We review the past 25 years of time series research that has been published in journals managed by the International Institute of Forecasters (Journal of Forecasting 1982-1985; International Journal of Forecasting 1985-2005). During this period, over one third of all papers_new published in these...

We review the past 25 years of time series research that has been published in journals managed by the International Institute of Forecasters (Journal of Forecasting 1982-1985; International Journal of Forecasting 1985-2005). During this period, over one third of all papers_new published in these...

In this paper I introduce quantile spectral densities that summarize the cyclical behavior of time series across their whole distribution by analyzing periodicities in quantile crossings. This approach can capture systematic changes in the impact of cycles on the distribution of a time series...

This paper shows through regression simulations that, when there are two highly collinear regressors, at least one of which has a simultaneous relationship with the dependent variable, t-ratios typically do not decline to non-significance as text book theory predicts. Coefficients and/or...

We investigate whether outliers in cross-country samples and the common methods we use to address them affect the trustworthiness of our empirical results. Our analysis begins by documenting recent international business (IB) research practices in the identification and treatment of outliers. We...

We show that the presence of short-term overreaction in a stock price could make estimates of the conditional moments of stock returns be strongly affected by the frequency of time series. This conclusion implies that the other measures of stock returns, such as the conditional Sharpe ratio, its...

I introduce the time-varying GARCH-in-mean (TVGARCH-in-mean) model and propose an estimation strategy for the stochastic time-varying risk premium parameter. A Monte Carlo study shows that the proposed algorithm has good finite sample properties. Using monthly excess returns on the CRSP index, I...

Textbook theory predicts that t-ratios decline towards zero in regressions when there is collinearity between two regressors. This paper shows that this often does not occur if the regression suffers from simultaneity or omitted variable bias. With more collinearity, t-ratios generally increase...

High dimensional composite index makes experts' preferences in setting weights a hard task. In the literature, one of the approaches to derive weights from a data set is Principal Component or Factor Analysis that, although conceptually different, they are similar in results when FA is based on...