A market-augmented model for SIMEX Brent crude oil futures contracts

Brent crude oil futures contracts are traded on both the Singapore International Monetary Exchange (SIMEX) and the International Petroleum Exchange (IPE). Through a mutual offset system between SIMEX and IPE, Brent crude oil futures contracts can be traded up to nineteen hours each day. The inter-re...

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Bibliographic Details
Main Authors: SEQUEIRA, J. M., McALEER, Michael
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2000
Subjects:
Online Access:https://ink.library.smu.edu.sg/lkcsb_research/5076
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Institution: Singapore Management University
Language: English
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Summary:Brent crude oil futures contracts are traded on both the Singapore International Monetary Exchange (SIMEX) and the International Petroleum Exchange (IPE). Through a mutual offset system between SIMEX and IPE, Brent crude oil futures contracts can be traded up to nineteen hours each day. The inter-relationship between the two futures contracts, the spot price of Brent crude oil and the riskfree interest rate, suggest the existence of cointegration among SIMEX Brent crude oil futures prices, lagged IPE Brent crude oil futures prices, Brent spot prices and the London Inter-bank Offer Rate (LIBOR). Error-correction representations of two standard futures pricing models, namely the unbiased expectations and cost-of-carry hypotheses, are formulated for SIMEX Brent crude oil futures contracts. These formulations are augmented by including the lagged IPE futures price in the mispricing error. The resulting Augmented Unbiased Expectations Hypothesis (AUEH) and the Augmented Cost-of-Carry (ACOC) models are estimated and tested against each other, and also against the standard unbiased expectations and cost-of-carry models, using nested and non-nested testing procedures. Forecasting comparisons are also made among the various models and the autoregressive integrated moving average models fitted to SIMEX Brent crude oil futures prices. Results from the nonnested tests and the forecasting criteria show clearly that the augmented models outperform their standard (non-augmented) counterparts.