Optimal Test for Parameter Instability When the Unstable Process and the Error Distribution are Unknown

This paper proposes asymptotically optimal tests for unstable parameter process under the feasible circumstance that the researcher has little information about the unstable parameter process and the error distribution, and suggests conditions under which the knowledge of those processes does not provide asymptotic power gains. I first derive a test under known error distribution, which is asymptotically equivalent to LR tests for correctly identified unstable parameter processes under suitable conditions. The conditions are weak enough to cover a wide range of unstable processes such as various types of structural breaks and time varying parameter processes. The test is then extended to semiparametric models in which the underlying distribution in unknown but treated as unknown infinite dimensional nuisance parameter. The semiparametric test is adaptive in the sense that its asymptotic power function is equivalent to the power envelope under known error distribution.

US Corporate Default Swap Valuation: The Market Liquidity Hypothesis and Autonomous Credit Risk

This paper develops a reduced form three-factor model which includes a liquidity proxy of market conditions which is then used to provide implicit prices. The model prices are then compared with observed market prices of credit default swaps to determine if swap rates adequately reflect market risks. The findings of the analysis illustrate the importance of liquidity in the valuation process. Moreover, market liquidity, a measure of investors. willingness to commit resources in the credit default swap (CDS) market, was also found to improve the valuation of investors. autonomous credit risk. Thus a failure to include a liquidity proxy could underestimate the implied autonomous credit risk. Autonomous credit risk is defined as the fractional credit risk which does not vary with changes in market risk and liquidity conditions.