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% · 5/5 recordsLast OpenAlex observation 22 Oct 2026, 01:39 UTC
PUBLICATIONS5In the selected collection
CROSSREF CITATIONS95/5 with known counts
OPENALEX CITATIONS225/5 with known counts
OPENALEX MEAN4.4Per article with a known count
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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

Hunan University of Science and Technology1Poznań University of Economics and Business1Guangdong University of Foreign Studies14/5 records with data

Countries

China1Italy1Poland14/5 records with data

Primary topics

Market Dynamics and Volatility55/5 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.

View data & coverage

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: 5/5 articles. Latest history observation: 2026-10-22T01:39:28.483642+00:00. Source totals are never added together.
Research side by side

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Display range
International Journal of Finance & Banking Studies

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
5 MATCHING PUBLICATIONSExplore results →Export CSV ↓
INDEXED PUBLICATIONS5
CROSSREF CITATIONS9
CROSSREF · CITED PUBLICATIONS60.0%
CROSSREF · MEAN CITATIONS1.8

Crossref citation coverage: 5 / 5 publications (100.0%). Latest observation: 21 Oct 2026, 00:21 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 CITATIONS22
DOI MATCH COVERAGE100.0%5 / 5 publications
MEAN · KNOWN COUNTS ONLY4.45 known · 0 unknown
MEDIAN · KNOWN COUNTS ONLY5

Observation range: 21 Oct 2026 00:22 UTC — 22 Oct 2026 01:39 UTC. Missing matches are not zero citations. Previous observations may remain if a refresh fails or a DOI no longer matches.

OpenAlex citation distributionNo citations11–536–20121+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 / 5 with data · 1 missing or unmatched. Percentages use all 5 selected publications.

Countries

4 / 5 with data · 1 missing or unmatched. Percentages use all 5 selected publications.

Primary topics

5 / 5 with data · 0 missing or unmatched. Percentages use all 5 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 5 / 5 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): 2026-10-21T00:22:00.296479+00:00 — 2026-10-22T01:39:28.483642+00:00. Older observations may be retained after failed or incomplete refreshes.

OpenAlex · Citations received by year

42.00 2017 · All selected publications · OpenAlex · Citations received by year: 1 · Annual history coverage 5/52018 · All selected publications · OpenAlex · Citations received by year: 3 · Annual history coverage 5/52019 · All selected publications · OpenAlex · Citations received by year: 1 · Annual history coverage 5/52020 · All selected publications · OpenAlex · Citations received by year: 2 · Annual history coverage 5/52021 · All selected publications · OpenAlex · Citations received by year: 3 · Annual history coverage 5/52022 · All selected publications · OpenAlex · Citations received by year: 2 · Annual history coverage 5/52023 · All selected publications · OpenAlex · Citations received by year: 4 · Annual history coverage 5/52024 · All selected publications · OpenAlex · Citations received by year: 1 · Annual history coverage 5/52025 · All selected publications · OpenAlex · Citations received by year: 1 · Annual history coverage 5/52026 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 5/5 2017201820192020202120222023202420252026
View openalex · citations received by year data & coverage
Citation yearJournal / scopeOpenAlex · Citations received by yearPublicationsAnnual history known
2017All selected publications155/5
2018All selected publications355/5
2019All selected publications155/5
2020All selected publications255/5
2021All selected publications355/5
2022All selected publications255/5
2023All selected publications455/5
2024All selected publications155/5
2025All selected publications155/5
2026All selected publications055/5

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.

Mean1.8
Median1
No citations21–526–20121+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
International Journal of Finance & Banking Studies
SSBFNET
59225/51.8160.05/5 · 100.0%

* Percentage among publications with a known citation count.

Explore publications

View all 5 →

Most cited · Crossref

JOURNAL ARTICLE

Euro ve ABD Dolar? Kurlar? ile Pay Senedi Endeksleri Aras?ndaki ?li?kinin ?ncelenmesi

Hicabi Ersoy · Ayben Koy

International Journal of Finance & Banking Studies · 2016

Read abstract

Bu çal??mada Türkiye’de pay senetleri fiyatlar? ile döviz kurlar? aras?ndaki ili?ki, VAR metodu (vektör oto regresyon modeli) kullan?larak ara?t?r?lm??t?r. Döviz kurlar? ve pay senedi fiyatlar?ndan olu?an de?i?kenler aras?nda do?rusal bir ba??nt? olup olmad???n?n tespiti amac?yla bu model kullan?lm??t?r. Bu amaçla, döviz kurlar?, B?ST Banka ve B?ST S?nai endeksleri ele al?nm??t?r. Veriler Ocak 2011’den Aral?k 2014’e kadar olan döneme ait günlük de?i?meleri içermektedir. Türkiye’de en fazla i?lem yap?lan döviz kurlar? ABD dolar? ve Euro oldu?u için, bu kurlar tercih edilmi?tir.

DOI 10.20525/ijfbs.v5i2.2696 Crossref citations5 OpenAlex citations
JOURNAL ARTICLE

Portfolio Diversification with Commodities in Times of Financialization

Adam Zaremba

International Journal of Finance & Banking Studies · 2015

Read abstract

The study concentrates on the benefits of passive commodity investments in the context of the phenomenon of financialization. The research investigates the implications of increase in the correlation coefficients between equity and commodity investments for investors in financial markets. The paper is composed of several parts. First, the attributes of commodity investments and their benefits in the portfolio optimization are explored. Second, the phenomenon of the financialization is described and the research hypothesis is developed. Next, an empirical analysis is performed. I simulate the mean-variance spanning tests to examine the benefits of commodity investments before and after accounting for the impact of financialization. I proceed separate analysis for pre- and post-financialization period. The empirical research is based on asset classes’ returns and other related variables from years 1991-2012. The performed investigations indicate that the market financialization may have significant implications for commodity investors. Due to increase in correlation coefficients, the inclusion of the commodity futures in the traditional stock-bond portfolio appears to be no longer reasonable.

DOI 10.20525/ijfbs.v4i1.2022 Crossref citations9 OpenAlex citations
JOURNAL ARTICLE

Investigation of the Linkage among China’s Macroeconomy, Stock Market and Real Estate Market

Guo Jianhua · Long Huidian

International Journal of Finance & Banking Studies · 2013

Read abstract

As two important constituents of China’s macro economy, there are a variety of relationships among China’s stock market, real estate market and its macro economy. In order to investigate these relationships, in this paper, especially with the Macroeconomic Boom Index reflecting China’s macro economy, we use cointegration theory and Granger analysis to demonstrate that there are long-term equilibrium relationship and bidirectional causality between the macro economy and the securities business, also between the macro economy and the real estate market, however, this kind of long-term Equilibrium relationship and bidirectional causality appears very weak.

DOI 10.20525/ijfbs.v2i2.1411 Crossref citations5 OpenAlex citations
JOURNAL ARTICLE

Commodity Pricing through Crises

Giulio Cifarelli

International Journal of Finance & Banking Studies · 2025

Read abstract

The pricing of six highly liquid futures commodity contracts is investigated using a Markov switching procedure. The data set spans an exceptionally turbulent period, characterized by a complex interplay of economic/financial and political shocks. Markov switching analysis exploits time series nonlinearity to identify the nature and the timing of the implicit changes of regime. Building on a HAM framework, we use the time varying parameterization of the transition probability estimates to link these shifts to exogenous variables. We provide in this way additional information on the co-movement of the time series and on their regime shifts, eventually conducive to herding pricing behaviour. The WTI oil futures price and DJIA stock index are used as proxies for global shocks as they turn out to be the main common drivers of the changes in regime of most futures commodity prices.   

DOI 10.20525/ijfbs.v14i3.40570 Crossref citations0 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

Selected results

JOURNAL ARTICLE

Commodity Pricing through Crises

Giulio Cifarelli

International Journal of Finance & Banking Studies · 2025

Read abstract

The pricing of six highly liquid futures commodity contracts is investigated using a Markov switching procedure. The data set spans an exceptionally turbulent period, characterized by a complex interplay of economic/financial and political shocks. Markov switching analysis exploits time series nonlinearity to identify the nature and the timing of the implicit changes of regime. Building on a HAM framework, we use the time varying parameterization of the transition probability estimates to link these shifts to exogenous variables. We provide in this way additional information on the co-movement of the time series and on their regime shifts, eventually conducive to herding pricing behaviour. The WTI oil futures price and DJIA stock index are used as proxies for global shocks as they turn out to be the main common drivers of the changes in regime of most futures commodity prices.   

DOI 10.20525/ijfbs.v14i3.40570 Crossref citations0 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

Euro ve ABD Dolar? Kurlar? ile Pay Senedi Endeksleri Aras?ndaki ?li?kinin ?ncelenmesi

Hicabi Ersoy · Ayben Koy

International Journal of Finance & Banking Studies · 2016

Read abstract

Bu çal??mada Türkiye’de pay senetleri fiyatlar? ile döviz kurlar? aras?ndaki ili?ki, VAR metodu (vektör oto regresyon modeli) kullan?larak ara?t?r?lm??t?r. Döviz kurlar? ve pay senedi fiyatlar?ndan olu?an de?i?kenler aras?nda do?rusal bir ba??nt? olup olmad???n?n tespiti amac?yla bu model kullan?lm??t?r. Bu amaçla, döviz kurlar?, B?ST Banka ve B?ST S?nai endeksleri ele al?nm??t?r. Veriler Ocak 2011’den Aral?k 2014’e kadar olan döneme ait günlük de?i?meleri içermektedir. Türkiye’de en fazla i?lem yap?lan döviz kurlar? ABD dolar? ve Euro oldu?u için, bu kurlar tercih edilmi?tir.

DOI 10.20525/ijfbs.v5i2.2696 Crossref citations5 OpenAlex citations
JOURNAL ARTICLE

Portfolio Diversification with Commodities in Times of Financialization

Adam Zaremba

International Journal of Finance & Banking Studies · 2015

Read abstract

The study concentrates on the benefits of passive commodity investments in the context of the phenomenon of financialization. The research investigates the implications of increase in the correlation coefficients between equity and commodity investments for investors in financial markets. The paper is composed of several parts. First, the attributes of commodity investments and their benefits in the portfolio optimization are explored. Second, the phenomenon of the financialization is described and the research hypothesis is developed. Next, an empirical analysis is performed. I simulate the mean-variance spanning tests to examine the benefits of commodity investments before and after accounting for the impact of financialization. I proceed separate analysis for pre- and post-financialization period. The empirical research is based on asset classes’ returns and other related variables from years 1991-2012. The performed investigations indicate that the market financialization may have significant implications for commodity investors. Due to increase in correlation coefficients, the inclusion of the commodity futures in the traditional stock-bond portfolio appears to be no longer reasonable.

DOI 10.20525/ijfbs.v4i1.2022 Crossref citations9 OpenAlex citations
JOURNAL ARTICLE

Investigation of the Linkage among China’s Macroeconomy, Stock Market and Real Estate Market

Guo Jianhua · Long Huidian

International Journal of Finance & Banking Studies · 2013

Read abstract

As two important constituents of China’s macro economy, there are a variety of relationships among China’s stock market, real estate market and its macro economy. In order to investigate these relationships, in this paper, especially with the Macroeconomic Boom Index reflecting China’s macro economy, we use cointegration theory and Granger analysis to demonstrate that there are long-term equilibrium relationship and bidirectional causality between the macro economy and the securities business, also between the macro economy and the real estate market, however, this kind of long-term Equilibrium relationship and bidirectional causality appears very weak.

DOI 10.20525/ijfbs.v2i2.1411 Crossref citations5 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 00:21 UTC · ijfbscomplete · ijfbs · 21 Oct 2026 00:21 UTC
ojs-rest21 Oct 2026 00:21 UTC · ijfbscomplete · ijfbs · 21 Oct 2026 00:14 UTC
oai-pmh20 Oct 2026 19:56 UTC · ijfbscomplete · ijfbs · 20 Oct 2026 19:55 UTC
openalex-enrichment21 Oct 2026 00:22 UTC · ijfbscomplete · ijfbs · 21 Oct 2026 00:21 UTC
Full import history & methodology →