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% · 3/3 recordsLast OpenAlex observation 22 Oct 2026, 03:48 UTC
PUBLICATIONS3In the selected collection
CROSSREF CITATIONS83/3 with known counts
OPENALEX CITATIONS83/3 with known counts
OPENALEX MEAN2.67Per article with a known count
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topic: Financial Markets and Investment Strategies 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

Illinois Institute of Technology1Stockton University11/3 records with data

Countries

United States11/3 records with data

Primary topics

Financial Markets and Investment Strategies33/3 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.

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Annual history: 3/3 articles. Latest history observation: 2026-10-22T03:48:39.425110+00:00. Source totals are never added together.
Research side by side

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

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Display range
International Journal of Finance & Banking Studies

Publications

Articles by publication year

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Crossref citations

Latest lifetime totals · grouped by publication year

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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
3 MATCHING PUBLICATIONSExplore results →Export CSV ↓
INDEXED PUBLICATIONS3
CROSSREF CITATIONS8
CROSSREF · CITED PUBLICATIONS33.3%
CROSSREF · MEAN CITATIONS2.67

Crossref citation coverage: 3 / 3 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 CITATIONS8
DOI MATCH COVERAGE100.0%3 / 3 publications
MEAN · KNOWN COUNTS ONLY2.673 known · 0 unknown
MEDIAN · KNOWN COUNTS ONLY1

Observation range: 22 Oct 2026 02:38 UTC — 22 Oct 2026 03:48 UTC. Missing matches are not zero citations. Previous observations may remain if a refresh fails or a DOI no longer matches.

OpenAlex citation distributionNo citations11–516–20121+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

1 / 3 with data · 2 missing or unmatched. Percentages use all 3 selected publications.

Countries

1 / 3 with data · 2 missing or unmatched. Percentages use all 3 selected publications.

Primary topics

3 / 3 with data · 0 missing or unmatched. Percentages use all 3 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 3 / 3 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): 2026-10-22T02:38:23.142573+00:00 — 2026-10-22T03:48:39.425110+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 3/32018 · All selected publications · OpenAlex · Citations received by year: 1 · Annual history coverage 3/32019 · All selected publications · OpenAlex · Citations received by year: 2 · Annual history coverage 3/32020 · All selected publications · OpenAlex · Citations received by year: 1 · Annual history coverage 3/32021 · All selected publications · OpenAlex · Citations received by year: 2 · Annual history coverage 3/32022 · All selected publications · OpenAlex · Citations received by year: 1 · Annual history coverage 3/32023 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 3/32024 · All selected publications · OpenAlex · Citations received by year: 1 · Annual history coverage 3/32025 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 3/32026 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 3/3 2017201820192020202120222023202420252026
View openalex · citations received by year data & coverage
Citation yearJournal / scopeOpenAlex · Citations received by yearPublicationsAnnual history known
2017All selected publications033/3
2018All selected publications133/3
2019All selected publications233/3
2020All selected publications133/3
2021All selected publications233/3
2022All selected publications133/3
2023All selected publications033/3
2024All selected publications133/3
2025All selected publications033/3
2026All selected publications033/3

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.

Mean2.67
Median0
No citations21–506–20121+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
3883/32.67033.33/3 · 100.0%

* Percentage among publications with a known citation count.

Explore publications

View all 3 →

Most cited · Crossref

JOURNAL ARTICLE

Etkin Piyasalar Hipotezi ve Davran??sal Finans Çat??mas?

İhsan KULALI

International Journal of Finance & Banking Studies · 2016

Read abstract

Etkin Piyasalar Hipotezi ve Davran??sal Finans, finansal literatürün kar??t argümanlar? savunan iki temel modelini olu?turmaktad?r. Bunlardan ilki yat?r?mc?lar? rasyonel olarak kabul ederken di?eri ise yat?r?mc?lar? normal olarak ifade etmektedir. Etkin Piyasa Hipotezi’ne göre piyasalar bilgisel olarak daima etkindir. Hisseler en nihayetinde denge fiyat?na ula?acakt?r. Ya?anan finansal krizler ise k?sa dönemli düzeltme hareketleridir. Davran??sal finans, alternatif bir model olarak geli?tirilmi?tir. Buna göre yat?r?mc?lar farkl? bilgilere farkl? zamanlarda ula?maktad?r ve onlar? farkl? de?erlendirmektedir. Yat?r?m kararlar? psikolojik ve duygusal faktörlerden etkilenmektedir. Yat?r?mc?lar?n makine olarak görülmesi kabul edilemez. Davran??sal finans çok daha yeni bir konumdad?r ve çok say?da yeni çal??maya ihtiyaç duymaktad?r. Bununla birlikte iki teori aras?ndaki çat??ma yeni finansal krizlerin önlenmesi aç?s?ndan çok önemlidir. Yak?n gelecekte teorilerin kar??t olmaktan ziyade tamamlay?c? olarak kullan?lmas? beklenmektedir.   

DOI 10.20525/ijfbs.v5i2.1238 Crossref citations7 OpenAlex citations
JOURNAL ARTICLE

What Makes Underwriting and Non-Underwriting Clients of Brokerage Firms Receive Different Recommendations?

Shaowen Hua

International Journal of Finance & Banking Studies · 2016

Read abstract

I explore company characteristics which explain the difference in analysts’ recommendations for companies that were underwritten (affiliated) versus non-underwritten (unaffiliated) by analysts’ brokerage firms. Prior literature documents that analysts issue more optimistic recommendations to underwriting clients of analysts’ brokerage employers. Extant research uses regression models to find general associations between recommendations and financial qualities of companies, with or without underwriting relationship. However, regression models cannot identify the qualities that cause the most difference in recommendations between affiliated versus unaffiliated companies. I adopt uplift random forest model, a popular technique in recent marketing and healthcare research, to identify the type of companies that earn analysts’ favor. I find that companies of stable earnings in the past, higher book-to-market ratio, smaller sizes, worsened earnings, and lower forward PE ratio are likely to receive higher recommendations if  they are affiliated with analysts than if they are unaffiliated with analysts. With uplift random forest model, I show that analysts pay more attention on price-related than earnings-related matrices when they value affiliated versus unaffiliated companies. This paper contributes to the literature by introducing an effective predictive model to capital market research and shedding additional light on the usefulness of analysts’ reports.

DOI 10.20525/ijfbs.v5i3.2780 Crossref citations1 OpenAlex citations
JOURNAL ARTICLE

Bond Portfolio Allocations in South Africa Emerging Markets

Jinghua Wang · John Bilson

International Journal of Finance & Banking Studies · 2016

Read abstract

Over the past fifty years, economic growth in emerging markets has been supported by investments in capital and technology from the developed world. The benefit of this development for the emerging markets, as measured by growth in income, employment, and wealth, is immediately apparent. There have also been significant advantages for the developed world through opportunities for higher risk adjusted returns from investments in emerging markets. This study explores the benefits of the diversification of global government bond portfolio, and provides complete performance evaluations of DMs with or without South Africa emerging market (SAEM) bonds. The study examines the benefits of inclusion of SAEM bonds in DMs, the degrees of financial integration among the research markets, the relative bond returns of dynamic factor models with time-varying coefficients and the robust tests of bond portfolio performance between DMs with SAEM and bond index. The results of this study provide important implications for global investors by identifying diversification gains in SAEM.

DOI 10.20525/ijfbs.v5i1.3430 Crossref citations0 OpenAlex citations

Selected results

JOURNAL ARTICLE

What Makes Underwriting and Non-Underwriting Clients of Brokerage Firms Receive Different Recommendations?

Shaowen Hua

International Journal of Finance & Banking Studies · 2016

Read abstract

I explore company characteristics which explain the difference in analysts’ recommendations for companies that were underwritten (affiliated) versus non-underwritten (unaffiliated) by analysts’ brokerage firms. Prior literature documents that analysts issue more optimistic recommendations to underwriting clients of analysts’ brokerage employers. Extant research uses regression models to find general associations between recommendations and financial qualities of companies, with or without underwriting relationship. However, regression models cannot identify the qualities that cause the most difference in recommendations between affiliated versus unaffiliated companies. I adopt uplift random forest model, a popular technique in recent marketing and healthcare research, to identify the type of companies that earn analysts’ favor. I find that companies of stable earnings in the past, higher book-to-market ratio, smaller sizes, worsened earnings, and lower forward PE ratio are likely to receive higher recommendations if  they are affiliated with analysts than if they are unaffiliated with analysts. With uplift random forest model, I show that analysts pay more attention on price-related than earnings-related matrices when they value affiliated versus unaffiliated companies. This paper contributes to the literature by introducing an effective predictive model to capital market research and shedding additional light on the usefulness of analysts’ reports.

DOI 10.20525/ijfbs.v5i3.2780 Crossref citations1 OpenAlex citations
JOURNAL ARTICLE

Etkin Piyasalar Hipotezi ve Davran??sal Finans Çat??mas?

İhsan KULALI

International Journal of Finance & Banking Studies · 2016

Read abstract

Etkin Piyasalar Hipotezi ve Davran??sal Finans, finansal literatürün kar??t argümanlar? savunan iki temel modelini olu?turmaktad?r. Bunlardan ilki yat?r?mc?lar? rasyonel olarak kabul ederken di?eri ise yat?r?mc?lar? normal olarak ifade etmektedir. Etkin Piyasa Hipotezi’ne göre piyasalar bilgisel olarak daima etkindir. Hisseler en nihayetinde denge fiyat?na ula?acakt?r. Ya?anan finansal krizler ise k?sa dönemli düzeltme hareketleridir. Davran??sal finans, alternatif bir model olarak geli?tirilmi?tir. Buna göre yat?r?mc?lar farkl? bilgilere farkl? zamanlarda ula?maktad?r ve onlar? farkl? de?erlendirmektedir. Yat?r?m kararlar? psikolojik ve duygusal faktörlerden etkilenmektedir. Yat?r?mc?lar?n makine olarak görülmesi kabul edilemez. Davran??sal finans çok daha yeni bir konumdad?r ve çok say?da yeni çal??maya ihtiyaç duymaktad?r. Bununla birlikte iki teori aras?ndaki çat??ma yeni finansal krizlerin önlenmesi aç?s?ndan çok önemlidir. Yak?n gelecekte teorilerin kar??t olmaktan ziyade tamamlay?c? olarak kullan?lmas? beklenmektedir.   

DOI 10.20525/ijfbs.v5i2.1238 Crossref citations7 OpenAlex citations
JOURNAL ARTICLE

Bond Portfolio Allocations in South Africa Emerging Markets

Jinghua Wang · John Bilson

International Journal of Finance & Banking Studies · 2016

Read abstract

Over the past fifty years, economic growth in emerging markets has been supported by investments in capital and technology from the developed world. The benefit of this development for the emerging markets, as measured by growth in income, employment, and wealth, is immediately apparent. There have also been significant advantages for the developed world through opportunities for higher risk adjusted returns from investments in emerging markets. This study explores the benefits of the diversification of global government bond portfolio, and provides complete performance evaluations of DMs with or without South Africa emerging market (SAEM) bonds. The study examines the benefits of inclusion of SAEM bonds in DMs, the degrees of financial integration among the research markets, the relative bond returns of dynamic factor models with time-varying coefficients and the robust tests of bond portfolio performance between DMs with SAEM and bond index. The results of this study provide important implications for global investors by identifying diversification gains in SAEM.

DOI 10.20525/ijfbs.v5i1.3430 Crossref citations0 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
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