Keynote speakers of the JEF'2021 Conference

Title: Tail Heterogeneity for Dynamic Covariance-Matrix-Valued Random Variables: the F-Riesz Distribution

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Summary: Heterogeneity of tail behavior in multivariate modeling in finance is a long standing challenge. This talk provides what might be a major step forward in this regard, particularly for modeling realized covariance matrix data. We introduce the new F-Riesz distribution to model tail-heterogeneity. In contrast to the typical matrix-valued distributions from the econometric literature, the F-Riesz distribution allows for different tail behavior across all variables in the system. We show how the distribution can be derived and easily simulated from. We also study the consistency properties of the maximum likelihood estimator in both static and dynamic models with F- Riesz innovations using both one-step and two-step (targeting) estimation techniques. Allowing for tail-heterogeneity when modeling covariance matrices appears empirically highly relevant. When applying the new distribution to realized covariance matrices of 30 U.S. stocks over a 14 year period, we find huge likelihood increases both in-sample and out-of-sample compared to all competing distributions, including the Wishart, inverse Wishart, Riesz, inverse Riesz, and matrix-F distribution. This provides promising avenues for future research.

Title: A penalized two-pass regression to predict stock returns with time-varying risk premia

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Summary: We develop a penalized two-pass regression with time-varying factor loadings. The penalization in the first pass enforces sparsity for the time-variation drivers while also maintaining compatibility with the no arbitrage restrictions by regularizing appropriate groups of coefficients. The second pass delivers risk premia estimates to predict equity excess returns. Our Monte Carlo results and our empirical results on a large cross-sectional data set of US individual stocks show that penalization without grouping can yield to nearly all estimated time-varying models violating the no arbitrage restrictions. Moreover, our results demonstrate that the proposed method reduces the prediction errors compared to a penalized approach without appropriate grouping or a time-invariant factor model.

Title: Nonparametric instrumental regression with right censored duration outcomes

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Summary: This paper analyzes the effect of a discrete treatment Z on a duration T. The treatment is not randomly assigned. The confounding issue is treated using a discrete instrumental variable explaining the treatment and independent of the error term of the model. Our framework is nonparametric and allows for random right censoring. This specification generates a nonlinear inverse problem and the average treatment effect is derived from its solution. We provide local and global identification properties that rely on a nonlinear system of equations. We propose an estimation procedure to solve this system and derive rates of convergence and conditions under which the estimator is asymptotically normal. When censoring makes identification fail, we develop partial identification results. Our estimators exhibit good finite sample properties in simulations. We also apply our methodology to the Illinois Reemployment Bonus Experiment.

Title: Unconventional Monetary Policy and Bond Market Connectedness in the New Normal

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Summary: The unconventional monetary policy (UMP) interventions of the major central banks have had remarkable financial and real economic effects worldwide since the global financial crisis. This study offers a framework to analyze the impact of UMPs on sovereign bond market return connectedness across countries and maturities. Our results help us identify the impact of some of the important policy interventions. The Fed's Operation Twist program of 2011 was effective in reducing the within-maturity connectedness of long-term bonds while increasing the within-maturity connectedness of short-term bonds. The Taper Tantrum of 2013 and the ECB’s policy convergence towards other major central banks in 2015 shaped the bond market return linkages afterward: The long-term connectedness increased and surpassed the short-term connectedness across countries, and the dispersion of the within-maturity connectedness decreased substantially. Finally, we use panel regressions to analyze the impact of monetary policy interventions on pairwise bond return connectedness along with other factors, such as the distance, trade, and portfolio investment flows between pairs of countries. In particular, we show that UMPs increased the pairwise long-term bond return connectedness over time.