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Record W1508565373

The Fall of Wall Street: How the Crisis Was Made and How it Could Have Been Avoided

2009· article· en· W1508565373 on OpenAlexaff
Yvan Allaire, Mihaela E. Firsirotu

Bibliographic record

VenueSSRN Electronic Journal · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic, financial, and policy analysis
Canadian institutionsUniversité du Québec à MontréalInstitute on Governance
Fundersnot available
KeywordsFinancial crisisFinancial marketBusinessInterdependenceFinancial systemFinanceEconomicsPolitical scienceKeynesian economicsLaw
DOInot available

Abstract

fetched live from OpenAlex

This paper focuses on the convoluted process that played a critical role in triggering the worldwide financial crisis of the 2007-2009. This financial crisis was clearly man-made. It was not a “perfect storm.” not an act of God. The all too familiar duo of greed and avarice played their number in the vast, rich, unregulated financial markets, in every nook and cranny of this wide-open domain. Unaware of the cumulative, correlated pressures that were building up in the system, reassured by precise but inaccurate mathematical models, vaguely worried but soothed by the immense pay-offs, most players rushed onward until the music stopped.When the first and weakest link, the sub-prime mortgage securitized notes, broke, the edifice that poor or corrupt financial engineers had designed fell like a house of cards. There were no back-up system, no built-in redundancies, no fail-safe mechanism. All parts of the worldwide financial system had become connected and interdependent. One piece failed, the whole system, brittle and vulnerable, collapsed.The causes of this crisis must be well understood and measures taken to prevent a crisis of the same kind in coming years. The last crisis of similar scope, in the 1930s did result in regulations that kept the financial world relatively crisis-free for some 40 years. Then, as is wont to happen, this period of relative calm led many to believe that de-regulation and under-regulation of the financial industry would bring large benefits. Financial markets, some believed, had become so efficient that they would swiftly correct any anomaly, reward rational risk-taking, and punish deviant behaviour.That turned out to be more ideology than grounded policy. The set of prescriptions contained in this paper, some of them anyway, may well be adopted in watered down form as policies and regulations. However, the fundamental causes of the recurring crises lie elsewhere.

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)0.002
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.297
Threshold uncertainty score0.657

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.222
Teacher spread0.203 · 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

Citations1
Published2009
Admission routes1
Has abstractyes

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