Despite a large and growing theoretical literature on flights to safety, there does not appear to exist an empirical characterization of flight-to-safety (FTS) episodes. Using only data on bond and stock returns, we identify and characterize flight to safety episodes for 23 countries. On...

Despite a large and growing theoretical literature on flights to safety, there does not appear to exist an empirical characterization of flight-to-safety (FTS) episodes. Using only data on bond and stock returns, we identify and characterize flight to safety episodes for 23 countries. On...

We apply causality extraction (CE) algorithms on more than 36,000 articles from 2 major financial newspapers (WSJ, FT) and three major newswires (DJ, MNI Market News, Reuters) over the extended period 1980-2020 to shed light on the fundamental triggers of flights to safety. Our CE algorithm...

We identify flight-to-safety (FTS) days for 23 countries using only stock and bond returns and a model averaging approach. FTS days comprise less than 2% of the sample, and are associated with a 2.7% average bond-equity return differential and significant flows out of equity funds and into...

We identify flight-to-safety (FTS) days for 23 countries using only stock and bond returns and a model averaging approach. FTS days comprise less than 2% of the sample, and are associated with a 2.7% average bond-equity return differential and significant flows out of equity funds and into...

We identify flight-to-safety (FTS) days for 23 countries using only stock and bond returns and a model averaging approach. FTS days comprise less than 2% of the sample, and are associated with a 2.7% average bond-equity return differential and significant flows out of equity funds and into...

Using only daily data on bond and stock returns, we identify and characterize flight to safety (FTS) episodes for 23 countries. On average, FTS days comprise less than 3% of the sample, and bond returns exceed equity returns by 2.5 to 4%. The majority of FTS events are country-specific not...

We examine the performance of volatility models that incorporate features such as long (short) memory, regime-switching and multifractality along with two competing distributional assumptions of the error component, i.e. Normal vs Student-t. Our precise contribution is twofold. First, we...

We use weekly survey data on short-term and medium-term sentiment of German investors to estimate the parameters of a stochastic model of opinion dynamics. The bivariate nature of our data set also allows us to explore the interaction between the two hypothesized opinion formation processes,...

We investigate the predictability of both volatility and volume for a large sample of Japanese stocks. The particular emphasis of this paper is on assessing the performance of long memory time series models in comparison to their short-memory counterparts. Since long memory models should have a...