QRFE Seminar Series
Nuclear Norm Regularized Estimation of Panel Regression Model
Dr. Martin Weidner, from the University College London, will be present: Nuclear Norm Regularized Estimation of Panel Regression Model
Lunch: 12:30PM inMHL 418.
For the first QRFE seminar of the year, We have Ilaria Piatti, from Oxford Business School, Associate Professor of Finance, talking about Rationality and Subjective Bond Risk Premia.
For further information on Ilaria Piatti here.
The complex tail dependency structure in a dynamic network with a large number of nodes is an important object to study. Here we propose a network quantile autoregression model (NQAR), which characterizes the dynamic quantile behavior.
While a large literature on return predictability has shown a link between valuation levels and expected rates of returns, we document a robust link between valuation levels and the shape of the distribution of cumulative (up to 24 months) total returns.
Recessions are often accompanied by spikes of corporate default and prolonged declines of business credit.
Empirical evidence suggests that investor protection affects asset prices. We develop a dynamic asset pricing model to shed light on the empirical regularities and underlying mechanisms at play.
Abstract: We propose a method to explore the causal transmission of a catalyst variable through two endogenous variables of interest. The method is based on the reduced-form system formed from the conditional distribution of the two endogenous variables given the catalyst.
A QRFE research seminar.
This paper studies empirically the relation between macro uncertainty shocks and the cross-section of currency excess returns.
The bootstrap is typically much less reliable in the context of time-series models with serial correlation of unknown form than it is when regularity conditions for the conventional IID bootstrap, based on resampling, apply.
This paper introduces a model with regime switching, which is driven by an autoregressive latent factor correlated with the innovation to the observed time series.
The main contribution of this paper is to study the applicability of the bootstrap to estimating the distribution of the standard test of overidentifying restrictions of Hansen (1982) when the model is globally identified but the rank condition fails to hold (lack of first order local identification).
We present a dynamic agency model of investment, borrowing and payout decisions by a mature corporation operating in perfect financial markets. Risk-averse managers implement an inter-temporal strategy that maximizes their lifetime utility of managerial rents.