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Record W2119613640 · doi:10.1093/ajae/aat098

Portfolio Speculation and Commodity Price Volatility in a Stochastic Storage Model

2014· article· en· W2119613640 on OpenAlex
James Vercammen, Ali Doroudian

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.

Bibliographic record

VenueAmerican Journal of Agricultural Economics · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSpeculationFutures contractEconomicsPortfolioVolatility (finance)Financial economicsCashMid priceContangoMonetary economicsPrice levelFinance

Abstract

fetched live from OpenAlex

Abstract Simulated prices from a stochastic storage model are used to examine the price impacts of speculation by rational investors who diversify their financial portfolios by holding agricultural commodity futures. The main result is that rather than destabilizing commodity prices, as is commonly believed, portfolio speculation actually reduces price volatility. Portfolio speculation can potentially destabilize a commodity's price because the additional demand for long futures by speculators is expected to drive up the cash price during both periods of low net demand, when the cash price is below average, and periods of high net demand, when the cash price is above average. Our theoretical analysis demonstrates that the higher level of inventory that is associated with portfolio speculation results in a larger release of stocks during periods of high net demand. The price simulations reveal that this stock adjustment effect is strong since overall price volatility is smaller rather than larger with portfolio speculation.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.358
Threshold uncertainty score0.623

Codex and Gemma teacher scores by category

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

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 head0.011
GPT teacher head0.194
Teacher spread0.183 · 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