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Record W1514090413

Exotic hedging options in the foreign economic activity: comparative analysis

2007· article· en· W1514090413 on OpenAlexaboutno aff
Maria Kaneva

Bibliographic record

VenueJournal Region: Economics and Sociology · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicEconomic and Technological Developments in Russia
Canadian institutionsnot available
Fundersnot available
KeywordsLiberian dollarQuarter (Canadian coin)Exchange rateEconomicsExotic optionFinancial economicsForeign exchangeAsian optionMonetary economicsBusinessFinanceValuation of options
DOInot available

Abstract

fetched live from OpenAlex

The paper analyses the situation when Russian exporter receives his/her proceeds from abroad and wants to have them converted at the most favorable exchange rate in three month. There are some hedging options available to the exporter such as - a simple option (ordinary put) or a number of exotic forms including a barrier option, Asia one or a lookback option. The calculations of the option premiums made through mathematical models show that with a declining dollar exchange rate over the first quarter of 2003, an ordinary put premium was equal to zero, and therefore it was unlikely to be executed. A lookback option proved to be a single instrument allowing the opportunity to sell at the maximum possible exchange rate. The option was executed in the first quarter of 2003 because it was the same as initial one, and the exporter gained. In the first quarter of 2005, the dollar’s exchange rate varied more drastically because of the higher volatile exchange rate. Although the lookback put was profitable to the exporter, it would be more advisable for the exporter to use the barrier options. Which of four barrier options is being executed depends on whether the investor’s expectations coincide with the dynamics of the dollar’s exchange rate. The paper also describes the case where the investor’s expectations and the up-and-in put conditions coincide

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 score0.432
Threshold uncertainty score0.589

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 studies0.0010.001
Scholarly communication0.0000.000
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 head0.105
GPT teacher head0.343
Teacher spread0.238 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

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