The ordinary least squares (OLS) estimator for spatial autoregressions may be consistent as pointed out by Lee (2002), provided that each spatial unit is influenced aggregately by a significant portion of the total units. This paper presents a unified asymptotic distribution result of the...

The sample average is an unbiased estimator of the population mean, so it may seem innocuous that for estimating model parameters that do not involve the population mean, the data can be demeaned first. Using a first-order moving average (MA) model for example, we derive the analytical...

We develop the analytical second-order bias and variance of the estimated Sharpe ratio when the return series is not IID. We show that the bias and variance formulae depend upon the covariance structure of the data generating process

The issue of whether the new one-sided procedures for testing inequalities dominate the classical procedure in terms of power remains unresolved in the literature. The Monte Carlo results in this study suggest a theoretical approach that could provide an analytical resolution

We study the sample estimation risk of the traditional Sharpe ratio without the restrictive assumption of normality for return series. We derive analytical results for the approximate bias and variance of the sample Sharpe ratio in terms of the underlying distribution parameters. The results...