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Record W2951234042 · doi:10.1108/jdqs-02-2008-b0001

Implied Risk Preferences from Option Prices: Evidence from KOSPI 200 Index Options

2008· article· en· W2951234042 on OpenAlexaff
Byung Jin Kang, Tong Suk Kim, Sun Joong Yoon

Bibliographic record

VenueJournal of Derivatives and Quantitative Studies 선물연구 · 2008
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCapital Investment and Risk Analysis
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsEconomicsEconometricsRisk aversion (psychology)Robustness (evolution)Expected utility hypothesisActuarial scienceFinancial economics

Abstract

fetched live from OpenAlex

In this paper, we investigated the risk averse ness of KOSPI 200 option investors with very flexible risk preference structure. Contrary to the most of previous research either assuming a time-invariant underlying asset return distribution or assuming a well-known functional form for the underlying utility functions. we directly assume functional forms for Investors’risk aversion functions. With the direct specification on the risk aversion functions themselves. we can avoid the possibility 이 suffering from Internal inconsistency and of obtaining misleading risk aversion functions. From our empirical results using KOSPI 200 Index option prices from 1997 through 2006. we discovered that the investors' relative risk aversions exhibit ‘sharply decreasing' across wealth. In addition, our Implied subjective PDFs are found to more accurately forecast the distribution of realization than both the risk neutral PDFs and implied subjective PDFs from previous methods. For the robustness of our empirical results, we test the effects of estimation errors In the expected risk premium, and of financial crisis in the late of 1990s.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.093
Threshold uncertainty score0.661

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.173
GPT teacher head0.318
Teacher spread0.144 · 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 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

Citations1
Published2008
Admission routes1
Has abstractyes

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