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...

This chapter surveys recent econometric methodologies for inference in large dimensional conditional factor models in finance. Changes in the business cycle and asset characteristics induce time variation in factor loadings and risk premia to be accounted for. The growing trend in the use of...

We analyze the dynamics, and the spatial distribution of nighttime light using the open source data of the Defense Meteorological Satellite Program of the U.S. Air Force. A detailed analysis of the relevant literature and our study of the database allow us to set up a best-practice for the use...

We present a detailed methodological study of the application of the modified profile likelihood method for the calibration of nonlinear financial models characterised by a large number of parameters. We apply the general approach to the Log-Periodic Power Law Singularity (LPPLS) model of...

Purpose – We use a large and rich data set consisting of over 123,000 single-family houses sold in Switzerland between 2005 and 2017 to investigate the accuracy and volatility of different methods for estimating and updating hedonic valuation models.Design/methodology/approach – We apply six...

This paper uses fractional cointegration analysis to examine whether long-run relations exist between securitized real estate returns and three sets of variables frequently used in the literature as the factors driving securitized real estate returns. That is, we examine whether such...