We propose a shrinkage and selection methodology specifically designed for network inference using high dimensional data through a regularised linear regression model with Spike-and-Slab prior on the parameters. The approach extends the case where the error terms are heteroscedastic, by adding...

The real estate market in China has been growing rapidly during the past decade, with different property price patterns across various regions. Among different types of properties, prices of retail properties have not been sufficiently analyzed. This study focuses on forecasting problems of...

We explore the performance of mixed-frequency predictive regressions for stock returns from the perspective of a Bayesian investor. We develop a constrained parameter learning approach for sequential estimation allowing for belief revisions. Empirically, we find that mixed-frequency models...