mildly explosive behavior in the weekly time series of seven U.S. fixed income yield spreads between September 2002 and January 2015. We find statistically significant evidence of such behavior in six of these spreads. Mild explosivity migrates from short-term funding markets to more volatile medium- and long-term markets during the Great Financial Crisis. For some markets, we statistically validate the conjecture, originally suggested by Gorton (2009a,b), that ...
Globalization Institute Working Papers , Paper 324

Working Paper
The Contribution of Jump Activity and Sign to Forecasting Stock Price Volatility
Murphy, Anthony; Hizmeri, Rodrigo; Bu, Ruijun; Tsionas, Mike G.; Izzeldin, Marwan (2020-11-17)
This paper proposes a novel approach to decompose realized jump measures by type of activity (finite/infinite) and by sign. We also provide noise-robust versions of the ABD jump test (Andersen et al. 2007) and realized semivariance measures for use at high frequency sampling intervals. The volatility forecasting exercise involves the use of different types of jumps, forecast horizons, sampling frequencies, calendar and transaction time-based sampling schemes, as well as standard and noise-robust volatility measures. We find that infinite (finite) jumps improve the forecasts at shorter ...
Working Papers , Paper 1902

Working Paper
Regular Variation of Popular GARCH Processes Allowing for Distributional Asymmetry
Prono, Todd (2017-09-22)
Linear GARCH(1,1) and threshold GARCH(1,1) processes are established as regularly varying, meaning their heavy tails are Pareto like, under conditions that allow the innovations from the, respective, processes to be skewed. Skewness is considered a stylized fact for many financial returns assumed to follow GARCH-type processes. The result in this note aids in establishing the asymptotic properties of certain GARCH estimators proposed in the literature.
Finance and Economics Discussion Series , Paper 2017-095

Working Paper
Better the Devil You Know: Improved Forecasts from Imperfect Models
Oh, Dong Hwan; Patton, Andrew J. (2021-11-05)
Many important economic decisions are based on a parametric forecasting model that is known to be good but imperfect. We propose methods to improve out-of-sample forecasts from a mis- specied model by estimating its parameters using a form of local M estimation (thereby nesting local OLS and local MLE), drawing on information from a state variable that is correlated with the misspecication of the model. We theoretically consider the forecast environments in which our approach is likely to o¤er improvements over standard methods, and we nd signicant fore- cast improvements from ...
Finance and Economics Discussion Series , Paper 2021-071

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
Interconnectedness in the Corporate Bond Market
Brunetti, Celso; Carl, Matthew; Gerszten, Jacob; Scotti, Chiara; Shin, Chaehee (2024-08-16)
Does interconnectedness improve market quality? Yes.We develop an alternative network structure, the assets network: assets are connected if they are held by the same investors. We use several large datasets to build the assets network for the corporate bond market. Through careful identification strategies based on the COVID-19 shock and “fallen angels,” we find that interconnectedness improves market quality especially during stress periods. Our findings contribute to the debate on the role of interconnectedness in financial markets and show that highly interconnected corporate bonds ...
Finance and Economics Discussion Series , Paper 2024-066

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