The forecasting literature has identi ed two important issues: (i) several predictors have substantial and statistically signi cant predictive content, although only sporadically, and it is unclear whether this predictive content can be exploited reliably; (ii) in-sample predictive content does...

Much of the trading activity in Equity markets is directed to brokerage houses. In exchange they provide so-called quot;soft dollarsquot; which basically are amounts spent in quot;researchquot; for identifying profitable trading opportunities. Soft dollars represent about USD 1 out of every USD...

The short article is focused on four issues associated with challenges in estimating and forecasting economic trends during financial crises: difficulties in forecasting the eruption of a large-scaled financial crisis, evaluation of some high-frequency modeling techniques, comparison of two...

We consider forecasting a single time series using high-dimensional predictors in the presence of a possible nonlinear forecast function. The sufficient forecasting (Fan et al., 2016) used sliced inverse regression to estimate lower-dimensional sufficient indices for non-parametric forecasting...

Providing a more accurate covariance matrix forecast can substantially improve the performance of optimized portfolios. Using out-of-sample tests, in this paper, we evaluate alternative covariance matrix forecasting methods by looking at (1) their forecast accuracy, (2) their ability to track...

It is a common understanding that bankruptcy is not a sudden occurrence for any organizations. Macro and micro economic studies have suggested numerous influential factors, which have substantial evidence toward firm's performance (Bekeris, 2012) and survivability (Nehrebecka & Dzik, 2013). With...

This article evaluates and compares the forecasting performance of three international organizations: the United Nations, the International Monetary Fund and the World Bank. The annual forecasts made by the United Nations in the period of 1981-2011 are found to be fairly robust, in terms of bias...

We consider forecasting a single time series when there is a large number of predictors and a possible nonlinear effect. The dimensionality was first reduced via a high-dimensional factor model implemented by the principal component analysis. Using the extracted factors, we develop a link-free...

In this research note we report on our current efforts on developing a leading indicator of housing prices that could be used to forecast housing prices. Specifically we use Google search index at city level to predict Case-Shiller index. The methodology is based on Granger causality where we...

How can information on financial conditions be used to better understand macroeconomic developments and improve macroeconomic projections? We investigate this question for France by constructing country-specific financial conditions indices (FCIs) that are tailored to movements in GDP,...