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This paper proposes to explain how financial assets influence realized volatility by developing an optimal day-to-day forecast. The methodological proposal is based on using the best econometric and machine learning models to forecast realized volatility. In particular, the best forecasting from heterogeneous autoregressive and long short-term memory models are used to determine the influence of the Standard and Poor’s 500 index, euro–US dollar exchange rate, price of gold, and price of Brent crude oil on the realized volatility of natural gas. These financial assets influenced the realized volatility of natural gas in 87.4% of the days analyzed; the euro–US dollar exchange rate was the primary financial asset and explained 40.1% of the influence. The results of the proposed daily analysis differed from those of the methodology used to study the entire period. The traditional model, which studies the entire period, cannot determine temporal effects, whereas the proposed methodology can. The proposed methodology allows us to distinguish the effects for each day, week, or month rather than averages for entire periods, with the flexibility to analyze different frequencies and periods. This methodological capability is key to analyzing influences and making decisions about realized volatility.\u003C\u002Fjats:p>",{"EN":110,"VI":111},"A hybrid econometrics and machine learning based modeling of realized volatility of natural gas","Mô hình hóa lai ghép dựa trên kinh tế lượng và học máy cho độ biến động thực tế của khí tự nhiên",{"VOID":113},"10.1186\u002Fs40854-023-00577-0","PUBLICATION","VERIFIED","2024-12-15T12:32:00.942+00:00","Auto Verify",[119],"EN",[121],"VI","https:\u002F\u002Fjfin-swufe.springeropen.com\u002Farticles\u002F10.1186\u002Fs40854-023-00577-0",[124],{"id":125,"sortIndex":19,"researcher":18,"roles":126,"affiliations":127,"properties":136,"displayName":140,"givenName":18,"familyName":18},"a9fea331-8be2-46c3-8c7c-e0c51587dc77",[],[128],{"id":129,"sortIndex":19,"affiliation":130,"properties":18},"8cd7b594-285f-4d17-8432-c07fe2f3356c",{"id":129,"createTime":18,"updateTime":18,"relativeEntities":131,"slug":18,"properties":132,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":135,"statistic":18},[],{"title":133},{"VI":134},"Departamento de Industrias, Universidad Técnica Federico Santa María, Av. 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Res Int Bus Financ 39:824–839",{"doi":467},"10.1016\u002Fj.ribaf.2015.01.004",{"id":18,"text":469,"url":18,"identifiers":470},"Wang J, Feng L, Tang X, Bentley Y, Höök M (2017) The implications of fossil fuel supply constraints on climate change projections: a supply-side analysis. Futures 86:58–72",{"doi":471},"10.1016\u002Fj.futures.2016.04.007",{"id":18,"text":473,"url":18,"identifiers":474},"Wang M, Zhao L, Du R, Wang C, Chen L, Tian L, Stanley HE (2018) A novel hybrid method of forecasting crude oil prices using complex network science and artificial intelligence algorithms. Appl Energy 220:480–495",{"doi":475},"10.1016\u002Fj.apenergy.2018.03.148",{"id":18,"text":477,"url":18,"identifiers":478},"Wang J, Huang Y, Ma F, Chevallier J (2020a) Does high-frequency crude oil futures data contain useful information for predicting volatility in the US stock market? New evidence. Energy Econ 91:104897",{"doi":479},"10.1016\u002Fj.eneco.2020.104897",{"id":18,"text":481,"url":18,"identifiers":482},"Wang J, Lei C, Guo M (2020b) Daily natural gas price forecasting by a weighted hybrid data-driven model. J Petrol Sci Eng 192:107240",{"doi":483},"10.1016\u002Fj.petrol.2020.107240",{"id":18,"text":485,"url":18,"identifiers":486},"Yuyan G, di H, Yan M, Hongmin Z (2023) Realised volatility prediction of high-frequency data with jumps based on machine learning. Connect Sci 35(1):2210265",{"doi":487},"10.1080\u002F09540091.2023.2210265",false,{"id":490,"createTime":491,"updateTime":492,"relativeEntities":493,"slug":494,"properties":495,"entityType":114,"verifyStatus":115,"verifyTime":508,"verifyNote":117,"languages":18,"translateLanguages":18,"viewCount":19,"primaryUrl":509,"fullTextUrl":18,"authors":510,"publicationType":143,"publisherRelationship":561,"citationCount":18,"citationInfo":18,"publishDate":607,"publishYear":608,"citationAnalyzeStatus":609,"lastCitationAnalyze":610,"indexDatabases":611,"openAccess":18,"references":18,"isForceReanalyzing":488},"0bc861d3-2085-418f-8142-3bde3ed4cf6f","2024-04-06T17:30:22.450+00:00","2026-08-14T21:24:13.477+00:00",[],"Evaluating-short-and-long-term-investment-strategies-development-and-validation-of-the-investment-strategies-scale-ISS-",{"abstract":496,"title":498,"gsPaper":500,"keywords":502,"references":504,"doi":506},{"EN":497},"In response to the growing importance of understanding individual investment strategies, the present study aimed to develop a new scale for measuring both the short- and long-term investment strategies of individuals. The study assessed the psychometric properties of the investment strategies scale (ISS) using data collected from 1428 individual investors. In the initial study, an exploratory factor analysis (EFA) was conducted to investigate the factor structure of the proposed scale (N = 700). The EFA results yielded a two-factor structure, and Cronbach’s alpha values for short- and long-term investment strategies were 0.90 and 0.88, respectively. A confirmatory factor analysis was performed to validate the factor structure of the scale in the second study (N = 728). The results demonstrated that the two-factor model fit the data well. In the third study, the correlation between Hofstede’s long-term orientation and the two dimensions of the scale was investigated. The results indicated that long-term investment strategies significantly predict long-term orientation, thus confirming the concurrent validity of the scale. These findings demonstrate that the proposed ISS is a reliable and valid instrument for measuring individuals’ short- and long-term investment strategies, contributing to a deeper understanding of investment decision-making processes. This study introduces a novel measurement tool—ISS—specifically designed to comprehensively assess both short- and long-term investment strategies among individual investors.",{"EN":499},"Evaluating short- and long-term investment strategies: development and validation of the investment strategies scale (ISS)",{"VOID":501},"[\"17790942158515109755\"]",{"EN":503},"",{"VOID":505},"Abreu M, Mendes V (2010) Financial literacy and portfolio diversification. Quant Finance 10(5):515–528. https:\u002F\u002Fdoi.org\u002F10.1080\u002F14697680902878105\nAgnew JR, Szykman LR (2005) Asset allocation and information overload: the influence of information display, asset choice, and investor experience. 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J Consum Affairs 44(2):276–295. https:\u002F\u002Fdoi.org\u002F10.1111\u002Fj.1745-6606.2010.01169.x\nSarigül H (2015) Finansal okuryazarlık tutum ve davranış ölçeği: geliştirme, geçerlik ve güvenirlik. J Manag Econ Res 13(1):200–218\nSaylık A (2019) Hofstede’nin kültür boyutları ölçeğinin Türkçeye uyarlanması; geçerlik ve güvenirlik çalışması. Uluslararası Türkçe Edebiyat Kültür Eğitim Dergisi 8(3):1860–1881. https:\u002F\u002Fdoi.org\u002F10.7884\u002Fteke.4482\nStatman M, Scheid J (2008) Correlation, return gaps, and the benefits of diversification. J Portfolio Manag 34(3):132–139. https:\u002F\u002Fdoi.org\u002F10.3905\u002Fjpm.2008.706250\nStolper OA, Walter A (2017) Financial literacy, financial advice, and financial behaviour. J Bus Econ 87:581–643. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11573-017-0853-9\nUraz Kaya İ, Kilic B (2021) Finansal Okuryazarlık ve Dijitalleşme: Ölçek Geliştirme Üzerine Bir Çalışma. İktisadi İdari ve Siyasal Araştırmalar Dergisi 6(15):296–315. https:\u002F\u002Fdoi.org\u002F10.25204\u002Fiktisad.901135\nVan Rooij MC, Lusardi A, Alessie RJ (2011) Financial literacy and retirement planning in the Netherlands. J Econ Psychol 32(4):593–608. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.joep.2011.02.004\nYamane T (1967) Statistics, an introductory analysis, 2nd edn. Harper and Row, New York\nYe Y, Wang Y, Yang X (2022) Bank loan information and information asymmetry in the stock market: evidence from China. Financ Innov 8:62. https:\u002F\u002Fdoi.org\u002F10.1186\u002Fs40854-022-00367-0\nYoo B, Donthu N, Lenartowicz T (2011) Measuring Hofstede’s five dimensions of cultural values at the individual level: development and validation of CVSCALE. J Int Consum Mark 23(3–4):193–210. https:\u002F\u002Fdoi.org\u002F10.1080\u002F08961530.2011.578059",{"VOID":507},"10.1186\u002Fs40854-023-00573-4","2024-06-26T20:48:56.322+00:00","https:\u002F\u002Fjfin-swufe.springeropen.com\u002Farticles\u002F10.1186\u002Fs40854-023-00573-4",[511,529,544],{"id":512,"sortIndex":19,"researcher":18,"roles":513,"affiliations":515,"properties":524,"displayName":526,"givenName":18,"familyName":18},"4d410aaa-15ec-4b61-99e1-0929c791d365",[514],"AUTHOR",[516],{"id":517,"sortIndex":19,"affiliation":518,"properties":18},"0238cb2f-391e-4455-b482-0bfa0001eea0",{"id":517,"createTime":18,"updateTime":18,"relativeEntities":519,"slug":18,"properties":520,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":523,"statistic":18},[],{"title":521},{"VI":522},"Department of Software Engineering, Faculty of Engineering and Natural Sciences, Bandirma Onyedi Eylul University, Balikesir, Turkey",[],{"title":525,"gsAuthor":527},{"VI":526},"Ibrahim Arpaci",{"VOID":528},"[\"rFAIcLwAAAAJ\"]",{"id":530,"sortIndex":90,"researcher":18,"roles":531,"affiliations":532,"properties":539,"displayName":541,"givenName":18,"familyName":18},"578c6d3e-ca47-4e0b-b454-47d4e92d36d3",[514],[533],{"id":517,"sortIndex":19,"affiliation":534,"properties":18},{"id":517,"createTime":18,"updateTime":18,"relativeEntities":535,"slug":18,"properties":536,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":538,"statistic":18},[],{"title":537},{"VI":522},[],{"title":540,"gsAuthor":542},{"VI":541},"Omer 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study analyzes the relationship between savings, investment, and economic growth in Nepal over 1975–2016. The structural breaks in the variables have been accounted for using the (Zivot and Andrews’s, J Bus Econ Stat 10: 251–270 1992) unit root test along with (Gregory and Hansen’s, Oxf Bull Econ Stat 58: 555–560, 1996) cointegration approach. The ARDL approach to cointegration in the presence of structural breaks has also been utilized to analyze the long-and short-run dynamics of savings, investment, and growth in Nepal. The results show structural breaks in the real GDP per capita during 2001 when the Royal Massacre and a state of emergency have taken place in Nepal. After allowing for this structural break, evidence of a cointegration relationship amongst savings, investment, and economic growth was identified. The estimates of the ARDL approach suggest that investment has a significant and positive impact on economic growth. However, gross domestic savings have a negative impact on growth in the long run. These results clearly show weaknesses of the economy in mobilizing savings into productive sectors.",{"EN":622},"Savings, investment, and growth in Nepal: an empirical analysis",{"VOID":624},"[\"1465800090183978446\"]",{"VOID":626},"Abu N (2010) Saving-economic growth nexus in Nigeria, 1970–2007: Granger causality and co-integration analyses. Rev Econ Bus Stud 3(1):93–104\nAdhikary BK (2015) Dynamic Effects of FDI, Trade Openness, Capital Formation and Human Capital on the Economic Growth Rate in the Least Developed Economies: Evidence from Nepal. Int J Trade Econ Finance 6(1):1–7\nAghion P, Comin D, Howitt P, Tecu I (2016) When does domestic savings matter for economic growth? IMF Econ Rev 64(3):381–407\nAlguacil M, Cuadros A, Orts V (2004) Does saving really matter for growth? Mexico (1970–2000). J Int Dev 16(2):281–290\nAng JB (2007) Are saving and investment cointegrated? The case of Malaysia (1965–2003). Applied Econ 39(17):2167–2174\nArndt HW (1991) Saving, investment and growth: recent Asian experience. PSL Q Rev 44(177):151–162\nAttanasio OP, Picci L, Scorcu AE (2000) Saving, growth, and investment: a macroeconomic analysis using a panel of countries. Rev Econ Stat 82(2):182–211\nBist JP, Bista NB (2018) Finance–Growth Nexus in Nepal: An Application of the ARDL Approach in the Presence of Structural Breaks. Vikalpa 43(4):236–249\nBolarinwa ST, Obembe OB (2017) Empirical Analysis of the Nexus between Saving and Economic Growth in Selected African Countries (1981–2014). J Dev Policy Pract 2(1):110–129\nBudha B (2012) A multivariate analysis of savings, investment and growth in Nepal. Munich Personal RePEc Archive. Retrieved from google: https:\u002F\u002Fmpra.ub.uni-muenchen.de\u002F43346\u002F.\nCarroll CD, Overland J, Weil DN (2000) Saving and growth with habit formation. Am Econ Rev 90(3):341–355\nCarroll CD, Weil DN (1994) Saving and growth: a reinterpretation. Carnegie-Rochester Conference Series on Public Policy 40:133–192\nChao X, Kou G, Peng Y, Alsaadi F E (2019) Behavior monitoring methods for trade-based money laundering integrating macro and micro prudential regulation: a case from China. Technological and Economic Development of Economy, 1–16.\nDermirguc-Kunt A (2006). Finance and economic development: Policy choices for developing countries (Working Paper No. 3955). World Bank Policy Research. Retrieved from http:\u002F\u002Fdocuments.worldbank.org\u002Fcurated\u002Fen\u002F825071468316170479\u002Fpdf\u002Fwps3955.pdf\nDomar ED (1946) Capital expansion, rate of growth, and employment. Econometrica, Journal of the Econometric Society 14(2):137–147\nGavin M, Hausmann R, Tavli E (1997) Saving behavior in Latin America: overview and policy issues. In: Hausmann R, Reisen R (eds) Promoting Savings in Latin America. OECD and Inter-American Development Bank, Paris\nGregory AW, Hansen BE (1996) Practitioners corner: tests for cointegration in models with regime and trend shifts. Oxf Bull Econ Stat 58(3):555–560\nHarrod RF (1939) Toward a Dynamic Economic. Macmillan and Co. Ltd., London\nJangili R (2011) Causal relationship between saving, investment and economic growth for India–what does the relation imply?. Available at: https:\u002F\u002Fmpra.ub.uni-muenchen.de\u002F40002\u002F1\u002FMPRA_paper_40002.pdf\nKhundrakpam JK, Ranjan R (2010) Saving-investment nexus and international capital mobility in India: Revisiting Feldstein-Horioka hypothesis. Indian Econ Rev 45(1):49–66\nKou G, Chao X, Peng Y, Alsaadi FE, Herrera-Viedma E (2019) Machine learning methods for systemic risk analysis in financial sectors. Technological Econ Dev Econ 29:1–27\nLee CC, Chang CP (2005) Structural breaks, energy consumption, and economic growth revisited: Evidence from Taiwan. Energy Econ 27(6):857–872\nLevine R (1997) Financial development and economic growth: Views and agenda. J Econ Lit 35(2):688–726\nLucas RE Jr (1988) On the mechanics of economic development. J Monetary Econ 22(1):3–42\nMa W, Li H (2016) Time-varying saving–investment relationship and the Feldstein–Horioka puzzle. Econ Model 53:166–178\nMacKinnon JG, Haug AA, Michelis L (1999) Numerical distribution functions of likelihood ratio tests for cointegration. J Appl Econometrics 14(5):563–577\nMasih R, Peters S (2010) A revisitation of the savings–growth nexus in Mexico. Econ Lett 107(3):318–320\nMason A (1988) Saving, economic growth, and demographic change. Popul Dev Rev 14(1):113–144\nMohan R (2006) Causal relationship between savings and economic growth in countries with different income levels. Econ Bull 5(3):1–12\nNarayan PK (2005) The saving and investment nexus for China: evidence from cointegration tests. Appl Econ 37(17):1979–1990\nOdhiambo NM (2009) Savings and economic growth in South Africa: A multivariate causality test. J Policy Model 31(5):708–718\nPatra SK, Murthy DS, Kuruva MB, Mohanty A (2017) Revisiting the causal nexus between savings and economic growth in India: An empirical analysis. Economia 18(3):380–391\nPerron P (1989) The great crash, the oil price shock, and the unit root hypothesis. Econometrica 57(6):1361–1401\nPesaran M, Shin Y, Smith R (2001) Bounds testing approaches to the analysis of level relationships. J Appl Econ 16(3):289–326\nRomer PM (1986) Increasing returns and long-run growth. J Pol Econ 94(5):1002–1037\nSahoo P, Nataraj G, Kamaiah B (2001) Savings and Economic Growth in India: The Long Run Nexus. Savings Dev 25(1):67–80\nSingh T (2010) Does domestic saving cause economic growth? A time-series evidence from India. J Policy Model 32(2):231–253\nSinha D, Sinha T (1998) Cart before the horse? The saving–growth nexus in Mexico. Econ Lett 61(1):43–47\nSolow RM (1956) A contribution to the theory of economic growth. Q J Econ 70(1):65–94\nSolow RM (1988) Growth theory and after. Am Econ Rev 78(3):307–317\nSothan S (2014) Causal relationship between domestic saving and economic growth: Evidence from Cambodia. Int J Econ Finance 6(9):213–220\nSwan TW (1956) Economic growth and capital accumulation. Econ Rec 32(2):334–361\nTang CF, Chua SY (2012) The savings-growth nexus for the Malaysian economy: a view through rolling sub-samples. Appl Econ 44(32):4173–4185\nTang CF, Tan BW (2014) A revalidation of the savings–growth nexus in Pakistan. Econ Model 36:370–377\nToda HY, Yamamoto T (1995) Statistical inference in vector autoregressions with possibly integrated processes. J Econometrics 66(1–2):225–250\nVerma R (2007) Savings, investment and growth in India: an application of the ARDL bounds testing approach. South Asia Econ J 8(1):87–98\nWorld Bank (2018). World Development Indicators. Retrieved from: https:\u002F\u002Fdatabank.worldbank.org\u002Fsource\u002Fworld-development-indicators\nZivot E, Andrews DW (1992) Further evidence on the great crash, the oil-price shock, and the unit-root. J Bus Econ Stat 10(3):251–270",{"VOID":628},"10.1186\u002Fs40854-019-0154-0","2024-05-16T00:25:00.600+00:00","https:\u002F\u002Fjfin-swufe.springeropen.com\u002Farticles\u002F10.1186\u002Fs40854-019-0154-0",[632,649,666],{"id":633,"sortIndex":19,"researcher":18,"roles":634,"affiliations":635,"properties":644,"displayName":646,"givenName":18,"familyName":18},"e4884a2b-31ea-44a3-9687-9cb891feb49f",[514],[636],{"id":637,"sortIndex":19,"affiliation":638,"properties":18},"84dd451f-38db-44db-9c43-dec24eaf456d",{"id":637,"createTime":18,"updateTime":18,"relativeEntities":639,"slug":18,"properties":640,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":643,"statistic":18},[],{"title":641},{"VI":642},"Global College International affiliated to Midwestern University, Kathmandu, Nepal",[],{"title":645,"gsAuthor":647},{"VI":646},"Aadersh 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Bist",{"VOID":682},"[\"Eovo7NQAAAAJ\"]",{"url":630,"publisher":684,"properties":729},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":685,"slug":10,"properties":686,"entityType":16,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":19,"subjectFields":689,"manageAffiliations":698,"indexDatabases":709,"url":85,"thumbnailPath":18,"statistic":724,"gsStatistic":18,"type":93,"analyzePriority":18},[],{"issn":687,"title":688},{"VOID":13},{"EN":15},[690,694],{"id":22,"createTime":18,"updateTime":18,"relativeEntities":691,"label":692,"description":693,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":25},{},{"id":28,"createTime":18,"updateTime":18,"relativeEntities":695,"label":696,"description":697,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":31},{},[699,704],{"id":35,"createTime":18,"updateTime":18,"relativeEntities":700,"slug":18,"properties":701,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":703,"statistic":18},[],{"title":702},{"EN":39},[],{"id":42,"createTime":18,"updateTime":18,"relativeEntities":705,"slug":18,"properties":706,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":708,"statistic":18},[],{"title":707},{"EN":46},[],[710,717],{"id":50,"indexDatabase":711,"url":61,"indexYears":62,"academicFieldIds":716,"indexDatabaseRanking":66},{"id":52,"createTime":18,"updateTime":18,"relativeEntities":712,"label":713,"description":714,"key":58,"publicationTags":715,"standard":18},[],{"EN":55,"VI":55},{"EN":55,"VI":57},[60],[64,65],{"id":68,"indexDatabase":718,"url":81,"indexYears":18,"academicFieldIds":723,"indexDatabaseRanking":18},{"id":70,"createTime":18,"updateTime":18,"relativeEntities":719,"label":720,"description":721,"key":77,"publicationTags":722,"standard":18},[],{"EN":73,"VI":73},{"EN":75,"VI":76},[79,80],[83,84],{"impactFactor":19,"impactFactorByYear":725,"i10Index":19,"i10IndexLast5Year":19,"totalPublication":88,"totalPublicationByYear":726,"totalCitation":19,"totalCitationByYear":727,"totalCitationPerPublication":19,"totalCitationPerPublicationByYear":728,"hindexLast5Year":19,"hindex":19},{},{"2021":90,"2024":90},{},{},{"pages":730,"volume":732},{"VOID":731},"1-13",{"VOID":733},"5",{"total":19,"publishYear":735,"statisticByYear":736},2019,{},"2019-11-06","2026-07-22T00:53:42.517+00:00",[79,66],{"id":741,"createTime":742,"updateTime":743,"relativeEntities":744,"slug":745,"properties":746,"entityType":114,"verifyStatus":115,"verifyTime":755,"verifyNote":117,"languages":18,"translateLanguages":18,"viewCount":19,"primaryUrl":756,"fullTextUrl":18,"authors":757,"publicationType":143,"publisherRelationship":807,"citationCount":19,"citationInfo":856,"publishDate":858,"publishYear":735,"citationAnalyzeStatus":17,"lastCitationAnalyze":859,"indexDatabases":860,"openAccess":18,"references":861,"isForceReanalyzing":488},"eb80a2bf-ec18-4dd9-8017-490ce64ec296","2024-02-08T13:31:15.419+00:00","2026-05-05T02:24:04.795+00:00",[],"Effect-of-family-control-on-corporate-dividend-policy-of-firms-in-Pakistan",{"abstract":747,"title":749,"gsPaper":751,"doi":753},{"EN":748},"This study examines the impact of family control on the dividend policy of firms in Pakistan, covering the period from 2009 to 2016. It also investigates whether family control moderates the impact of firm-specific factors on the dividend policy. The GMM model for panel data estimation is used. The mean difference univariate analysis shows that family firms differ from nonfamily firms based on financial characteristics. The multivariate analysis shows that family firms pay lower dividends than nonfamily firms. Besides, firm size inversely affects the dividend policy, whereas tangibility positively affects it. Moreover, family control does not moderate the impact of all firm-specific factors on the dividend policy. Overall, family control, size, and tangibility are found to be the main determinants of the dividend policy in Pakistan.",{"EN":750},"Effect of family control on corporate dividend policy of firms in Pakistan",{"VOID":752},"[\"988554761649984880\"]",{"VOID":754},"10.1186\u002Fs40854-019-0158-9","2024-04-28T02:23:54.555+00:00","https:\u002F\u002Fjfin-swufe.springeropen.com\u002Farticles\u002F10.1186\u002Fs40854-019-0158-9",[758,775,790],{"id":759,"sortIndex":19,"researcher":18,"roles":760,"affiliations":761,"properties":770,"displayName":772,"givenName":18,"familyName":18},"9c81d66d-686f-4616-a8f0-8d407153e375",[514],[762],{"id":763,"sortIndex":19,"affiliation":764,"properties":18},"578c39c6-7711-4984-bccf-eb213b45f4e9",{"id":763,"createTime":18,"updateTime":18,"relativeEntities":765,"slug":18,"properties":766,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":769,"statistic":18},[],{"title":767},{"VI":768},"Faculty Member, Air University School of Management, Air University, Islamabad, Pakistan",[],{"title":771,"gsAuthor":773},{"VI":772},"Imran 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H, Attiya J (2009) Dynamics and determinants of dividend policy in Pakistan: evidence from Karachi stock exchange non-financial firms. 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Reg Stud 48(3):501–515",{"doi":867},{"id":18,"text":1357,"url":1358,"identifiers":1359},"Theurillat T, Corpataux J, Crevoisier O (2010) Property sector financialization: the case of swiss pension funds (1992–2005). Eur Plan Stud 18(2):189–212. https:\u002F\u002Fdoi.org\u002F10.1080\u002F09654310903491507","https:\u002F\u002Fdoi.org\u002F10.1080\u002F09654310903491507",{"doi":1360},"10.1080\u002F09654310903491507",{"id":863,"text":1362,"url":865,"identifiers":1363},"Tse RYC, Ganesan S (1997) Causal relationship between construction flows and GDP: evidence from Hong Kong. Constr Manag Econ 15(4):371–376",{"doi":867},{"id":18,"text":1365,"url":1366,"identifiers":1367},"Zhang H, Kou G, Peng Y (2019) Soft consensus cost models for group decision making and economic interpretations. Eur J Oper Res 277(3):964–980. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ejor.2019.03.009","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ejor.2019.03.009",{"mag":1368,"openalex":1369,"doi":1370},"2920878653","W2920878653","10.1016\u002Fj.ejor.2019.03.009",{"id":18,"text":1372,"url":1373,"identifiers":1374},"Zhu R, Hu X, Liu C (2020) Structural analysis of inter-industrial linkages: an application to the Australian construction industry. Constr Manag Econ. https:\u002F\u002Fdoi.org\u002F10.1080\u002F01446193.2020.1785627","https:\u002F\u002Fdoi.org\u002F10.1080\u002F01446193.2020.1785627",{"mag":1375,"openalex":1376,"doi":1377},"3038700608","W3038700608","10.1080\u002F01446193.2020.1785627",{"id":1379,"createTime":1380,"updateTime":1381,"relativeEntities":1382,"slug":1383,"properties":1384,"entityType":114,"verifyStatus":115,"verifyTime":1395,"verifyNote":117,"languages":1396,"translateLanguages":18,"viewCount":19,"primaryUrl":1397,"fullTextUrl":18,"authors":1398,"publicationType":143,"publisherRelationship":1435,"citationCount":1485,"citationInfo":1486,"publishDate":1489,"publishYear":1487,"citationAnalyzeStatus":1490,"lastCitationAnalyze":1491,"indexDatabases":1492,"openAccess":18,"references":1493,"isForceReanalyzing":488},"a4bc2bfb-6853-4344-80e7-8141f0d69e33","2024-04-17T19:30:21.693+00:00","2026-02-25T12:10:25.497+00:00",[],"Intraday-patterns-of-price-clustering-in-Bitcoin",{"openalex":1385,"abstract":1387,"title":1389,"gsPaper":1391,"doi":1393},{"VOID":1386},"W4206186897",{"EN":1388},"\u003Cjats:title>Abstract\u003C\u002Fjats:title>\u003Cjats:p>In this study, an investigation is conducted into the phenomenon of price clustering in Bitcoin (BTC) denominated in the Japanese yen (JPY). It answers two questions using tick-by-tick data. The first is whether price clustering exists in BTC\u002FJPY transactions, and the other is how the scale of price clustering varies throughout a trading day. With the assistance of statistical measures, the last two digits of BTC price were discovered to cluster at the numbers that end with ’00’. In addition, the scales of BTC\u002FJPY clustering at ’00’ tended to decline at the specific hour intervals. This study contributes to the emerging literature on price clustering and investor behavior.\u003C\u002Fjats:p>",{"EN":1390},"Intraday patterns of price clustering in Bitcoin",{"VOID":1392},"[]",{"VOID":1394},"10.1186\u002Fs40854-021-00307-4","2024-05-16T12:04:15.020+00:00",[119],"https:\u002F\u002Fjfin-swufe.springeropen.com\u002Farticles\u002F10.1186\u002Fs40854-021-00307-4",[1399,1418],{"id":1400,"sortIndex":19,"researcher":18,"roles":1401,"affiliations":1402,"properties":1411,"displayName":1415,"givenName":18,"familyName":18},"e0a7faef-2ae1-4117-a632-b019b7141bc3",[],[1403],{"id":1404,"sortIndex":19,"affiliation":1405,"properties":18},"688f491f-bb6a-4842-8de2-4a02b2c3f1bb",{"id":1404,"createTime":18,"updateTime":18,"relativeEntities":1406,"slug":18,"properties":1407,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1410,"statistic":18},[],{"title":1408},{"VI":1409},"Shenzhen Audencia Business School, Shenzhen University, Shenzhen 518060, China",[],{"orcid":1412,"title":1414,"openalex":1416},{"VOID":1413},"https:\u002F\u002Forcid.org\u002F0000-0002-8885-0477",{"EN":1415},"Donglian Ma",{"VOID":1417},"A5027155545",{"id":1419,"sortIndex":90,"researcher":18,"roles":1420,"affiliations":1421,"properties":1430,"displayName":1432,"givenName":18,"familyName":18},"35a34925-b4da-4d26-940f-4ab778444404",[],[1422],{"id":1423,"sortIndex":19,"affiliation":1424,"properties":18},"9cb7e334-609c-4cdb-b490-62ab2371a170",{"id":1423,"createTime":18,"updateTime":18,"relativeEntities":1425,"slug":18,"properties":1426,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1429,"statistic":18},[],{"title":1427},{"EN":1428},"Graduate School of Economics, Osaka University, Osaka, 560-0043, Japan",[],{"title":1431,"openalex":1433},{"EN":1432},"Hisashi Tanizaki",{"VOID":1434},"A5082595689",{"url":18,"publisher":1436,"properties":1481},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":1437,"slug":10,"properties":1438,"entityType":16,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":19,"subjectFields":1441,"manageAffiliations":1450,"indexDatabases":1461,"url":85,"thumbnailPath":18,"statistic":1476,"gsStatistic":18,"type":93,"analyzePriority":18},[],{"issn":1439,"title":1440},{"VOID":13},{"EN":15},[1442,1446],{"id":22,"createTime":18,"updateTime":18,"relativeEntities":1443,"label":1444,"description":1445,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":25},{},{"id":28,"createTime":18,"updateTime":18,"relativeEntities":1447,"label":1448,"description":1449,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":31},{},[1451,1456],{"id":35,"createTime":18,"updateTime":18,"relativeEntities":1452,"slug":18,"properties":1453,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1455,"statistic":18},[],{"title":1454},{"EN":39},[],{"id":42,"createTime":18,"updateTime":18,"relativeEntities":1457,"slug":18,"properties":1458,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1460,"statistic":18},[],{"title":1459},{"EN":46},[],[1462,1469],{"id":50,"indexDatabase":1463,"url":61,"indexYears":62,"academicFieldIds":1468,"indexDatabaseRanking":66},{"id":52,"createTime":18,"updateTime":18,"relativeEntities":1464,"label":1465,"description":1466,"key":58,"publicationTags":1467,"standard":18},[],{"EN":55,"VI":55},{"EN":55,"VI":57},[60],[64,65],{"id":68,"indexDatabase":1470,"url":81,"indexYears":18,"academicFieldIds":1475,"indexDatabaseRanking":18},{"id":70,"createTime":18,"updateTime":18,"relativeEntities":1471,"label":1472,"description":1473,"key":77,"publicationTags":1474,"standard":18},[],{"EN":73,"VI":73},{"EN":75,"VI":76},[79,80],[83,84],{"impactFactor":19,"impactFactorByYear":1477,"i10Index":19,"i10IndexLast5Year":19,"totalPublication":88,"totalPublicationByYear":1478,"totalCitation":19,"totalCitationByYear":1479,"totalCitationPerPublication":19,"totalCitationPerPublicationByYear":1480,"hindexLast5Year":19,"hindex":19},{},{"2021":90,"2024":90},{},{},{"issue":1482,"volume":1483},{"VOID":192},{"VOID":1484},"8",8,{"total":1485,"publishYear":1487,"statisticByYear":1488},2022,{"2022":88,"2023":90,"2024":1104},"2022-12-01","ERROR_IN_GET_PLATFORM_ID","2026-02-25T12:10:25.496+00:00",[79,66],[1494,1498,1502,1506,1509,1513,1517,1521,1525,1529,1533,1537,1541,1545,1549,1553,1557,1561,1565,1569,1573,1577,1581,1585,1589,1593,1597,1601,1605,1609,1613,1617,1621,1625,1629,1633,1637,1641,1645,1649,1652,1656,1660,1664,1668,1671,1675,1679,1683,1687,1691,1695,1699,1703,1707,1711,1715,1719,1723,1727,1731,1735,1739,1743],{"id":18,"text":1495,"url":18,"identifiers":1496},"Aggarwal R, Lucey BM (2007) Psychological barriers in gold prices? 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Econometrica 33(1):88–113. https:\u002F\u002Fdoi.org\u002F10.2307\u002F1911890",{"doi":1690},"10.2307\u002F1911890",{"id":18,"text":1692,"url":18,"identifiers":1693},"Palao F, Pardo A (2012) Assessing price clustering in European carbon markets. Appl Energy 92:51–56. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.apenergy.2011.10.022",{"doi":1694},"10.1016\u002Fj.apenergy.2011.10.022",{"id":18,"text":1696,"url":18,"identifiers":1697},"Petukhina AA, Reule RCG, Härdle WK (2021) Rise of the machines? Intraday high-frequency trading patterns of cryptocurrencies. Eur J Finance 27(1–2):8–30. https:\u002F\u002Fdoi.org\u002F10.1080\u002F1351847X.2020.1789684. arXiv:2009.04200",{"doi":1698},"10.1080\u002F1351847X.2020.1789684",{"id":18,"text":1700,"url":18,"identifiers":1701},"Schwartz AL, Van Ness BF, Van Ness RA (2004) Clustering in the futures market: evidence from S&P 500 futures contracts. J Future Mark 24(5):413–428. https:\u002F\u002Fdoi.org\u002F10.1002\u002Ffut.10129",{"doi":1702},"10.1002\u002Ffut.10129",{"id":18,"text":1704,"url":18,"identifiers":1705},"Sifat IM, Mohamad A, Mohamed Shariff MSB (2019) Lead-Lag relationship between Bitcoin and Ethereum: evidence from hourly and daily data. Res Int Bus Finance 50:306–321. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ribaf.2019.06.012",{"doi":1706},"10.1016\u002Fj.ribaf.2019.06.012",{"id":18,"text":1708,"url":18,"identifiers":1709},"Sigaki HYD, Perc M, Ribeiro HV (2019) Clustering patterns in efficiency and the coming-of-age of the cryptocurrency market. Sci Rep 9(1440):1–9. https:\u002F\u002Fdoi.org\u002F10.1038\u002Fs41598-018-37773-3",{"doi":1710},"10.1038\u002Fs41598-018-37773-3",{"id":18,"text":1712,"url":18,"identifiers":1713},"Sonnemans J (2006) Price clustering and natural resistance points in the Dutch stock market: a natural experiment. Eur Econ Rev 50(8):1937–1950. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.euroecorev.2005.09.001",{"doi":1714},"10.1016\u002Fj.euroecorev.2005.09.001",{"id":18,"text":1716,"url":18,"identifiers":1717},"Sopranzetti BJ, Datar V (2002) Price clustering in foreign exchange spot markets. J Financial Mark 5(4):411–417. https:\u002F\u002Fdoi.org\u002F10.1016\u002FS1386-4181(01)00032-5",{"doi":1718},"10.1016\u002FS1386-4181(01)00032-5",{"id":18,"text":1720,"url":18,"identifiers":1721},"Urquhart A (2016) The inefficiency of Bitcoin. Econ Lett 148:80–82. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.econlet.2016.09.019",{"doi":1722},"10.1016\u002Fj.econlet.2016.09.019",{"id":18,"text":1724,"url":18,"identifiers":1725},"Urquhart A (2017) Price clustering in Bitcoin. Econ Lett 159:145–148. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.econlet.2017.07.035",{"doi":1726},"10.1016\u002Fj.econlet.2017.07.035",{"id":18,"text":1728,"url":18,"identifiers":1729},"Verousis T, Ap Gwilym O (2013) Trade size clustering and the cost of trading at the London Stock Exchange. Int Rev Financial Anal 27:91–102. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.irfa.2012.08.007",{"doi":1730},"10.1016\u002Fj.irfa.2012.08.007",{"id":18,"text":1732,"url":18,"identifiers":1733},"Verousis T, Ap Gwilym O (2014) The implications of a price anchoring effect at the upstairs market of the London Stock Exchange. Int Rev Financial Anal 32:37–46. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.irfa.2013.12.001",{"doi":1734},"10.1016\u002Fj.irfa.2013.12.001",{"id":18,"text":1736,"url":18,"identifiers":1737},"Yarovaya L, Ziȩba D (2020) Intraday volume-return nexus in cryptocurrency markets: a novel evidence from cryptocurrency classification. SSRN Electron J. https:\u002F\u002Fdoi.org\u002F10.2139\u002Fssrn.3711667",{"doi":1738},"10.2139\u002Fssrn.3711667",{"id":18,"text":1740,"url":18,"identifiers":1741},"Zargar FN, Kumar D (2019) Informational inefficiency of Bitcoin: a study based on high-frequency data. Res Int Bus Finance 47:344–353. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ribaf.2018.08.008",{"doi":1742},"10.1016\u002Fj.ribaf.2018.08.008",{"id":18,"text":1744,"url":18,"identifiers":1745},"Zhang Y, Chan S, Chu J, Nadarajah S (2019) Stylised facts for high frequency cryptocurrency data. Physica A 513:598–612. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.physa.2018.09.042",{"doi":1746},"10.1016\u002Fj.physa.2018.09.042",{"id":1748,"createTime":1749,"updateTime":1750,"relativeEntities":1751,"slug":1752,"properties":1753,"entityType":114,"verifyStatus":115,"verifyTime":1763,"verifyNote":117,"languages":18,"translateLanguages":18,"viewCount":19,"primaryUrl":1764,"fullTextUrl":18,"authors":1765,"publicationType":143,"publisherRelationship":1794,"citationCount":18,"citationInfo":18,"publishDate":1845,"publishYear":1846,"citationAnalyzeStatus":1490,"lastCitationAnalyze":1847,"indexDatabases":1848,"openAccess":18,"references":18,"isForceReanalyzing":488},"18c88314-3ca1-4bcd-80b9-23b318689360","2024-01-04T08:06:41.456+00:00","2026-02-13T09:32:37.458+00:00",[],"Effect-of-interest-rate-on-economic-performance-evidence-from-Islamic-and-non-Islamic-economies",{"abstract":1754,"title":1756,"gsPaper":1758,"references":1759,"doi":1761},{"EN":1755},"Saving and investment are two of the most important tools for economic growth. The interest rate has always been considered an important determinant of saving and investment. However, according to Islamic teachings, riba or earning interest on saving or investment is forbidden, and thus, many Muslims try to avoid earning income from the interest rate. Therefore, the aim of this study is to assess the effects of this religious guideline on the financial decisions of an Islamic country’s population and its impact on saving and investment. We applied the random effect and system generalized method of moments (GMM) model separately to data of 17 non-Islamic and 17 Islamic countries from 2005 to 2013. The results suggest that people in Islamic countries are not concerned about the interest rate on saving, but in non-Islamic countries, the interest rate, per capita income, and inflation have significant positive impacts, and national expenditure has a significant negative impact on saving. However, in Islamic countries, remittances received and national expenditure have negative significant impacts, and per capita income has a positive significant impact on saving. In the case of investment, interest rate and inflation show a negative effect on investment while trade affects investment positively in both Islamic and non-Islamic countries. Furthermore, domestic credit provided by banks has a negative significant effect on investment in non-Islamic countries, while in Islamic countries, remittances show a positive significant impact on investment. The governments and policy makers of Islamic countries should not imitate the economic policies of non-Islamic countries because religious factors play an important role in the interest rate–saving relationship. Instead, they should increase per capita income by improving employment conditions and by reducing remittances received and national expenditure. Policies on saving should not allow earning interest. Furthermore, in order to increase investment, efforts should be made to lower the interest rate and inflation, and to enhance remittances received and trade. These policies will increase saving and investment in Islamic countries, ultimately resulting in improved economic growth.",{"EN":1757},"Effect of interest rate on economic performance: evidence from Islamic and non-Islamic economies",{"VOID":1392},{"VOID":1760},"Anyanwu JC, Oaikhenan HE (1995) Modern macroeconomics : theory and applications in Nigeria”\nArellano M, Bover O (1995) Another look at the instrumental variable estimation of error-components models. J Econ 68(1):29–51\nAthukorala PC (1998) Interest rates, saving and investment: evidence from India. J Oxford Development Studies 26:2\nAysan, A., Gaobo, P. and Marie-Ange Veganzones-Varoudakis. (2005). How to Boost Private Investment in the MENA Countries: The Role of Economic Reforms. Topics in Middle Eastern and North African Economics, MEEA, Online Journal, (VII): 1-15. [Online] Available: http:\u002F\u002Fwww.luc.edu\u002Forgs\u002Fmeea\u002Fvolume7\u002FAysan.pdf\nBader M, Malawi AI (2010) The impact of interest rate on investment in Jordan: a cointegration analysis. Journal of King Abdul Aziz University: Economics and Administration 24(1):199–209\nChristy and Clendenin (1976) Introduction to Investment. Bellwood Publishers, pp.24–53\nEl Khamlichi A, K. Laaradh (2012) Performance persistence of Islamic Equity Mutual Funds, International Islamic Capital Market Conference, pp. 19–20\nGeng, Nan and N’Diaye Papa (2012) Determinants of corporate investment in China: Evidence from cross-country firm level data. IMF Working Paper No. WP\u002F 12\u002F80, International Monetary Fund\nGerrard P, Barton Cunningham J (1997) Islamic banking: a study in Singapore”. Int J Bank Mark 15(6):204\nGreene J, Villanueva D (1990) Determinants of private investment in LDCs. Finance and Development 27(4):40\nHaron, Noraffifah A (2000) The effect of conventional interest rates and rate of profit on funds deposited with Islamic Banking System in Malaysia. International Journal of Islamic Financial Services 1:3\nHyder K, Ahmed QM (2003) Why private investment in Pakistan has collapsed and how it can be restored. Lahore J Econ 9.1:108\nJalaluddin AKM (1992) Savings behaviour in Islamic framework. Econ Bull (Persatuan Ekonomi, Kajian Perniagaan dan Pengurusan, Shah Alam) 2(3):71–85\nOnwumere JUJ, Okore OA, Ibe IG (2012) The impact of interest rate liberalization on savings and investment: Evidence from Nigeria”. RJFA 3:10\nKasri RA, Kassim SH (2009) Empirical determinants of saving in the Islamic banks: evidence from Indonesia”. J King Abdulaziz University: Islamic Economics 22:181–201\nKassim S, Majid MA, Yusof RM (2009) Impact of monetary policy shocks on conventional and Islamic banks in a dual banking system: evidence from Malaysia. J Econ Coop Dev 30:41–58\nKeynes JM (1936) The General Theory of Employment, Interest and Money”. Macmillan, London\nKhan AH, Hasan L, Malik A, Knerr B (1992) dependency ratio, foreign capital inflows and the rate of savings in Pakistan [with comments]. The Pakistan Dev Rev 31(4):843–856\nLarsen EJ (2004) The impact of loan rates on direct real estate investment holding period return. Financial Services Review 13:111–121\nLevin A, Lin CF, Chu CSJ (2002) Unit root tests in panel data: asymptotic and finite-sample properties. J Econ 108(1):1–24\nMohsen M, Rezazadeh Karsalari A (2011) The non-linear relationship between private investment and real interest rates based on dynamic threshold panel: the case of developing countries. JMIB 21:32–42\nMetawa SA, Almossawi M (1998) Banking behavior of Islamic bank customers: perspectives and implications. IJBM 16:299–313\nMetwally MM (1997) Differences between the financial characteristics of interest-free banks and conventional banks. Eur Bus Rev 97(2):92–98\nMuhammad DS, Lakhan R, Ghulam M, Numan (2013) Rate of interest and its impact on investment to the extent of Pakistan. Pakistan Journal of Commerce and Social Sciences 7(1):91–99\nNasir S, Khalid M (2004) Saving-investment behaviour in Pakistan: an empirical investigation. The Pakistan Dev Rev 43(4):665–682\nPattanaik, Behera, Rajesh (2013) Real interest rate impact on investment and growth-What the empirical evidence for India suggests. Reserve Bank of India. Available at https:\u002F\u002Fwww.rbi.org.in\u002FScripts\u002FPublicationsView.aspx?id=15113\nSalahuddin M, Islam MR, Salim SA (2009) Determinants of investment in muslim Developing countries:An empirical investigation”. Int J Econ Manag 3(1):100–129\nSmith A (1776) An inquiry into the nature and causes of the wealth of nations: Volume One\nThe Qur’an, the Holy Book of the Muslims\nTokuoka, Kiichi (2012) Does the Business Environment Affect Corporate Investment in India? IMF Working Paper, WP\u002F12\u002F70.\nUusmani MT, Taqī ʻUs̲mānī M (2002) An introduction to Islamic finance (Vol. 20). Brill.\nWang DH, Yu TH (2007) The role of interest rate in investment decisions: a fuzzy logic framework. Global Business and Economic Review 9(4):448–457\nWorld Bank development indicators (WDI) (various issues)",{"VOID":1762},"10.1186\u002Fs40854-016-0028-7","2024-05-14T04:08:23.707+00:00","https:\u002F\u002Fjfin-swufe.springeropen.com\u002Farticles\u002F10.1186\u002Fs40854-016-0028-7",[1766,1781],{"id":1767,"sortIndex":19,"researcher":18,"roles":1768,"affiliations":1769,"properties":1778,"displayName":1780,"givenName":18,"familyName":18},"bfed073e-ecff-4ad1-8ade-37ff26a5ebab",[514],[1770],{"id":1771,"sortIndex":19,"affiliation":1772,"properties":18},"7a20d65f-9973-4e14-8992-d05584458044",{"id":1771,"createTime":18,"updateTime":18,"relativeEntities":1773,"slug":18,"properties":1774,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1777,"statistic":18},[],{"title":1775},{"VI":1776},"Karachi University Business School, University of Karachi, Karachi, Pakistan",[],{"title":1779},{"VI":1780},"Saba Mushtaq",{"id":1782,"sortIndex":90,"researcher":18,"roles":1783,"affiliations":1784,"properties":1791,"displayName":1793,"givenName":18,"familyName":18},"396433a7-c4f4-4edf-9aac-42503c89dbfa",[514],[1785],{"id":1771,"sortIndex":19,"affiliation":1786,"properties":18},{"id":1771,"createTime":18,"updateTime":18,"relativeEntities":1787,"slug":18,"properties":1788,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1790,"statistic":18},[],{"title":1789},{"VI":1776},[],{"title":1792},{"VI":1793},"Danish Ahmed Siddiqui",{"url":1764,"publisher":1795,"properties":1840},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":1796,"slug":10,"properties":1797,"entityType":16,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":19,"subjectFields":1800,"manageAffiliations":1809,"indexDatabases":1820,"url":85,"thumbnailPath":18,"statistic":1835,"gsStatistic":18,"type":93,"analyzePriority":18},[],{"issn":1798,"title":1799},{"VOID":13},{"EN":15},[1801,1805],{"id":22,"createTime":18,"updateTime":18,"relativeEntities":1802,"label":1803,"description":1804,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":25},{},{"id":28,"createTime":18,"updateTime":18,"relativeEntities":1806,"label":1807,"description":1808,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":31},{},[1810,1815],{"id":35,"createTime":18,"updateTime":18,"relativeEntities":1811,"slug":18,"properties":1812,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1814,"statistic":18},[],{"title":1813},{"EN":39},[],{"id":42,"createTime":18,"updateTime":18,"relativeEntities":1816,"slug":18,"properties":1817,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1819,"statistic":18},[],{"title":1818},{"EN":46},[],[1821,1828],{"id":50,"indexDatabase":1822,"url":61,"indexYears":62,"academicFieldIds":1827,"indexDatabaseRanking":66},{"id":52,"createTime":18,"updateTime":18,"relativeEntities":1823,"label":1824,"description":1825,"key":58,"publicationTags":1826,"standard":18},[],{"EN":55,"VI":55},{"EN":55,"VI":57},[60],[64,65],{"id":68,"indexDatabase":1829,"url":81,"indexYears":18,"academicFieldIds":1834,"indexDatabaseRanking":18},{"id":70,"createTime":18,"updateTime":18,"relativeEntities":1830,"label":1831,"description":1832,"key":77,"publicationTags":1833,"standard":18},[],{"EN":73,"VI":73},{"EN":75,"VI":76},[79,80],[83,84],{"impactFactor":19,"impactFactorByYear":1836,"i10Index":19,"i10IndexLast5Year":19,"totalPublication":88,"totalPublicationByYear":1837,"totalCitation":19,"totalCitationByYear":1838,"totalCitationPerPublication":19,"totalCitationPerPublicationByYear":1839,"hindexLast5Year":19,"hindex":19},{},{"2021":90,"2024":90},{},{},{"pages":1841,"volume":1843},{"VOID":1842},"1-14",{"VOID":1844},"2","2016-07-29",2016,"2026-02-13T09:32:37.457+00:00",[79,66],{"id":1850,"createTime":1851,"updateTime":1852,"relativeEntities":1853,"slug":1854,"properties":1855,"entityType":114,"verifyStatus":115,"verifyTime":1864,"verifyNote":117,"languages":18,"translateLanguages":18,"viewCount":19,"primaryUrl":1865,"fullTextUrl":18,"authors":1866,"publicationType":143,"publisherRelationship":1942,"citationCount":19,"citationInfo":1993,"publishDate":1996,"publishYear":1994,"citationAnalyzeStatus":17,"lastCitationAnalyze":1997,"indexDatabases":1998,"openAccess":18,"references":1999,"isForceReanalyzing":488},"448cda6c-2655-4907-8023-e5698bf8ffc1","2023-12-08T06:50:19.490+00:00","2026-01-31T14:13:39.103+00:00",[],"Insurance-market-density-and-economic-growth-in-Eurozone-countries-the-granger-causality-approach",{"abstract":1856,"title":1858,"gsPaper":1860,"doi":1862},{"EN":1857},"This study examines the relationship between insurance market density (IMD) and economic growth. We employed Granger causality technique in 19 Eurozone countries for the period 1980-2014. We use three different indicators of IMD, namely life insurance density, non-life insurance density, and total insurance density. We particularly emphasize on whether Granger causality runs between IMD and economic growth both ways, one way, or not at all. Our empirical result recognizes the presence of both unidirectional and bidirectional causality between insurance market density and economic growth. However, these results are mostly non-uniform across Eurozone countries. This study holds important policy implications- economic policies should recognize the differences in the insurance market density and economic growth in order to maintain sustainable economic growth in the Eurozone.",{"EN":1859},"Insurance market density and economic growth in Eurozone countries: the granger causality approach",{"VOID":1861},"[\"4324319171053640127\"]",{"VOID":1863},"10.1186\u002Fs40854-017-0065-x","2024-04-29T02:43:13.228+00:00","http:\u002F\u002Fjfin-swufe.springeropen.com\u002Farticles\u002F10.1186\u002Fs40854-017-0065-x",[1867,1882,1897,1914,1929],{"id":1868,"sortIndex":19,"researcher":18,"roles":1869,"affiliations":1870,"properties":1879,"displayName":1881,"givenName":18,"familyName":18},"59ef1ee7-2860-4a64-af71-aad171d9f3ba",[514],[1871],{"id":1872,"sortIndex":19,"affiliation":1873,"properties":18},"6a9bb456-55ab-4f12-999a-f81f063cdd79",{"id":1872,"createTime":18,"updateTime":18,"relativeEntities":1874,"slug":18,"properties":1875,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1878,"statistic":18},[],{"title":1876},{"VI":1877},"Vinod Gupta School of Management, Indian Institute of Technology Kharagpur, India",[],{"title":1880},{"VI":1881},"Rudra P. Pradhan",{"id":1883,"sortIndex":90,"researcher":18,"roles":1884,"affiliations":1885,"properties":1892,"displayName":1894,"givenName":18,"familyName":18},"b5e7a1c2-72ae-402f-8ada-5babbf891050",[514],[1886],{"id":1872,"sortIndex":19,"affiliation":1887,"properties":18},{"id":1872,"createTime":18,"updateTime":18,"relativeEntities":1888,"slug":18,"properties":1889,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1891,"statistic":18},[],{"title":1890},{"VI":1877},[],{"title":1893,"gsAuthor":1895},{"VI":1894},"Saurav 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Doctoral Dissertation, University of Nebraska, Lincoln",{"doi":867},{"id":863,"text":2280,"url":865,"identifiers":2281},"Ward D, Zurbruegg R (2000) Does insurance promote economic growth? Evidence from OECD countries. J Risk Insur 67(4):489–506",{"doi":867},{"id":18,"text":2283,"url":18,"identifiers":2284},"Wasow B, Hill RD (1986) Determinants of insurance penetration: a cross-country analysis. In: B. Wasow B, Hill RD (eds) Insurance industry in economic development. New York University Press, New York, pp 160–176",{},{"id":863,"text":2286,"url":865,"identifiers":2287},"Webb IP, Grace MF, Skipper HD (2005a) The effect of banking and insurance on the growth of capital and output. SBS Revista De TermasFinancieros 2(2):1–32",{"doi":867},{"id":863,"text":2289,"url":865,"identifiers":2290},"Webb IP, Grace MF, Skpper HD (2005b) The Effect of Banking and Insurance on the Growth of Capital and Output. SBS Revista De Termas Financieros 2(2):1–32",{"doi":867},{"id":2292,"createTime":2293,"updateTime":2294,"relativeEntities":2295,"slug":2296,"properties":2297,"entityType":114,"verifyStatus":115,"verifyTime":2306,"verifyNote":117,"languages":18,"translateLanguages":18,"viewCount":19,"primaryUrl":2307,"fullTextUrl":18,"authors":2308,"publicationType":143,"publisherRelationship":2351,"citationCount":19,"citationInfo":2402,"publishDate":2405,"publishYear":2403,"citationAnalyzeStatus":17,"lastCitationAnalyze":2294,"indexDatabases":2406,"openAccess":18,"references":2407,"isForceReanalyzing":488},"cad48403-a591-45b6-809f-29d84c4e6b92","2024-01-09T07:47:46.175+00:00","2026-01-22T16:43:34.368+00:00",[],"Nexus-between-foreign-direct-investment-and-economic-growth-in-Bangladesh-an-augmented-autoregressive-distributed-lag-bounds-testing-approach",{"abstract":2298,"title":2300,"gsPaper":2302,"doi":2304},{"EN":2299},"The relationship between foreign direct investment (FDI) inflows and economic growth in host countries is a heavily debated issue. Although some studies have found evidence of the positive impact of FDI on economic growth, others have revealed the opposite result. Studies that examined the causality between FDI and gross domestic product (GDP) also have found evidence of unidirectional causality and, in some cases, a bidirectional causality. This study investigated the causal nexus between FDI and GDP in Bangladesh by employing standard time-series econometric tools, namely, augmented Dickey-Fuller, augmented Dickey-Fuller generalized least square, Kwiatkowski-Phillips-Schmidt-Shin, and Lee-Strazicich unit root tests to check stationarity, augmented autoregressive distributed lag (augmented ARDL) bounds testing approach to check cointegration, and Granger causality to explore the direction of causality. The augmented ARDL model found a long-run relationship between FDI and GDP. In addition, the error correction model and Granger causality results indicated the presence of a unidirectional causality running from GDP to FDI.",{"EN":2301},"Nexus between foreign direct investment and economic growth in Bangladesh: an augmented autoregressive distributed lag bounds testing approach",{"VOID":2303},"[\"8963013476530052705\"]",{"VOID":2305},"10.1186\u002Fs40854-019-0164-y","2024-05-07T23:23:43.255+00:00","https:\u002F\u002Fjfin-swufe.springeropen.com\u002Farticles\u002F10.1186\u002Fs40854-019-0164-y",[2309,2334],{"id":2310,"sortIndex":19,"researcher":18,"roles":2311,"affiliations":2312,"properties":2329,"displayName":2331,"givenName":18,"familyName":18},"78778f6c-85af-43ee-827a-3bbfd581c344",[514],[2313,2321],{"id":2314,"sortIndex":19,"affiliation":2315,"properties":18},"321e2a06-d159-48b5-ab4b-e15dbc8d0540",{"id":2314,"createTime":18,"updateTime":18,"relativeEntities":2316,"slug":18,"properties":2317,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":2320,"statistic":18},[],{"title":2318},{"VI":2319},"Department of Economics, University of Manitoba, Winnipeg, Canada",[],{"id":2322,"sortIndex":90,"affiliation":2323,"properties":18},"79b83c1d-069d-4568-96f7-97abf53e326f",{"id":2322,"createTime":18,"updateTime":18,"relativeEntities":2324,"slug":18,"properties":2325,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":2328,"statistic":18},[],{"title":2326},{"VI":2327},"Department of Economics, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, Bangladesh",[],{"title":2330,"gsAuthor":2332},{"VI":2331},"Bibhuti Sarker",{"VOID":2333},"[\"a_aUq30AAAAJ\"]",{"id":2335,"sortIndex":90,"researcher":18,"roles":2336,"affiliations":2337,"properties":2346,"displayName":2348,"givenName":18,"familyName":18},"d60eae20-6b96-4927-9ded-c97c6392fb0d",[514],[2338],{"id":2339,"sortIndex":19,"affiliation":2340,"properties":18},"65cb9cd4-6b7b-4661-9501-7fc64f4a329e",{"id":2339,"createTime":18,"updateTime":18,"relativeEntities":2341,"slug":18,"properties":2342,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":2345,"statistic":18},[],{"title":2343},{"VI":2344},"Department of Economics, Rajshahi University, Rajshahi, Bangladesh",[],{"title":2347,"gsAuthor":2349},{"VI":2348},"Farid Khan",{"VOID":2350},"[\"evO_n_kAAAAJ\"]",{"url":2307,"publisher":2352,"properties":2397},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":2353,"slug":10,"properties":2354,"entityType":16,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":19,"subjectFields":2357,"manageAffiliations":2366,"indexDatabases":2377,"url":85,"thumbnailPath":18,"statistic":2392,"gsStatistic":18,"type":93,"analyzePriority":18},[],{"issn":2355,"title":2356},{"VOID":13},{"EN":15},[2358,2362],{"id":22,"createTime":18,"updateTime":18,"relativeEntities":2359,"label":2360,"description":2361,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":25},{},{"id":28,"createTime":18,"updateTime":18,"relativeEntities":2363,"label":2364,"description":2365,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":31},{},[2367,2372],{"id":35,"createTime":18,"updateTime":18,"relativeEntities":2368,"slug":18,"properties":2369,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":2371,"statistic":18},[],{"title":2370},{"EN":39},[],{"id":42,"createTime":18,"updateTime":18,"relativeEntities":2373,"slug":18,"properties":2374,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":2376,"statistic":18},[],{"title":2375},{"EN":46},[],[2378,2385],{"id":50,"indexDatabase":2379,"url":61,"indexYears":62,"academicFieldIds":2384,"indexDatabaseRanking":66},{"id":52,"createTime":18,"updateTime":18,"relativeEntities":2380,"label":2381,"description":2382,"key":58,"publicationTags":2383,"standard":18},[],{"EN":55,"VI":55},{"EN":55,"VI":57},[60],[64,65],{"id":68,"indexDatabase":2386,"url":81,"indexYears":18,"academicFieldIds":2391,"indexDatabaseRanking":18},{"id":70,"createTime":18,"updateTime":18,"relativeEntities":2387,"label":2388,"description":2389,"key":77,"publicationTags":2390,"standard":18},[],{"EN":73,"VI":73},{"EN":75,"VI":76},[79,80],[83,84],{"impactFactor":19,"impactFactorByYear":2393,"i10Index":19,"i10IndexLast5Year":19,"totalPublication":88,"totalPublicationByYear":2394,"totalCitation":19,"totalCitationByYear":2395,"totalCitationPerPublication":19,"totalCitationPerPublicationByYear":2396,"hindexLast5Year":19,"hindex":19},{},{"2021":90,"2024":90},{},{},{"pages":2398,"volume":2400},{"VOID":2399},"1-18",{"VOID":2401},"6",{"total":19,"publishYear":2403,"statisticByYear":2404},2020,{},"2020-02-06",[79,66],[2408,2415,2421,2427,2430,2436,2442,2446,2452,2455,2461,2468,2474,2479,2485,2488,2494,2497,2503,2508,2515,2521,2528,2534,2540,2546,2552,2558,2564,2570,2576,2582,2589,2595,2601,2607,2614,2617,2623,2626,2632,2638,2644,2650,2653,2659,2662,2668,2671,2677,2683,2689,2692,2698,2704,2710,2713,2716,2722,2728,2734,2740,2743,2749,2755,2762,2768,2775,2781,2787,2793,2799,2802,2808,2814],{"id":18,"text":2409,"url":2410,"identifiers":2411},"Adhikary 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