The complexity of machine learning models presents a substantial barrier to their adoption for many investors. The algorithms that generate machine learning predictions are sometimes regarded as “black box”, demanding interpretation and additional explanation. In this paper, we present a...

Statistical learning models have profoundly changed the rules of trading on the stock exchange. Quantitative analysts try to utilise them predict potential profits and risks in a better manner. However, the available studies are mostly focused on testing the increasingly complex machine learning...

A large set of financial variables has only limited power to predict a latent factor common to the year-ahead forecast errors for real Gross Domestic Product (GDP) growth, the unemployment rate, and Consumer Price Index (CPI) inflation for three sets of professional forecasters: the Federal...

A large set of financial variables has only limited power to predict a latent factor common to the year-ahead forecast errors for real Gross Domestic Product (GDP) growth, the unemployment rate, and Consumer Price Index (CPI) inflation for three sets of professional forecasters: the Federal...

We present a factor augmented forecasting model for assessing the financial vulnerability in Korea. Dynamic factor models often extract latent common factors from a large panel of time series data via the method of the principal components (PC). Instead, we employ the partial least squares (PLS)...

When do financial markets help in predicting economic activity? With incomplete markets, the link between financial and real economy is state-dependent and financial indicators may turn out to be useful particularly in forecasting "tail" macroeconomic events. We examine this conjecture by...

A consensus has recently emerged that a number of variables in addition to the level, slope, and curvature of the term structure can help predict interest rates and excess bond returns. We demonstrate that the statistical tests that have been used to support this conclusion are subject to very...

A 'lost decade' for the Eurozone is looming on the horizon. Under these circumstances, stable indicators for future economic activity are especially valuable to decision makers. This paper examines the predictive power of the yield spread, one of the most reliable indicators for gross domestic...

An OLS and probit framework is used to examine the predictive power of yield spreads with respect to GDP growth and recessions in the Eurozone from the 1990s to the recent past. Credit default swap (CDS) data on sovereign bonds, which provide a direct measure of default risk, are employed as...