An examination of the necessary and sufJicient conditions for market eflciency: the case of hogs
- 1 January 1989
- journal article
- Published by Taylor & Francis in Applied Economics
- Vol. 21 (2) , 193-204
- https://doi.org/10.1080/758532403
Abstract
The pricing efficiency of the live hog futures market is examined utilizing both necessary and sufficient conditions. Out-of-sample forecasts from an econometric model, an ARIMA model and a composite forecasting model are compared with the forward prices of the futures market within a mean squared error framework. At least one model, and frequently all of them, forecast more accurately than the futures market, a necessary condition for market efficiency. The sufficient condition is assessed using simulated market trading strategies based o,n the most accurate model forecasts. Results suggest that informational inefficiencies exist in the live hog futures market.Keywords
This publication has 14 references indexed in Scilit:
- More on the Speed of Adjustment in Inventory ModelsJournal of Money, Credit and Banking, 1986
- Joint Production, Quasi-Fixed Factors of Production, and Investment in Finished Goods InventoriesJournal of Money, Credit and Banking, 1984
- Inventory Demand and Cost of Capital EffectsThe Review of Economics and Statistics, 1980
- Inventory Behavior in Durable-Goods Manufacturing: The Target-Adjustment ModelBrookings Papers on Economic Activity, 1976
- Time Series versus Structural Models: A Case Study of Canadian Manufacturing Inventory BehaviorInternational Economic Review, 1975
- Cost of Capital and Inventory Investment: Further EvidenceSouthern Economic Journal, 1973
- Expected Sales, Actual Sales, and Inventory-Investment RealizationJournal of Political Economy, 1966
- The Relevance of Sales Anticipatory Data in Explaining Inventory InvestmentInternational Economic Review, 1965
- Estimators for Seemingly Unrelated Regression Equations: Some Exact Finite Sample ResultsJournal of the American Statistical Association, 1963
- An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation BiasJournal of the American Statistical Association, 1962