We analyse the well-known TORQ dataset of trades on the NYSE over a 3-month period, breaking down transactions depending on whether the active or passive side was institutional or private. This allows us to compare the returns on the different trade categories. We find that, however we analyse...

We examine whether consumer confidence - as a proxy for individual investor sentiment - affects expected stock returns internationally in 18 industrialized countries. In line with recent evidence for the U.S., we find that sentiment negatively forecasts aggregate stock market returns on average...

We use weekly survey data on short-term and medium-term sentiment of German investors in order to study the causal relationship between investors' mood and subsequent stock price changes. In contrast to extant literature for other countries, a tri-variate vector autoregression for short-run...

We develop an agent-based financial market model in which agents follow technical and fundamental trading rules to determine their speculative investment positions. A central feature of our model is that we consider direct interactions between speculators due to which they may decide to change...

Previous evidence suggests that less liquid stocks entail higher average returns. Using NYSE data, we present evidence that both the sensitivity of returns to liquidity and liquidity premia have significantly declined over the past four decades to levels that we cannot statistically distinguish...

This paper studies the effects of FOMC communication on U.S. financial markets’ returns and volatility using a GARCH model over the period from 1998 to 2006. We build a new data set that includes information on all FOMC speeches, post-meeting statements, monetary policy reports and...

Using a GARCH model, we study the effects of Federal Funds target rate changes and FOMC communication on emerging equity market returns and volatility over the period 1998–2006. First, both types of news have a significant impact on market returns. Second, target rate changes are more...

Daily financial market returns (as log difference in closing prices) may be quite sensitive to operation with low trading volumes and big changes in prices frequently traded at market closing times. This paper proposes a more robust estimation of market returns by providing a new indicator that...

We present a new matrix-logarithm model of the realized covariance matrix of stock returns. The model uses latent factors which are functions of both lagged volatility and returns. The model has several advantages: it is parsimonious; it does not require imposing parameter restrictions; and, it...

This paper investigates whether investor sentiment can explain stock returns on the German stock market. Based on a principal component analysis, we construct a sentiment indicator that condenses information of several well-known sentiment proxies. We show that this indicator explains the return...