We present a unifying identification strategy of dynamic average treatment effect parameters for staggered interventions when parallel trends are valid only after controlling for interactive fixed effects. This setting nests the usual parallel trends assumption, but allows treated units to have...

We establish a framework to study the factor structure in stock variance under a high-frequency and high-dimensional setup. We prove the consistency of conducting principal component analysis on realized variances in estimating the factor structure. Moreover, based on strong empirical evidence,...

How does the predictability of future noisy flows impact asset prices? We answer this question by developing a dynamic multi-asset price impact model. The model setup is general---both flows and fundamental returns can be correlated for the cross-section of assets, and flows can exhibit a...

A low frequency factor model regression uses returns computed at a lower frequency than data available. An example is using monthly rather than daily returns to estimate the Capital Asset Pricing Model (CAPM). I show that when using overlapping observations to estimate low frequency factor model...

In the paper the analysis of current conditions of the financial market of Russian Federation is performed. The principal components analysis is applied to analyze and obtain the simulation coefficients for government bonds as indicators and numeric features of digital twin modelling of regions...

While the level of disparities across regions in 10 advanced European economies studied in this paper mostly reflects productivity gaps, the increase since the Great Recession has resulted from diverging unemployment rates. Following the pandemic, this could be further exacerbated given...

We develop a novel approach based on the generalised canonical correlation (GCC) analysis to consistently estimating the multilevel factor model and providing the proper inference theory for the high dimensional panel data. Importantly, our approach is shown to be robust to a non-zero...

Asset returns exhibit grouped heterogeneity, and a “one-size-fits-all” model has been elusive empirically. This paper proposes a Bayesian Clustering Model (BCM) combining Bayesian factor selection and panel tree for asset clustering. The Bayesian model marginal likelihood guides the tree...

In recent years, road construction projects in Egypt have experienced significant cost overruns. This has coincided with a remarkable increase in the volume and capacity of road construction in Egypt over the last two decades. Consequently, there is an urgent need for a systematic analysis of...

This letter applies Siniscalchi (2009)’s Vector Expected Utility to introduce ambiguity aversion into factor models for assets’ returns. The resulting criterion is tractable and its adjustment for ambiguity vanishes as initial wealth increases. Finally, it can be related to shrinkage...