E. Scott Mayfield

On Determining the Dimension of Real-Time Stock-Price Data

The authors estimate the dimension of high-frequency stock-price data using the correlation integral of P. Grassberger and I. Procaccia. The data, even after filtering, appear to be of low dimension. To control for dependence in higher moments, the authors use a new technique known as the method of delays in their reconstruction. Delaying the data leads dimension estimates similar to random processes. They conclude that the data are either of low dimension with high entropy or nonlinear but of high dimension.

Interest rate parity and the exchange risk premium Evidence from panel data

This paper provides evidence that a time-varying risk premium is responsible for the rejection of the interest rate parity theory. We us a panel data set of returns on the Eurocurrency deposits and employ cross-section / time series methods to account for common movements in risk premia across deposits denominated in different currencies.

Explaining The Term Structure Of Interest Rates: A Panel Data Approach

This paper demonstrates that a time-varying risk premium can account for the rejection of the expectations theory of the term structure of interest rates. Rather than model risks directly, in terms of observables, we instead exploit an implication of the capital asset pricing model concerning how risk premia for a given maturity structure will vary through time in a related manner across different types of assets. We use a panel data set of returns on Eurocurrency deposits and employ cross-section/time-series methods to account for related movements in risk premia across assets that differ by currency denomination. We find that our ability to explain the term structure of interest rates is greatly improved by allowing for these unobserved but related movements in risk premia. In addition, the methodology developed in this paper can be used to model time-varying risk premia when studying other types of present-value relationships in financial markets.