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Record W7132362509

Tsingshan: A Short Squeeze on the LME’s Nickel Futures Market

2024· other· W7132362509 on OpenAlexaff
Renxuan 王任轩, 阎志鹏, 赵玲

Bibliographic record

VenueCEIBS Institutional Repository · 2024
Typeother
Language
Field
Topic
Canadian institutionsCentre Casa
Fundersnot available
KeywordsFutures contractNickelBoomFutures marketTerm (time)
DOInot available

Abstract

fetched live from OpenAlex

2022年3月,在 伦敦金融交易所(London Metal Exchange,简称LME)爆发了一场史诗级镍期货逼空风暴。我国不锈钢产业龙头企业青山控股作为LME镍期货的主要空头方遭受极大损失。青山控股在LME持有20万吨镍期货空单,交割期在3月。但是由于青山自身生产的是高冰镍,不满足LME的交割标准;同时,由于俄乌局势等“黑天鹅”事件,青山更加难以实现现货交割。临近交割期,镍期货价格暴涨,青山账面已浮亏80多亿元,镍期货市场也陷入无序。3月9日,LME出人意料地暂停了镍交易,同时取消了3月8号零点以前的交易,为这次伦镍逼仓事件按下了暂停键。本次事件虽然暂时告一段落,但依然给中国企业敲响了警钟。青山为何会被逼仓?期货交易有哪些风险?企业可以如何优化期货交易策略?

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.047
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0050.003
Scholarly communication0.0120.008
Open science0.0010.004
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0380.004

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 head0.018
GPT teacher head0.253
Teacher spread0.235 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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