In this paper we describe a solution to the problem of controlling the size of homoskedasticity tests in linear regression contexts.

Models use for natural resources prices usually preclude the possibility of large changes (jumps) resulting from discrete, unexpected events. To test for the presence of jumps and ARCH effects, we propose to use bounds and bootstrap test techniques, thus solving the unidentified nuisance...

We use the Monte-Carlo (MC) test technique to find valid p-values when testing for discontinuities in jump-diffusion models. While the distribution of the LR statistic for this test is typically non-standard, we show that the MC p-value is finite sample exact if no other (identified) nuisance...