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Record W1986747684 · doi:10.1093/cje/bev017

Keynes and the interwar commodity option markets

2015· article· en· W1986747684 on OpenAlexaboutno aff
Maria Cristina Marcuzzo, Eleonora Sanfilippo

Bibliographic record

VenueCambridge Journal of Economics · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Institutions
Canadian institutionsnot available
Fundersnot available
KeywordsSpeculationEconomicsCommodityFutures contractInvestment (military)ContangoFinancializationFinancial marketQuarter (Canadian coin)Financial economicsKeynesian economicsMarket economyMacroeconomicsFinancePoliticsLaw

Abstract

fetched live from OpenAlex

In the first quarter of the twentieth century, options began to be widely employed in the main financial centres in Europe and the USA for trading in spot and futures markets. From 1921 onward, Keynes embarked upon investment in these derivatives mainly—but not exclusively—in the commodity markets, showing a true fascination for this method of speculation. This type of financial investment he pursued mainly in the 1920s, with only a few operations undertaken during the 1930s. The option markets in which Keynes traded were metals—in particular copper, lead, spelter and, especially, tin. Besides metals, Keynes dealt in options also in other commodity markets, such as rubber and linseed oil, and sparingly in ordinary stocks and government securities. In this paper we offer a reconstruction of Keynes’s speculative activity in commodity options, drawing on the archival material kept in the Keynes Papers held at King’s College, Cambridge. This reconstruction is, to the best of our knowledge, entirely new to the literature and aims to provide an analysis of this particular aspect of Keynes’s investment behaviour, investigating his capacity to predict market trends and offering a preliminary assessment of his performance.

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.

How this classification was reachedexpand

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)0.003
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.531
Threshold uncertainty score0.417

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.049
GPT teacher head0.216
Teacher spread0.167 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2015
Admission routes1
Has abstractyes

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