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Record W2461767213 · doi:10.1108/qrfm-08-2015-0034

Following momentum and avoiding the “Minsky Moment” evidence from investors on the Financial Instability Hypothesis

2016· article· en· W2461767213 on OpenAlexfundno aff
Scott Pirie, Ronald King To Chan

Bibliographic record

VenueQualitative Research in Financial Markets · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Markets and Investment Strategies
Canadian institutionsnot available
FundersUniversity of British Columbia
KeywordsMomentum (technical analysis)Investment (military)EconomicsOriginalityValue (mathematics)Financial marketFinanceFinancial economicsSociologyQualitative researchLaw

Abstract

fetched live from OpenAlex

Purpose This study aims to find out how institutional investors use momentum in making investment decisions, and whether their actions are consistent with the Financial Instability Hypothesis of Hyman Minsky. Design/methodology/approach The study discusses the findings of interviews with 25 professional investors from the Hong Kong offices of five global financial institutions. All of the participants have several years of practical experience in global and regional markets. Findings Nearly all the managers interviewed said they use momentum in making investment decisions, and they do this in ways that are consistent with the Financial Instability Hypothesis, in which markets alternate between stable and unstable states. The participants are aware they may contribute to this, but they cannot avoid doing it because of short-term constraints in the present financial system. Originality/value This study adds to our knowledge of how professional investors use momentum in their investment strategies. It complements findings of quantitative studies that show momentum strategies have been profitable in many market settings. It also adds evidence that supports the Financial Instability Hypothesis.

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)0.022
metaresearch head score (Gemma)0.031
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
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 score0.315
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0220.031
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
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 head0.317
GPT teacher head0.385
Teacher spread0.068 · 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.

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

Citations3
Published2016
Admission routes1
Has abstractyes

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