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Record W2773809439

Volatility Persistence in Palestine Exchange Bulls and Bears: An Econometric Analysis of Time Series Data

2017· article· en· W2773809439 on OpenAlexvenueno aff
Ibrahim M. A. Awad, Abdel-Rahman Al-Ewesat

Bibliographic record

VenueReview of Economics and Finance · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsnot available
Fundersnot available
KeywordsVolatility (finance)EconomicsCointegrationPalestineStock (firearms)Long memoryEconometricsFinancial economicsStock marketMonetary economicsBiologyGeography
DOInot available

Abstract

fetched live from OpenAlex

This study aims at investigating volatility persistent in Palestine Exchange (PEX) bulls and bears. It also attempts to explore whether or not stock market volatility present a different behavior during PEX bulls and bears, which is likely to provide investors with a background information for more feasible investment in the PEX. Toward that end, the study employs Rescaled Range (R/S) to calculate the values of difference to find evidence of long memory behavior for the daily data observations from August, 1997 to December, 2014. The study finds that volatility isn¡¯t persistent in the PEX bear markets. Co-integration results show that there is an existence of cointegration, which indicates a long run equilibrium association between PEX bull and bear markets. The ECM results reveal that the speed of adjustment toward long run equilibrium is very low for PEX bull markets while the speed of adjustment toward long run equilibrium is unlikely to be attained for PEX bear markets. Further, the PEX bears markets are longer than PEX bulls markets, so that prudent investors should take volatility in PEX bulls and bears into account.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.349
Threshold uncertainty score0.807

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
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 head0.076
GPT teacher head0.265
Teacher spread0.189 · 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

Citations5
Published2017
Admission routes1
Has abstractyes

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