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Record W22282666 · doi:10.15173/esr.v12i1.452

Backwardation in Energy Future Markets: Metallgesellschaft Revisited

2003· article· en· W22282666 on OpenAlex
Narat Charupat, Richard Deaves

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueEnergy Studies Review · 2003
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCapital Investment and Risk Analysis
Canadian institutionsMcMaster University
Fundersnot available
KeywordsNormal backwardationFutures contractMargin (machine learning)Convenience yieldContangoEconomicsSet (abstract data type)Financial economicsEconometricsSpot contractActuarial scienceComputer science

Abstract

fetched live from OpenAlex

In this paper, we revisit the debate on the merits of the stack-and-roll hedging strategy employed by Metallgesellschaft's American subsidiary, MGRM. Since the profitability of this hedging strategy depends on whether or not backwardation was the norm in energy futures contracts, we first provide the evidence on backwardation with an updated data set. We then examine the two major risks that such a hedging strategy faces margin call risk due to price declines and contango risk. Based on the data up to 1992, we find that the strategy could be expected to be profitable while the risks were not very high. Based on the updated data (up to 2000), the program's expected profits are smaller but still significant, however, the risks are higher. The probabilities of encountering a similar problem to the one MGRM faced are twice as high with the updated data than with the data up to 1992. In other words, the risk-return pattern of such a strategy is less appealing now than when MGRM implemented its hedging program.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.952
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.035
GPT teacher head0.254
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it