We propose a new methodology to select a subset of assets for (partial) index replication, based on the latest research on factor models of large dimensions. Our method selects the set of leader stocks that can fully capture the systematic risk of the index to be replicated. Our selection...

A standard quantitative method to access credit risk employs a factor model based on joint multivariate normal distribution properties. By extending a one-factor Gaussian copula model to make a more accurate default forecast, this paper proposes to incorporate a state-dependent recovery rate...

We study equity premium out-of-sample predictability by extracting the information contained in a high number of macroeconomic predictors via large dimensional factor models. We compare the well known factor model with a static representation of the common components with a more general model...

Standard factor models focus on returns and leave prices undetermined. Thisapproach ignores information contained in the time-series of asset prices, relevantfor long-term investors and for detecting potential mispricing. To address this issue,we propose a novel (co-)integrated methodology to...

Purpose: The main aim of this research was to discuss the relationship between the patents and the performance of listed companies, more particularly, to find out whether China patent's claim impacted on China listed company's stock return rate or not. It was because the claim played the most...

We survey the literature on stock return forecasting, highlighting the challenges faced by forecasters as well as strategies for improving return forecasts. We focus on U.S. equity premium forecastability and illustrate key issues via an empirical application based on updated data. Some studies...

We study regime-specific systematic comovement between two large panels of variables that exhibit an approximate factor structure. Within each panel we identify threshold-type regimes through shifts in the factor loadings. For the resulting regimes, and with regard to the relation between any...

The asset allocation decision often relies upon correlation estimates arising from short-run data. Short-run correlation estimates may, however, be distorted by frictions. In this paper, we introduce a long-run wavelet-based correlation estimator, distinguishing between long-run common behavior...