The contribution of a satellite market to price discovery: Evidence from the Singapore exchange

The Singapore Exchange (SGX), a small satellite market, successfully competes with a large home market, the Osaka Securities Exchange (OSE), in trading the Nikkei 225 futures index. In this paper, we investigate the contribution of the SGX to price discovery and shed light on the reasons for its continued success. Evidence is provided from information revelation and price discovery of three competing but informationally linked markets of the Nikkei 225 index—domestic spot (Tokyo Stock Exchange), domestic futures (OSE), and foreign futures (SGX), which represents the satellite market. Overall, the futures market contributes 77% to price discovery, with the satellite market contributing 42% of the futures and 33% of the total price discovery. These figures, surprisingly, far exceed the satellite market's share of trading volume. Support is provided for the extended trading hours on the SGX for three of the four non‐overlapping trading sub‐periods. © 2004 Wiley Periodicals, Inc. Jrl Fut Mark 24:981–1004, 2004     

Contract modifications and the basis behavior of live cattle futures

The purpose of this study was to assess the basis behavior of the Live Cattle Futures contract at the Chicago Mercantile Exchange (CME) before and after the 1995 contract changes. Additionally, an alternative method of basis calculation utilizing weighted mean futures prices versus settlement futures prices was compared to determine which method provides a better representation of the basis level. Within a regression model with heteroskedascity error framework, we found that the level of nearby basis in the period after June 1995 has shifted lower and the average monthly open interest of net commercial long positions has substantially increased after the contract modifications. These empirical results are consistent with the notion that more long activity entered the market in response to the contract modifications. Additionally, an alternative (new) measure of basis calculation (cash price minus weighted mean futures price) produced similar results to two other commonly used measures. In conclusion, the 1995 contract changes have neither increased nor decreased the volatility of live cattle basis. © 2004 Wiley Periodicals, Inc. Jrl Fut Mark 24:557–590, 2004     

A note on price futures versus revenue futures contracts

Here we consider the hedging roles of a price futures contract versus a revenue futures contract. In the absence of idiosyncratic output risk, the revenue contract almost always dominates the price contract. Idiosyncratic output risk provides conditions under which the price contract should dominate. When production risk is largely idiosyncratic, a producer with an anticipated long actuals position might combine a long revenue futures position with a short price futures position. © 2004 Wiley Periodicals, Inc. Jrl Fut Mark 24:503–512, 2004     

CROSS‐DOCKING AND ITS IMPLICATIONS IN LOCATION‐DISTRIBUTION SYSTEMS

Cross‐docking replaces traditional warehousing, enabling continuous flow of items without storage. Here we model location‐distribution networks, that include cross‐docking facilities, to obtain the latter's impact on the supply chain. We formulate optimization models to minimize total cost in three multi‐echelon networks, each model generalizing the preceding one. The first includes a single manufacturer, one product type, and multiple customers. Cross‐docks are to be located between origin and destinations. Besides solving optimally, a tool for quantitative analysis of direct‐shipment decisions is developed. The second model considers more than one product: We determine a cost‐effective sequence of items for indirect shipment (via cross‐docks). Finally, in a network with multiple origins, optimal solutions are obtained for 40 medium‐sized and larger examples.     

EXPRESSING INVENTORY CONTROL POLICY IN THE TURNOVER CURVE

Estimation of the inventory level for an entire class of items is a valuable time saver when control of inventories at the aggregate level, rather than the item level, is of interest. Inventory approximation by location in supply chain network configuration and evaluation of inventory control policy shifts, are two examples of application. In this article, various popular inventory policies are related to a general function known as an inventory turnover curve that expresses inventory levels from the combined demand of multiple items. By knowing some basic item characteristics of representative items in a product class, the type of inventory policy being used, and the current aggregate inventory level, an inventory turnover curve can be constructed. This resulting turnover curve can be used to estimate inventory levels within 4.6%, on the average, of theoretically predicted ones.