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Record W2176617419 · doi:10.2849/9466

Catering to Investors Through Product Complexity

2016· article· en· W2176617419 on OpenAlexaff
Claire Célérier, Boris Vallée

Bibliographic record

VenueEconstor (Econstor) · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Markets and Investment Strategies
Canadian institutionsUniversity of Toronto
FundersToulouse School of Economics
KeywordsHeadlineProduct (mathematics)Yield (engineering)Investment (military)BusinessEconomicsMonetary economicsFinancial economicsAdvertising

Abstract

fetched live from OpenAlex

This study investigates the rationale for issuing complex securities to retail investors. We focus on a large market of investment products targeted exclusively at households: retail structured products in Europe. We develop an economic measure of product complexity in this market via a text analysis of 55,000 product payoff formulas. Over the 2002-2010 period, product complexity increases, risky products become more common, and product headline rates diverge from the prevailing interest rates as the latter decline. The complexity of a product is positively correlated with its headline rate and risk. Complex products appear more profitable to the banks distributing them, have a lower expost performance, and are more frequently sold by banks targeting low-income households. These empirical facts are consistent with banks strategically using product complexity to cater to yield-seeking households.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.403
Threshold uncertainty score1.000

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 studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.005

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 head0.062
GPT teacher head0.237
Teacher spread0.175 · 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; both teacher heads agree on what is shown here.

Study designObservational
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
Published2016
Admission routes1
Has abstractyes

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