Parity conditions and the efficiency of the Australian 90- and 180-day forward markets

Covered Interest Parity (CIP) holds in the 90 and 180 forward market for the AUD/USD spot exchange rate provided fully modified least absolute deviation model (FM-LAD) procedures are applied to daily data for the period from December 2, 1985 to December 29, 2000. CIP fails if corrected ordinary least squares (OLS) and fully modified OLS (FM-OLS) procedures are applied. However, UIP fails in both markets on early data: December 2, 1985 to December 31, 1991, but holds in the 90-day market in a later subperiod: January 2, 1992 to December 29, 2000 FM. UIP is modified (M) to accommodate a potential risk premium. The MUIP model does not provide strong evidence suggesting the presence of a time-varying risk premium (TRP).     

Market risk model selection and medium-term risk with limited data: Application to ocean tanker freight markets

The estimation of medium-term market risk dictated by limited data availability, is a challenging issue of concern amongst academics and practitioners. This paper addresses the issue by exploiting the concepts of volatility and quantile scaling in order to determine the best method for extrapolating medium-term risk forecasts from high frequency data. Additionally, market risk model selection is investigated for a new dataset on ocean tanker freight rates, which refer to the income of the capital good — tanker vessels. Certain idiosyncrasies inherent in the very competitive shipping freight rate markets, such as excessive volatility, cyclicality of returns and the medium-term investment horizons – found in few other markets – make these issues challenging. Findings indicate that medium-term risk exposures can be estimated accurately by using an empirical scaling law which outperforms the conventional scaling laws of the square and tail index root of time. Regarding the market risk model selection for short-term investment horizons, findings contradict most studies on conventional financial assets: interestingly, freight rate market risk quantification favors simpler specifications, such as the GARCH and the historical simulation models.     

Decomposing swap spreads

We analyze a six-factor model for Treasury bonds, corporate bonds, and swap rates and decompose swap spreads into three components: a convenience yield from holding Treasuries, a credit risk element from the underlying LIBOR rate, and a factor specific to the swap market. The convenience yield is by far the largest component of spreads. There is a discernible contribution from credit risk as well as from a swap-specific factor with higher variability which in certain periods is related to hedging activity in the mortgage-backed security market. The model also sheds light on the relation between AA hazard rates and the spread between LIBOR rates and General Collateral repo rates and on the level of the riskless rate compared to swap and Treasury rates.