This paper examines the joint process for volume and volatility. Locallinear models are used to analyze stability of the joint processes in different regions of volatility-volume space. It is found that this way of looking at the series changes dramatically the results found by using a global...

This paper documents a relation between the persistence of stock returns for a large firm index and trading volume. Previous results on the negative relation between volume and persistence are replicated, but a second effect is discovered. Persistence is directly related to the current rate of...

Chaos theory has touched on such fields as biology, cognitive science, and physics. By providing a unified and complete explanation of new statistical methods that are useful for testing for chaos in data sets, Brock, Hsieh, and LeBaron show how the principles of chaos theory can be applied to...

Equity market crashes or booms are extreme realizations of the underlying return distribution. This paper questions whether booms are more or less likely than crashes and whether emerging markets crash more frequently than developed equity markets. We apply Extreme Value Theory (EVT) to...

We present a new method, inspired by the bootstrap, whose goal it is to determine the quality and reliability of a neural network predictor. Our method leads to more robust forecasting along with a large amount of statistical information on forecast performance that we exploit. We exhibit the...

This paper uses an agent based financial market calibrated to aggregate data. It shows how these markets are able to magnify the volatility of fundamentals, and to create time series with persistent volatility. The mechanism for this persistence is explored using several of the time series...