We develop a new parametric bootstrap-based statistical test for presence of futures price and options-based implied volatility biases. The new test is applicable to data with overlapping prediction horizons. Information on anticipated volatility embedded in options prices is explicitly used...

In the period leading up to the start of the Margin Protection Program for Dairy Producers (MPP-Dairy), a survey was undertaken to assess dairy farmer knowledge, attitudes, impressions and expected participation decisions. All surveys were collected in July and August 2014. There are six main...

Livestock Gross Margin Insurance for Dairy Cattle (LGM-Dairy) is a recently introduced tool for protecting average income over feed cost margins in milk production. In this paper we examine the assumptions underpinning the rating method used to determine premiums charged for LGM-Dairy insurance...

In this analysis we compare the total expected government outlays and distribution of benefits under newly proposed dairy margin insurance programs to those under existing counter-cyclical payment programs. We combine simulation and structural modeling techniques to forecast milk price and dairy...

This study examines the risk management opportunities for fluid milk market participants in the United States through the use of milk futures contracts. We estimate the nature of basis risk from 2002–2011 using modern time-series and econometric techniques. The results of this investigation...

With increased volatility of feed prices dairy farm managers are no longer concerned with managing just milk price volatility but are considering the adoption of risk management programs that address income over feed cost (IOFC) margin risk. Successful margin risk management should be founded on...

A common approach in the literature, whether the investigation is about futures price risk premiums or biases in option-based implied volatility coefficients, is to use samples in which consecutive observations can be regarded as uncorrelated. That will be the case for non- overlapping forecast...