CiteNScope — Scholarly Index & Analytics
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Research across participating journals · All insights follow your collection filters.

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OpenAlex coverage 100.0% · 4/4 recordsLast OpenAlex observation 22 Oct 2026, 03:18 UTC
PUBLICATIONS4In the selected collection
CROSSREF CITATIONS24/4 with known counts
OPENALEX CITATIONS64/4 with known counts
OPENALEX MEAN1.5Per article with a known count
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country: Turkey Remove ×topic: Market Dynamics and Volatility Remove ×
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Output and reach

Publication activity alongside incoming citations.

Publication activity

Articles grouped by publication year

Publications

Hover over a year or focus the chart and use arrow keys to inspect values.

2026 is year to date. 0 undated publications excluded.

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Citations received

OpenAlex · year of the citing work

OpenAlex

Hover over a year or focus the chart and use arrow keys to inspect values.

2017–2026 annual-history window. 2026 is year to date. Unknown years have gaps.

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Research landscape

Leading affiliations and themes in this collection.

Full distributions & methodology ↓

Institutions

İstanbul Nişantaşı Üniversitesi1Zonguldak Bülent Ecevit University1Istanbul Medipol University14/4 records with data

Countries

Turkey44/4 records with data

Primary topics

Market Dynamics and Volatility44/4 records with data
Two perspectives on citations

Follow the research impact

Independent sources. Clear time scales.

Lifetime citations by publication year

Crossref and OpenAlex · separate totals for the same publication cohorts

Hover over a year or focus the chart and use arrow keys to inspect values.

Latest lifetime totals, grouped by the cited article’s year. These are not citations received in that year.

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Citations received each year

OpenAlex · incoming citation links grouped by citing-work year

OpenAlex

Hover over a year or focus the chart and use arrow keys to inspect values.

2017–2026 annual-history window. 2026 is year to date. Unknown years have gaps.

View data & coverage
Annual history: 4/4 articles. Latest history observation: 2026-10-22T03:18:09.609336+00:00. Source totals are never added together.
Research side by side

Compare journals

Select journals to compare the same collection filters. Source totals stay separate. These measures describe research activity, not journal quality.

Leave all unchecked to include every matching journal. Selection affects only comparison charts.
Display range
Bussecon Review of Social SciencesInternational Journal of Finance & Banking StudiesInternational Journal of Research in Business and Social Science

Publications

Articles by publication year

View data & coverage

Crossref citations

Latest lifetime totals · grouped by publication year

View data & coverage

OpenAlex citations

Latest lifetime totals · grouped by publication year

View data & coverage

OpenAlex · Citations received

By year of the citing work · 2017–2026

View data & coverage

2026 is year to date. Crossref and OpenAlex lifetime charts share a citation scale. Unknown observations appear as gaps; known zero stays zero. Annual receipts use available OpenAlex histories and may not sum to lifetime totals. 0 undated publications excluded from publication-year charts.

Full analytics report All distributions, publications, comparisons & data provenance
4 MATCHING PUBLICATIONSExplore results →Export CSV ↓
INDEXED PUBLICATIONS4
CROSSREF CITATIONS2
CROSSREF · CITED PUBLICATIONS50.0%
CROSSREF · MEAN CITATIONS0.5

Crossref citation coverage: 4 / 4 publications (100.0%). Latest observation: 21 Oct 2026, 07:22 UTC. Means and percentages use records with known counts.

OpenAlex / Separate citation source

A broader view of this research

DOI-matched OpenAlex observations for the same selected publications. These counts are separate from Crossref and are never added together.

OPENALEX CITATIONS6
DOI MATCH COVERAGE100.0%4 / 4 publications
MEAN · KNOWN COUNTS ONLY1.54 known · 0 unknown
MEDIAN · KNOWN COUNTS ONLY1.5

Observation range: 21 Oct 2026 07:22 UTC — 22 Oct 2026 03:18 UTC. Missing matches are not zero citations. Previous observations may remain if a refresh fails or a DOI no longer matches.

OpenAlex citation distributionNo citations11–536–20021+0Unknown0

Institutions, countries & topics

OpenAlex affiliations and primary-topic classification. Each publication counts once per institution or country; multi-affiliated publications appear in multiple groups, so percentages can sum above 100%. Countries describe author affiliations, not nationality. Topics use one primary topic per publication.

Institutions

4 / 4 with data · 0 missing or unmatched. Percentages use all 4 selected publications.

Countries

4 / 4 with data · 0 missing or unmatched. Percentages use all 4 selected publications.

Primary topics

4 / 4 with data · 0 missing or unmatched. Percentages use all 4 selected publications.

Citation year / OpenAlex

Citations received over time

Incoming citations to the selected publications, grouped by the year of the citing work. This is separate from lifetime citation totals grouped by the cited article’s publication year.

The publication filters above define which articles receive the citations. The citation-year range below only controls this chart and the incoming-citation comparison. Removing publication-year filters includes older articles’ incoming citations too.

Annual history available for 4 / 4 selected publications. Supported display window: 2017–2026; 2026 is incomplete. Within a successfully fetched ten-year window, omitted years mean zero. Missing histories and years beyond a saved observation’s window remain unknown (—); partial coverage can understate totals.

Annual-history observations (UTC): 2026-10-21T07:22:43.923249+00:00 — 2026-10-22T03:18:09.609336+00:00. Older observations may be retained after failed or incomplete refreshes.

OpenAlex · Citations received by year

21.00 2017 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 4/42018 · All selected publications · OpenAlex · Citations received by year: 1 · Annual history coverage 4/42019 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 4/42020 · All selected publications · OpenAlex · Citations received by year: 2 · Annual history coverage 4/42021 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 4/42022 · All selected publications · OpenAlex · Citations received by year: 1 · Annual history coverage 4/42023 · All selected publications · OpenAlex · Citations received by year: 1 · Annual history coverage 4/42024 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 4/42025 · All selected publications · OpenAlex · Citations received by year: 1 · Annual history coverage 4/42026 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 4/4 2017201820192020202120222023202420252026
View openalex · citations received by year data & coverage
Citation yearJournal / scopeOpenAlex · Citations received by yearPublicationsAnnual history known
2017All selected publications044/4
2018All selected publications144/4
2019All selected publications044/4
2020All selected publications244/4
2021All selected publications044/4
2022All selected publications144/4
2023All selected publications144/4
2024All selected publications044/4
2025All selected publications144/4
2026All selected publications044/4

Counts represent citation links, not unique citing papers across a journal: one paper citing two selected articles contributes two links. Older citations outside this window are excluded, so annual sums need not equal lifetime totals. OpenAlex methodology ↗

Crossref citation distribution

Latest Crossref totals for the selected publications; not citations received in the selected years.

Mean0.5
Median0.5
No citations21–526–20021+0Unknown0

Unknown counts are excluded from the mean, median and cited-publication rate.

Journal comparison

Same filters, source and counting rules across journals. Descriptive statistics, not a quality ranking.

Journal / publisherPublicationsCrossref citationsOpenAlex citationsOpenAlex coverageCrossref meanCrossref medianCrossref cited %*Crossref coverage
Bussecon Review of Social Sciences
Bussecon International Academy
1111/11.01100.01/1 · 100.0%
International Journal of Finance & Banking Studies
SSBFNET
1031/10.000.01/1 · 100.0%
International Journal of Research in Business and Social Science
SSBFNET
2122/20.50.550.02/2 · 100.0%

* Percentage among publications with a known citation count.

Explore publications

View all 4 →

Most cited · Crossref

JOURNAL ARTICLE

How does gold and oil price volatility affect Turkish financial markets?

Hakan Öner · Hande Kılıç Satıcı

International Journal of Research in Business and Social Science · 2020

Read abstract

Gold and oil price volatilities are thought to have an impact on financial markets. The main aim of this study is to examine the effects of changes in gold and oil prices on Turkish financial markets. For this purpose, the effects of gold and oil price volatilities on nominal US dollar/Turkish lira exchange rate, Borsa Istanbul 100 Index and Turkey 10-year bond interest rates are used to represent Turkish financial markets are analysed by Granger Casuality Test. The study comprises daily data over the period of June 1, 2010 - April 30, 2017. According to the results of the analysis, there is no causality relationship from gold and oil prices to Turkish financial markets. On the other hand, it is concluded that there is a one-way causality relationship from BIST100 index to Turkey 10-year bond interest rate and two-way causality relationship between BIST 100 index and nominal US dollar/Turkish lira exchange rate.

DOI 10.20525/ijrbs.v9i4.7331 Crossref citations2 OpenAlex citations
JOURNAL ARTICLE

The causality relationship between energy prices and developed countries indices

Yakup Soylemez

Bussecon Review of Social Sciences · 2021

Read abstract

The aim of this study is to determine the causality relationship between energy prices, which are among the most important inputs of the economy, and selected stock market indices of developed countries. Crude oil and natural gas are used as energy variables. G7 countries were selected to represent developed countries. Stock indices used in the study are Dow & Jones (USA), DAX (Germany), CAC40 (France), FTSE250 (England), FTSE Italia All Share (Italy), NIKKEI225 (Japan), and S&P/TSX (Canada). In the study, Johansen (1988) cointegration test and Granger (1969) causality test were used to analyse the causality relationship between energy prices and selected stock market indices. The research could not find a long-term balance relationship between energy prices and developed country indices. Also, while the causality relationship was determined between crude oil prices and NIKKEI225, DAX, and CAC40 indices, a causal relationship between natural gas prices and Dow & Jones and FTSE250 indices was determined. In the study, it was found that energy prices can be used for diversification in investments to be made with stock market indices of developed countries. This study is one of the most comprehensive studies in the literature that examines the relationship between energy prices and the stock market indices of G7 countries. It is expected to contribute to the literature in this way.

DOI 10.36096/brss.v3i2.2921 Crossref citations1 OpenAlex citations
JOURNAL ARTICLE

Conflict Risk and Its Implication on Economy and Financial System

Umit Hacioglu · Hasan Dincer · Ismail Erkan Celik

International Journal of Finance & Banking Studies · 2016

Read abstract

<p>Considering the impacts of the conflict on the economic parameters in terms of macroeconomics, the following factors might affect the profitability of the company: foreign capital outflows, decrease in exports, increase in the interest rates, disruption of the investment climate, increase in the exchange rates, increase in the costs of import entry etc. Due to the expectable decrease in profit shares as to the investors, the contraction in the risk appetite will cause volatility in the prices of equity securities markets based on the impacts of the conflict, and the equity securities will depreciate. In this study, the main contributions on conflict risk and related econometric models have been discussed.</p>

DOI 10.20525/ijfbs.v2i2.6380 Crossref citations3 OpenAlex citations
JOURNAL ARTICLE

Detecting multiple-equilibria and chaos in oil prices and global commodity markets

Ata Ozkaya

International Journal of Research in Business and Social Science · 2022

Read abstract

In the past 20 years, commodity markets have been examined under the hypothesis of whether the prices exhibit recurrent patterns or follow the stochastic processes. In this study, we analyze both global energy markets and food markets to detect the presence of multiple equilibria, which may lead to higher spikes in prices and to the occurrence of intermittency. This study focuses on daily prices in Brent petrol and Natural gas markets from 23 May 2017 to 23 May 2022. This time interval covers the period where extraordinary economic and financial policies have been preferred in countries worldwide amid the Covid-19 pandemic crisis. On the other hand, the study investigates global Food index monthly data from 2007M11 to 2022M4. Similarly, the time interval under examination points out the effects of the 2008 global crisis where expansionary monetary policies have been implemented both by the Federal Reserve of the U.S and the European Central Bank. We employed the phase-space reconstruction method for the Crude oil Brent Europe and spot Natural gas prices series, and global Food index data respectively. The main findings of the study demonstrate that commodity markets do not converge to a unique equilibrium level, instead multiple equilibria persist and chaotic behavior occurs. The presence of multiple equilibria leads to an increase in complexity and recurrently causes volatility in commodity markets, which may have spillover effects on other financial markets. Our results suggest that these effects simultaneously increase global inflationary pressures. From the perspective of policy making, it is crucial to establish a strategy to eliminate multiple equilibria and prevent high price spikes. Our findings have important implications for Central bank policies in emerging markets and portfolio and risk management.

DOI 10.20525/ijrbs.v11i6.19190 Crossref citations0 OpenAlex citations

Selected results

JOURNAL ARTICLE

Detecting multiple-equilibria and chaos in oil prices and global commodity markets

Ata Ozkaya

International Journal of Research in Business and Social Science · 2022

Read abstract

In the past 20 years, commodity markets have been examined under the hypothesis of whether the prices exhibit recurrent patterns or follow the stochastic processes. In this study, we analyze both global energy markets and food markets to detect the presence of multiple equilibria, which may lead to higher spikes in prices and to the occurrence of intermittency. This study focuses on daily prices in Brent petrol and Natural gas markets from 23 May 2017 to 23 May 2022. This time interval covers the period where extraordinary economic and financial policies have been preferred in countries worldwide amid the Covid-19 pandemic crisis. On the other hand, the study investigates global Food index monthly data from 2007M11 to 2022M4. Similarly, the time interval under examination points out the effects of the 2008 global crisis where expansionary monetary policies have been implemented both by the Federal Reserve of the U.S and the European Central Bank. We employed the phase-space reconstruction method for the Crude oil Brent Europe and spot Natural gas prices series, and global Food index data respectively. The main findings of the study demonstrate that commodity markets do not converge to a unique equilibrium level, instead multiple equilibria persist and chaotic behavior occurs. The presence of multiple equilibria leads to an increase in complexity and recurrently causes volatility in commodity markets, which may have spillover effects on other financial markets. Our results suggest that these effects simultaneously increase global inflationary pressures. From the perspective of policy making, it is crucial to establish a strategy to eliminate multiple equilibria and prevent high price spikes. Our findings have important implications for Central bank policies in emerging markets and portfolio and risk management.

DOI 10.20525/ijrbs.v11i6.19190 Crossref citations0 OpenAlex citations
JOURNAL ARTICLE

The causality relationship between energy prices and developed countries indices

Yakup Soylemez

Bussecon Review of Social Sciences · 2021

Read abstract

The aim of this study is to determine the causality relationship between energy prices, which are among the most important inputs of the economy, and selected stock market indices of developed countries. Crude oil and natural gas are used as energy variables. G7 countries were selected to represent developed countries. Stock indices used in the study are Dow & Jones (USA), DAX (Germany), CAC40 (France), FTSE250 (England), FTSE Italia All Share (Italy), NIKKEI225 (Japan), and S&P/TSX (Canada). In the study, Johansen (1988) cointegration test and Granger (1969) causality test were used to analyse the causality relationship between energy prices and selected stock market indices. The research could not find a long-term balance relationship between energy prices and developed country indices. Also, while the causality relationship was determined between crude oil prices and NIKKEI225, DAX, and CAC40 indices, a causal relationship between natural gas prices and Dow & Jones and FTSE250 indices was determined. In the study, it was found that energy prices can be used for diversification in investments to be made with stock market indices of developed countries. This study is one of the most comprehensive studies in the literature that examines the relationship between energy prices and the stock market indices of G7 countries. It is expected to contribute to the literature in this way.

DOI 10.36096/brss.v3i2.2921 Crossref citations1 OpenAlex citations
JOURNAL ARTICLE

How does gold and oil price volatility affect Turkish financial markets?

Hakan Öner · Hande Kılıç Satıcı

International Journal of Research in Business and Social Science · 2020

Read abstract

Gold and oil price volatilities are thought to have an impact on financial markets. The main aim of this study is to examine the effects of changes in gold and oil prices on Turkish financial markets. For this purpose, the effects of gold and oil price volatilities on nominal US dollar/Turkish lira exchange rate, Borsa Istanbul 100 Index and Turkey 10-year bond interest rates are used to represent Turkish financial markets are analysed by Granger Casuality Test. The study comprises daily data over the period of June 1, 2010 - April 30, 2017. According to the results of the analysis, there is no causality relationship from gold and oil prices to Turkish financial markets. On the other hand, it is concluded that there is a one-way causality relationship from BIST100 index to Turkey 10-year bond interest rate and two-way causality relationship between BIST 100 index and nominal US dollar/Turkish lira exchange rate.

DOI 10.20525/ijrbs.v9i4.7331 Crossref citations2 OpenAlex citations
JOURNAL ARTICLE

Conflict Risk and Its Implication on Economy and Financial System

Umit Hacioglu · Hasan Dincer · Ismail Erkan Celik

International Journal of Finance & Banking Studies · 2016

Read abstract

<p>Considering the impacts of the conflict on the economic parameters in terms of macroeconomics, the following factors might affect the profitability of the company: foreign capital outflows, decrease in exports, increase in the interest rates, disruption of the investment climate, increase in the exchange rates, increase in the costs of import entry etc. Due to the expectable decrease in profit shares as to the investors, the contraction in the risk appetite will cause volatility in the prices of equity securities markets based on the impacts of the conflict, and the equity securities will depreciate. In this study, the main contributions on conflict risk and related econometric models have been discussed.</p>

DOI 10.20525/ijfbs.v2i2.6380 Crossref citations3 OpenAlex citations

Data coverage & freshness

Source coverage refers to this result set; a publication may occur in several sources. Sync times refer to contributing journals.

Missing abstracts: 0 · Missing authors: 0 · Missing publication dates: 0 · Dates without day precision: 0

SourceMost recent successful journal syncLatest attempt
crossref21 Oct 2026 07:22 UTC · ijrbscomplete · ijrbs · 21 Oct 2026 07:22 UTC
ojs-rest21 Oct 2026 07:22 UTC · ijrbscomplete · ijrbs · 21 Oct 2026 06:46 UTC
oai-pmh20 Oct 2026 19:56 UTC · ijfbscomplete · ijfbs · 20 Oct 2026 19:55 UTC
openalex-enrichment21 Oct 2026 07:23 UTC · ijrbscomplete · ijrbs · 21 Oct 2026 07:22 UTC
Full import history & methodology →