Publication activity
Articles grouped by publication year
Hover over a year or focus the chart and use arrow keys to inspect values.
2026 is year to date. 0 undated publications excluded.
Research across participating journals · All insights follow your collection filters.
Publication activity alongside incoming citations.
Articles grouped by publication year
Hover over a year or focus the chart and use arrow keys to inspect values.
2026 is year to date. 0 undated publications excluded.
OpenAlex · year of the citing work
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.
Leading affiliations and themes in this collection.
Full distributions & methodology ↓Independent sources. Clear time scales.
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.
OpenAlex · incoming citation links grouped by citing-work year
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.
Select journals to compare the same collection filters. Source totals stay separate. These measures describe research activity, not journal quality.
Articles by publication year
Latest lifetime totals · grouped by publication year
Latest lifetime totals · grouped by publication year
By year of the citing work · 2017–2026
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.
Crossref citation coverage: 22 / 23 publications (95.7%). Latest observation: 21 Oct 2026, 00:21 UTC. Means and percentages use records with known counts.
DOI-matched OpenAlex observations for the same selected publications. These counts are separate from Crossref and are never added together.
Observation range: 22 Oct 2026 01:07 UTC — 22 Oct 2026 18:45 UTC. Missing matches are not zero citations. Previous observations may remain if a refresh fails or a DOI no longer matches.
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.
16 / 23 with data · 7 missing or unmatched. Percentages use all 23 selected publications.
16 / 23 with data · 7 missing or unmatched. Percentages use all 23 selected publications.
23 / 23 with data · 0 missing or unmatched. Percentages use all 23 selected publications.
Citations are the latest recorded totals for articles published in each year, not citations received during that year. Crossref and OpenAlex remain separate and share the same citation scale. 2026 is incomplete; newer articles have had less time to receive citations.
0 undated publications excluded. Unknown citation counts are shown as —, never as zero. Partial coverage can understate totals; expand each table for known / total records.
| Publication year | Journal / scope | Publications | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2013 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2014 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| 2015 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2016 | All selected publications | 5 | 5 | 5/5 | 5/5 |
| 2017 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 4 | 4 | 4/4 | 4/4 |
| 2020 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2021 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2022 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 1 | 1 | 0/1 | 1/1 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2013 | All selected publications | 4 | 2 | 2/2 | 2/2 |
| 2014 | All selected publications | 4 | 3 | 3/3 | 3/3 |
| 2015 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2016 | All selected publications | 8 | 5 | 5/5 | 5/5 |
| 2017 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 3 | 4 | 4/4 | 4/4 |
| 2020 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2021 | All selected publications | 4 | 2 | 2/2 | 2/2 |
| 2022 | All selected publications | 3 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | — | 1 | 0/1 | 1/1 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2013 | All selected publications | 6 | 2 | 2/2 | 2/2 |
| 2014 | All selected publications | 11 | 3 | 3/3 | 3/3 |
| 2015 | All selected publications | 8 | 2 | 2/2 | 2/2 |
| 2016 | All selected publications | 9 | 5 | 5/5 | 5/5 |
| 2017 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 7 | 4 | 4/4 | 4/4 |
| 2020 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2021 | All selected publications | 9 | 2 | 2/2 | 2/2 |
| 2022 | All selected publications | 3 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 0 | 1 | 0/1 | 1/1 |
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 23 / 23 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): 2026-10-22T01:07:51.324106+00:00 — 2026-10-22T18:45:55.336354+00:00. Older observations may be retained after failed or incomplete refreshes.
| Citation year | Journal / scope | OpenAlex · Citations received by year | Publications | Annual history known |
|---|---|---|---|---|
| 2017 | All selected publications | 0 | 23 | 23/23 |
| 2018 | All selected publications | 5 | 23 | 23/23 |
| 2019 | All selected publications | 2 | 23 | 23/23 |
| 2020 | All selected publications | 5 | 23 | 23/23 |
| 2021 | All selected publications | 5 | 23 | 23/23 |
| 2022 | All selected publications | 4 | 23 | 23/23 |
| 2023 | All selected publications | 6 | 23 | 23/23 |
| 2024 | All selected publications | 10 | 23 | 23/23 |
| 2025 | All selected publications | 4 | 23 | 23/23 |
| 2026 | All selected publications | 3 | 23 | 23/23 |
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 ↗
Publications by publication year. 2026 is an incomplete year.
| Period | Publications |
|---|---|
| 2013 | 2 |
| 2014 | 3 |
| 2015 | 2 |
| 2016 | 5 |
| 2017 | 1 |
| 2019 | 4 |
| 2021 | 2 |
| 2022 | 1 |
| 2023 | 1 |
| 2024 | 1 |
| 2026 | 1 |
Latest Crossref totals for the selected publications; not citations received in the selected years.
Unknown counts are excluded from the mean, median and cited-publication rate.
Same filters, source and counting rules across journals. Descriptive statistics, not a quality ranking.
| Journal / publisher | Publications | Crossref citations | OpenAlex citations | OpenAlex coverage | Crossref mean | Crossref median | Crossref cited %* | Crossref coverage |
|---|---|---|---|---|---|---|---|---|
| International Journal of Finance & Banking Studies SSBFNET | 23 | 29 | 54 | 23/23 | 1.32 | 0.5 | 50.0 | 22/23 · 95.7% |
* Percentage among publications with a known citation count.
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.
The purpose of this article was to assess the impact of financial market liquidity on international capital flows in emerging markets. Specifically, the research investigates the effect of bond market liquidity and stock market liquidity on foreign portfolio investments using data for five emerging African countries, being Egypt, Kenya, Mauritius, Nigeria and South Africa, for the period 2000 to 2020. The data was sourced from the Bloomberg and World Bank (WDI) databases. Panel data analysis (fixed effects model) was undertaken using three different liquidity measures: the effective spread; Amihud’s (2002) illiquidity measure; and market impact as measured by trading volume. Our findings revealed mixed results. It was found that stock market liquidity attracted foreign portfolio investments. Although bond market liquidity, as measured by the volume of trade, promoted foreign portfolio investment, it was different for the effective spread, as the higher the effective spread, the higher the inward FPI flows, and vice versa. Results on the effects of the bond effective spread on FPI show that as long as the bonds are above the investable grade, investors are not discouraged by the cost of trading. Our findings thus confirm that FPI inflows are predisposed on liquid and efficient host country financial markets. Further, the entrance of foreign investors in the host country’s domestic financial markets, leads to the enhancing of liquidity in the local market, thus increasing risk sharing between local and foreign investors.
This study tests for the applicability of the Adaptive Market Hypothesis (AMH) and Bounded rationality theories on the Johannesburg Stock Exchange (JSE). This is in order to determine the influence of behavioural risk factors on the efficiency of the stock market. Behavioural theories show a gap in the theory of Efficient Market Hypothesis. Using quantile regression, our study established the applicability of the Adaptive Market Hypothesis on the JSE. Past market returns were shown to be significant in predicting future returns and thus did not follow a random walk. The lagged return increased at higher quantiles and differed with changes in market conditions (i.e. pre-financial crisis, financial crisis and post-financial crisis). Thus, the predictability of returns varies with a change in market conditions. This paper is focused on only on the Johannesburg stock exchange in South Africa, more specifically the movement is the all share index. The findings should be able to be applied to emerging and developed economies. Business confidence is found to have a negative relationship with returns showing a lag in time for sentiment to be incorporated in prices. In contrast, consumer confidence is found to have a positive relationship with returns. In summary, investors are shown to be influenced by fundamental and behavioural factors.
The paper concentrates on the value premium across countries and contributes to the investment and asset pricing literature in three ways. First, I provide fresh evidence that the high-value countries perform significantly better than the low-value countries. Additionally, this phenomenon is indifferent to the choice of the computational currency, representative index or value indicator. Second, I demonstrate that the value effect can be successfully amplified by combining with country-level size and momentum effects. Third, I show that returns to the high-value countries deteriorate in financial crisis conditions, because the country-level value premium is negatively correlated with the credit spreads, TED spread and expected volatility. I examine data from 66 markets between years 2000 and 2013.
The puzzling momentum strategies’ payoffs are defying the rational financial theory asserting the stocks returns’ unpredictability. Moreover, the momentum effect persist the main stocks returns’ anomaly escaping any risk-based explanation. The resilience of this phenomenon had favoured the development of behavioural financial field, which breaks with the investor’ full rationality hypothesis. This paper attempts to reconcile between the rational and behavioural financial theories, through the introduction of the progressive rationality concept. Especially, we argue that recognizing the temporary inappropriate investors’ reactions; can resolve the puzzling momentum anomaly. To fulfil our objective, first we correct the monthly returns inherent to 56 stocks listed on the Tunisian stocks market from January 1998 to December 2011, from the related serial autocorrelations involved by the investors’ over and under reactions. Then, we examine the 6/6 momentum strategy’ excess returns before and after the monthly returns serial autocorrelations’ corrections. The result show that the momentum strategy is still profitable but no longer puzzling, since the related excess return is henceforth fully captured by a ? and a size effect..
This paper investigates whether personality traits, affects, and anticipated emotions measured before a stock market simulation explain participants’ trading style. The study relies on a sample of 133 undergraduate students from the University of Mons, Belgium, who participated in a four-hour CAC 40 trading simulation with a virtual portfolio of EUR 100,000. Regressions were estimated on several dimensions of trading style: number of transactions, minutes per order, average transaction size, average cash holdings, and portfolio volatility. The results show that psychological variables explain little of trading frequency or pacing but are informative about the structure of market exposure. Negative affect is associated with higher cash retention, whereas positive anticipated emotions are associated with lower cash holdings. Gender and openness also predict position size, while gender, age, and openness are significant predictors of portfolio volatility. Overall, the findings suggest that psychology explains less how much individuals trade than how they structure their market exposure.
This study delves into the performance of Indonesian state-owned enterprises (BUMN) stocks from February 2021 to October 2023, attracting investor attention due to their strategic position in the national economy. However, the stock performance during this period exhibited suboptimal movements, failing to surpass the returns of the Indonesia Stock Exchange Composite Index (IHSG). To address this, a prudent investment strategy is essential, encompassing portfolio construction and management. In portfolio construction, the study employs proven smart beta strategies, known for delivering superior returns compared to traditional portfolios. Portfolio management involves testing two strategies: a passive approach utilizing the buy-and-hold technique and an active approach employing portfolio recomposition. This quantitative descriptive study utilizes historical closing price data, forming portfolios based on selected beta groups. Weighting is adjusted, with higher beta stocks receiving a larger allocation in the portfolio. The research compares two beta groups (high and low) and two investment strategies (active and passive) using the Sharpe, Treynor, and Jensen indices. The results indicate that the high-beta group and active strategy outperform, aligning with the investment adage "high risk, high return." The high-beta group yields higher returns due to its increased risk profile, consistent with the notion of high-risk, high-reward investments. The active strategy provides opportunities to discard underperforming stocks and enhance the weighting of well-performing ones during recomposition. These findings are valuable for investors seeking to capitalize on BUMN stocks at lower prices. The study aids in minimizing negative returns (losses) by identifying the most suitable strategy for BUMN portfolios. Investors can leverage this research to make informed decisions and navigate the challenges associated with investing in state-owned enterprises.
Mutual fund is one of the investment instruments widely used as an investment option. There are two essential things to be considered by the Investment Manager as a mutual fund manager: the stock selection and the market timing ability. The Covid-19 pandemic has caused many investors to experience potential investment losses. Understanding stock selection and market timing will be needed for determining which Investment Managers perform well in managing equity mutual fund, especially while dealing with the Covid-19 pandemic. The objective of this study is to analyze the ability of Investment Managers to perform stock selection and market timing, the performance of equity mutual fund, and the effect of stock selection and market timing ability on the performance of equity mutual fund in Indonesia. This study applies the Fama net selectivity methods to assess stock selection ability and Treynor-Mazuy and Henriksson-Merton models to analyze market timing ability. Sharpe, Treynor, and Jensen's alpha methods are also used for measuring mutual fund performance. The data is processed per mutual fund to recognize each mutual fund's stock selection and market timing ability. Furthermore, the research spans two time periods: before and following the Covid-19 pandemic. A dataset of 104 equity mutual funds from 2016-2021 has been analyzed. The findings show that only 9 and 12 Investment Managers have stock selection ability prior to and following the Covid-19 pandemic, respectively. According to Treynor Mazuy model, there are only two Investment Managers with market timing ability prior to the Covid-19 pandemic, and only twelve Investment Managers have market timing ability during the Covid-19 pandemic, according to the Henriksson-Merton model. Every mutual fund with stock selection ability outperformed the benchmark. However, not all equity mutual fund with market timing ability outperformed the benchmark.
This study tests for the applicability of the Adaptive Market Hypothesis (AMH) and Bounded rationality theories on the Johannesburg Stock Exchange (JSE). This is in order to determine the influence of behavioural risk factors on the efficiency of the stock market. Behavioural theories show a gap in the theory of Efficient Market Hypothesis. Using quantile regression, our study established the applicability of the Adaptive Market Hypothesis on the JSE. Past market returns were shown to be significant in predicting future returns and thus did not follow a random walk. The lagged return increased at higher quantiles and differed with changes in market conditions (i.e. pre-financial crisis, financial crisis and post-financial crisis). Thus, the predictability of returns varies with a change in market conditions. This paper is focused on only on the Johannesburg stock exchange in South Africa, more specifically the movement is the all share index. The findings should be able to be applied to emerging and developed economies. Business confidence is found to have a negative relationship with returns showing a lag in time for sentiment to be incorporated in prices. In contrast, consumer confidence is found to have a positive relationship with returns. In summary, investors are shown to be influenced by fundamental and behavioural factors.
The collective investment schemes in Kenya have witnessed increased volatility in their earnings, resulting in irregular growth in the industry. This necessitates the need to understand the factors contributing to poor financial returns from collective investment schemes. Hence this study sought to investigate the effect of equity investments and bond investments on Kenyan CIS’s performance. The specific objectives were: To assess the effect of equity investments, bond investments on financial performance of collective investment schemes in Kenya. The study was anchored on: modern portfolio theory and the efficient market hypothesis. The positivism philosophy was applied, with the firms adopting an explanatory research design. The target population was 17 Collective Investment Schemes registered by the Capital Markets Authority and were operational in the period 2010 to 2018. Secondary data was sought from the Capital Markets Authority Annual reports and from the respective websites of the CIS’. Data was analyzed using descriptive statistics, correlational analysis and panel regression analysis. Hypotheses were tested at a significance level of 0.05. Findings indicate that equity investment, bond investments have an insignificant effect on CIS’ return on assets. Further, equity investments had a positive and significant effect on liquidity whereas bond investments had an insignificant effect on liquidity. The study recommends that CISs actively revise their equity investments and bond investments to stimulate financial returns.
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
| Source | Most recent successful journal sync | Latest attempt |
|---|---|---|
| crossref | 21 Oct 2026 00:21 UTC · ijfbs | complete · ijfbs · 21 Oct 2026 00:21 UTC |
| ojs-rest | 21 Oct 2026 00:21 UTC · ijfbs | complete · ijfbs · 21 Oct 2026 00:14 UTC |
| oai-pmh | 20 Oct 2026 19:56 UTC · ijfbs | complete · ijfbs · 20 Oct 2026 19:55 UTC |
| openalex-enrichment | 21 Oct 2026 00:22 UTC · ijfbs | complete · ijfbs · 21 Oct 2026 00:21 UTC |