The Knowledge Structure, Emerging Trends, and Future Directions of Stock Market Volatility Research: A Bibliometric Review

Ubaid Ahmad  Peer; Rupinder Katoch; Muzzamil Rehman; Komal Diwakar; Mehjabeen Nish

doi:10.47743/saeb-2026-0020

Authors

Ubaid Ahmad Peer Mittal School of Business, Lovely Professional University, Punjab, India
Rupinder Katoch Mittal School of Business, Lovely Professional University, Punjab, India
Muzzamil Rehman Mittal School of Business, Lovely Professional University, Punjab, India
Komal Diwakar Sanjivani University, Kopargaon, Near Shirdi, Ahilyanagar (Ahmednagar)
Mehjabeen Nish Acharya Bangalore B-School, Karnataka, India

DOI:

https://doi.org/10.47743/saeb-2026-0020

Keywords:

bibliometric analysis, biblioshiny, literature review, stock market volatility, VosViewer, volatility spillovers.

Abstract

This bibliometric review examines the evolution of stock market volatility (SMV) research by analyzing 1,949 publications indexed in Scopus between 1980 and 2025. The study provides valuable insights into major research trends, influential contributions, and emerging themes, while highlighting potential directions for future research in the field. The research aimed to identify influential elements within the literature and perform a comprehensive analysis. The study investigated two direct research streams through a systematic review approach and conducted a network analysis of keywords and documents supported by content analysis. The findings suggested several areas for future research, including Islamic stock markets, structural breaks, cryptocurrency, economic policy uncertainty, and futures. Notably, hybrid models like ANN-GARCH, Wavelet-GARCH, and Copula-GARCH were found to have received limited attention, limited work is available on emotional and behavioural dimensions in the context of stock market volatility, which needs to be addressed through sentiment-driven modelling using NLP and social media indicators. Moreover, few studies are available related to comparative analysis across market segments & require panel Data-based Studies. The study covered various aspects of stock market volatility, encompassing models, applications, and empirical properties. The study comprehensively covers models, applications, and empirical properties of stock market volatility. Additionally, the study offered practical implications and recommendations for regulators (to make informed decisions regarding policy development and implementation) and portfolio managers (understanding of influential elements in stock market volatility). Overall, this bibliometric review contributes valuable insights to the field, providing a comprehensive knowledge of stock market volatility and paving the way for further research.

References

Abbas, F., & Satti, A. U. (2019). Empirical Analysis of Effects of Expected Inflation on Stock Returns. Pakistan Journal of Economic Studies, 2(1), 71–98.

Aggarwal, R., Inclan, C., & Leal, R. (1999). Volatility in Emerging Stock Markets. Journal of Financial and Quantitative Analysis, 34(1), 33–55. http://dx.doi.org/10.2307/2676245

Ahmed, A. D., & Huo, R. (2021). Volatility Transmissions Across International Oil Market, Commodity Futures and Stock Markets: Empirical Evidence from China. Energy Economics, 93, 1–14. http://dx.doi.org/10.1016/j.eneco.2020.104741

Ahmed, H. J. A., Hassan, A., & Nasir, A. M. (2005). The Relationship Between Trading Volume, Volatility, and Stock Market Returns: A Test of Mixed Distribution Hypothesis for a Pre and Post-Crisis on Kuala Lumpur Stock Exchange. Investment Management and Financial Innovations, 3(3), 146–158.

Ahmed, W. M. (2021). Stock Market Reactions to Upside and Downside Volatility of Bitcoin: A Quantile Analysis. The North American Journal of Economics and Finance, 57, 101379. http://dx.doi.org/10.1016/j.najef.2021.101379

Alam, M. N., Alam, M. S., & Chavali, K. (2020). Stock Market Response During COVID-19 Lockdown Period in India: An Event Study. The Journal of Asian Finance, Economics and Business, 7(7), 131–137. http://dx.doi.org/10.13106/jafeb.2020.vol7.no7.131

Alikhanov, A. (2013). To What Extent Are Stock Returns Driven by Mean and Volatility Spillover Effects? –Evidence From Eight European Stock Markets. Review of Economic Perspectives, 13(1), 3–29. http://dx.doi.org/10.2478/v10135-012-0013-7

Andersen, T. G., & Bollerslev, T. (1998). Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts. International Economic Review, 39(4), 885–905. http://dx.doi.org/10.2307/2527343

Andersen, T. G., Bollerslev, T., Diebold, F. X., & Vega, C. (2007). Real-time Price Discovery in Global Stock, Bonds, and Foreign Exchange Markets. Journal of International Economics, 73(2), 251–277. http://dx.doi.org/10.1016/j.jinteco.2007.02.004

Anglada-Tort, M., & Sanfilippo, K. R. M. (2019). Visualizing Music Psychology: A Bibliometric Analysis of Psychology of Music, Music Perception, and Musicae Scientiae from 1973 to 2017. Music & Science, 2, 2059204318811786. http://dx.doi.org/10.1177/2059204318811786

Apostolakis, G. N., Floros, C., Gkillas, K., & Wohar, M. (2021). Political Uncertainty, COVID-19 Pandemic and Stock Market Volatility Transmission. Journal of International Financial Markets, Institutions and Money, 74, 101383. http://dx.doi.org/10.1016/j.intfin.2021.101383

Ashfaq, S., Tang, Y., & Maqbool, R. (2020). Dynamics of Spillover Network Among Oil and Leading Asian Oil Trading Countries’ Stock Markets. Energy, 207, 1–13. http://dx.doi.org/10.1016/j.energy.2020.118077

Ashwani, B., & Sheera, V. (2018). Indian Stock Market Volatility and Economic Fundamentals : MIDAS Approach. Indian Journal of Finance, 12(8), 7–21. http://dx.doi.org/10.17010/ijf/2018/v12i8/130741

Bagchi, B. (2017). Volatility Spillovers Between Crude Oil Price and Stock Markets: Evidence from BRIC Countries. International Journal of Emerging Markets, 12(2), 352–365. http://dx.doi.org/10.1108/IJoEM-04-2015-0077

Bahloul, S., & Abid, F. (2014). Regime-Switching Behaviour in the Conditional Volatility of MENA Stock Market Returns. Journal of Emerging Market Finance, 13(3), 253–278. http://dx.doi.org/10.1177/0972652714552042

Bahloul, S., & Khemakhem, I. (2021). Dynamic Return and Volatility Connectedness Between Commodities and Islamic Stock Market Indices. Resources Policy, 71, 101993. http://dx.doi.org/10.1016/j.resourpol.2021.101993

Bai, L., Wei, Y., Wei, G., Li, X., & Zhang, S. (2021). Infectious disease pandemic and permanent volatility of international stock markets: A long-term perspective. Finance Research Letters, 40, 101709. http://dx.doi.org/10.1016/j.frl.2020.101709

Bakry, W., Kavalmthara, P. J., Saverimuttu, V., Liu, Y., & Cyril, S. (2022). Response of stock market volatility to COVID-19 announcements and stringency measures: A comparison of developed and emerging markets. Finance Research Letters, 46, 102350. http://dx.doi.org/10.1016/j.frl.2021.102350

Bali, T. G., & Weinbaum, D. (2007). A conditional extreme value volatility estimator based on high-frequency returns. Journal of Economic Dynamics and Control, 31(2), 361–397. http://dx.doi.org/10.1016/j.jedc.2005.10.002

Basuony, M. A., Hassan, M. K., & Hippier, W. J. (2021). The Impact of Macroeconomic News Announcements on Emerging Market Exchange Rates: Evidence from EGARCH Model. Research in International Business and Finance, 56, 101376–101385.

Belhassine, O., & Karamti, C. (2021). Volatility Spillovers and Hedging Effectiveness Between Oil and Stock Markets: Evidence from a Wavelet-based and Structural Breaks Analysis. Energy Economics, 102, 1–18. http://dx.doi.org/10.1016/j.eneco.2021.105513

Bentes, I. (2014). Estéticas Insurgentes e Mídia-multidão. Liinc em Revista, 10(1), 330–343. http://dx.doi.org/10.18617/liinc.v10i1.704

Bhattacharjee, N., & De, A. (2022). Black Swan Event and the Stock Market Volatility Response to Shocks in Developed, Emerging, Frontier and the BRIC Markets: Lessons from the COVID-19 Pandemic. BBR. Brazilian Business Review, 19(5), 492–507. http://dx.doi.org/10.15728/bbr.2022.19.5.2.en

Bhowmik, R., & Wang, S. (2020). Stock Market Volatility and Return Analysis: A Systematic Literature Review. Entropy, 22(5), 522. http://dx.doi.org/10.3390/e22050522

Boldanov, R., Degiannakis, S., & Filis, G. (2016). Time-Varying Correlation Between Oil and Stock Market Volatilities: Evidence from Oil-importing and Oil-exporting Countries. International Review of Financial Analysis, 48, 209–220. http://dx.doi.org/10.1016/j.irfa.2016.10.002

Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. http://dx.doi.org/10.1016/0304-4076(86)90063-1

Bollerslev, T., Engle, R. F., & Wooldridge, J. M. (1988). A Capital Asset Pricing Model with Time-Varying Covariances. Journal of Political Economy, 96(1), 116–131. http://dx.doi.org/10.1086/261527

Bollerslev, T., & Ole Mikkelsen, H. (1996). Modeling and pricing long memory in stock market volatility. Journal of Econometrics, 73(1), 151–184. http://dx.doi.org/10.1016/0304-4076(95)01736-4

Bouri, E. (2015). Return and Volatility Linkages Between Oil Prices and the Lebanese Stock Market in Crisis Periods. Energy, 89, 365–371. http://dx.doi.org/10.1016/j.energy.2015.05.121

Brancaccio, E., Bernardina, A., & Damiano, B. (2020). Stock Market Volatility, Speculation and Unemployment: A Granger-causality Analysis. PSL Quarterly Review, 73(293), 137–160.

Buldyrev, S. V., Flori, A., & Pammolli, F. (2021). Market instability and the size-variance relationship. Scientific Reports, 11(1), 5737. http://dx.doi.org/10.1038/s41598-021-84680-1

Campbell, J. Y., & Shiller, R. J. (1988). The Dividend-price Ratio and Expectations of Future Dividends and Discount Factors. Review of Financial Studies, 1(3), 195–228. http://dx.doi.org/10.1093/rfs/1.3.195

Cevik, N. K., Cevik, E. I., & Dibooglu, S. (2020). Oil Prices, Stock Market Returns and Volatility Spillovers: Evidence from Turkey. Journal of Policy Modeling, 42(3), 597–614. http://dx.doi.org/10.1016/j.jpolmod.2020.01.006

Chancharoenchai, K., & Dibooglu, S. (2006). Volatility Spillovers and Contagion During the Asian Crisis: Evidence from Six Southeast Asian Stock Markets. Emerging Markets Finance & Trade, 42(2), 4–17. http://dx.doi.org/10.2753/REE1540-496X420201

Charfeddine, L., & Al Refai, H. (2019). Political Tensions, Stock Market Dependence and Volatility Spillover: Evidence from the Recent Intra-GCC Crises. The North American Journal of Economics and Finance, 50, 101032. http://dx.doi.org/10.1016/j.najef.2019.101032

Chatziantoniou, I., Gabauer, D., & Stenfors, A. (2025). US Sectoral Stock Market Volatility and Geopolitical Risk Categories. Finance Research Letters, 76(February), 106916. http://dx.doi.org/10.1016/j.frl.2025.106916

Chen, H., Li, F., & Wang, Y. (2015). Component GARCH-M type models for wind power forecasting. IEEE Power & Energy Society General Meeting: IEEE. http://dx.doi.org/10.1109/PESGM.2015.7285800

Chen, X., Zhu, H., Zhang, X., & Zhao, L. (2022). A Novel Time-varying FIGARCH Model for Improving Volatility Predictions. Physica A: Statistical Mechanics and its Applications, 589, 1–14. http://dx.doi.org/10.1016/j.physa.2021.126635

Chen, Y., Zhao, H., Li, Z., & Lu, J. (2020). A dynamic analysis of the relationship between investor sentiment and stock market realized volatility: Evidence from China. PLoS One, 15(12), e0243080. http://dx.doi.org/10.1371/journal.pone.0243080

Cheng, T., Liu, J., Yao, W., & Zhao, A. B. (2022). The Impact of COVID-19 Pandemic on the Volatility Connectedness Network of Global Stock Market. Pacific-Basin Finance Journal, 71, 1–22. http://dx.doi.org/10.1016/j.pacfin.2021.101678

Chiang, T. C., & Doong, S. C. (2001). Empirical Analysis of Stock Returns and Volatility: Evidence from Seven Asian Stock Markets based on TAR-GARCH Model. Review of Quantitative Finance and Accounting, 17(3), 301–318.

Chkili, W., & Hamdi, M. (2021). An artificial neural network augmented GARCH model for Islamic stock market volatility: Do asymmetry and long memory matter? International Journal of Islamic and Middle Eastern Finance and Management, 14(5), 853–873. http://dx.doi.org/10.1108/IMEFM-05-2019-0204

Coffie, W. (2015). Modelling and Forecasting the Conditional Heteroscedasticity of Stock Returns Using Asymmetric Models: Empirical Evidence from Ghana and Nigeria. Journal of Accounting and Finance, 15(5), 109–123.

Coffie, W. (2018). Modelling and Forecasting Volatility of the Botswana and Namibia Stock Market Returns: Evidence Using GARCH Models With Different Distribution Densities. Global Business and Economics Review, 20(1), 18–35. http://dx.doi.org/10.1504/GBER.2018.088469

Conrad, C., & Loch, K. (2015). Anticipating Long-Term Stock Market Volatility. Journal of Applied Econometrics, 30(7), 1090–1114. http://dx.doi.org/10.1002/jae.2404

Corsi, F. (2009). A Simple Approximate Long-Memory Model of Realised Volatility. Journal of Financial Econometrics, 7(2), 174–196. http://dx.doi.org/10.1093/jjfinec/nbp001

Dabwor, D. T., Iorember, P. T., & Yusuf Danjuma, S. (2022). Stock Market Returns, Globalization and Economic Growth in Nigeria: Evidence from Volatility and Cointegrating Analyses. Journal of Public Affairs, 22(2), e2393.

Dash, S. R., & Mahakud, J. (2013). Investor sentiment and stock return: Do industries matter? Margin: The Journal of Applied Economic Research, 7(3), 315–349. http://dx.doi.org/10.1177/0973801013491530

Degiannakis, S., Filis, G., & Arora, V. (2018). Oil Prices and Stock Markets: A Review of the Theory and Empirical Evidence. The Energy Journal, 39(5), 85–130. http://dx.doi.org/10.5547/01956574.39.5.sdeg

Diebold, F. X., & Yilmaz, K. (2009). Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets. The Economic Journal, 119(534), 158–171. http://dx.doi.org/10.1111/j.1468-0297.2008.02208.x

Diebold, F. X., & Yilmaz, K. (2012). Better to Give than to Receive: Predictive Directional Measurement of Volatility Spillovers. International Journal of Forecasting, 28(1), 57–66. http://dx.doi.org/10.1016/j.ijforecast.2011.02.006

Engle, R. F. (1982). Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation. Econometrica, 50(4), 987–1007. http://dx.doi.org/10.2307/1912773

Engle, R. F. (1990). Discussion. The Review of Financial Studies, 3(1), 103–106. http://dx.doi.org/10.1093/rfs/3.1.103

Engle, R. F., Ghysels, E., & Sohn, B. (2013). Stock Market Volatility and Macroeconomic Fundamentals. The Review of Economics and Statistics, 95(3), 776–797. http://dx.doi.org/10.1162/REST_a_00300

Ewing, B. T., & Malik, F. (2016). Volatility Spillovers Between Oil Prices and the Stock Market Under Structural Breaks. Global Finance Journal, 29, 12–23. http://dx.doi.org/10.1016/j.gfj.2015.04.008

Ferreira, T. S., Machado, M. A., & Silva, P. Z. (2021). Asymmetric Impact of Investor Sentiment on Brazilian Stock Market Volatility. RAM. Revista de Administração Mackenzie, 22(4), 1–28. http://dx.doi.org/10.1590/1678-6971/eramf210208

Finta, M. A., Frijns, B., & Tourani-Rad, A. (2019). Volatility Spillovers Among Oil and Stock Markets in the US and Saudi Arabia. Applied Economics, 51(4), 329–345. http://dx.doi.org/10.1080/00036846.2018.1494811

Gamba-Santamaria, S., Gomez-Gonzalez, J. E., Hurtado-Guarin, J. L., & Melo-Velandia, L. F. (2019). Volatility Spillovers Among Global Stock Markets: Measuring Total and Directional Effects. Empirical Economics, 56(5), 1581–1599. http://dx.doi.org/10.1007/s00181-017-1406-3

Glänzel, W., Schlemmer, B., Schubert, A., & Thijs, B. (2006). Proceedings literature as additional data source for bibliometric analysis. Scientometrics, 68(3), 457–473. http://dx.doi.org/10.1007/s11192-006-0124-y

Glosten, L. R., Jagannathan, R., & Runkle, D. E. (1993). On the Relation Between the Expected Value and the Volatility of the Nominal Excess Return on Stocks. The Journal of Finance, 48(5), 1779–1801. http://dx.doi.org/10.1111/j.1540-6261.1993.tb05128.x

Guo, H., & Savickas, R. (2006). Idiosyncratic Volatility, Stock Market Volatility, and Expected Stock Returns. Journal of Business & Economic Statistics, 24(1), 43–56. http://dx.doi.org/10.1198/073500105000000180

Gupta, H., Chaudhary, R., & Gupta, S. (2022). COVID-19 Impact on Major Stock Markets. FIIB Business Review, 11, 336–346. http://dx.doi.org/10.1177/2319714521994514

Hamao, Y., Masulis, R. W., & Ng, V. (1990). Correlations in Price Changes and Volatility Across International Stock Markets. The Review of Financial Studies, 3(2), 281–307. http://dx.doi.org/10.1093/rfs/3.2.281

Hamilton, J. D. (1996). This is What Happened to the Oil Price-Macroeconomy Relationship. Journal of Monetary Economics, 38(2), 215–220. http://dx.doi.org/10.1016/S0304-3932(96)01282-2

Hammoudeh, S., & Li, H. (2008). Sudden Changes in Volatility in Emerging Markets: The Case of Gulf Arab Stock Markets. International Review of Financial Analysis, 17(1), 47–63. http://dx.doi.org/10.1016/j.irfa.2005.01.002

Haritha, P., & Rishad, A. (2020). An Empirical Examination of Investor Sentiment and Stock Market Volatility: Evidence from India. Financial Innovation, 6(1), 1–15. http://dx.doi.org/10.1186/s40854-020-00198-x

Harrison, B., & Moore, W. (2012). Forecasting Stock Market Volatility in Central and Eastern European Countries. Journal of Forecasting, 31(6), 490–503. http://dx.doi.org/10.1002/for.1214

Hernandez, J. A., Shahzad, S. J., Sadorsky, P., Uddin, G. S., Bouri, E., & Kang, S. H. (2022). Regime Specific Spillovers Across US Sectors and the Role of Oil Price Volatility. Energy Economics, 107, 1–13. http://dx.doi.org/10.1016/j.eneco.2022.105834

Hoang Van, H., Tuan, P. K., & Le, T. P. (2020). Firm-specific News and Anomalies. In R. Gharoie Ahangar & A. Salman (Eds.), Investment Strategies in Emerging New Trends in Finance. London: IntechOpen. http://dx.doi.org/10.5772/intechopen.94286

Horng, W. J., Hu, T. C., & Huang, M. C. (2012). DCC Analysis of the Two Stock Market Returns by a Threshold Model: Empirical Study of the Stock Markets in Japan and Canada. Advanced Materials Research, 468-471, 181–185. http://dx.doi.org/10.4028/www.scientific.net/AMR.468-471.181

Horváth, R., Lyócsa, Š., & Baumöhl, E. (2018). Stock Market Contagion in Central and Eastern Europe: Unexpected Volatility and Extreme Co-exceedance. European Journal of Finance, 24(5), 391–412. http://dx.doi.org/10.1080/1351847X.2017.1307773

Hou, W., Cui, B., Song, Y., & Chen, Y. (2024). Volatilities and Return Co-movements Among Stock Markets in Mainland China, Hong Kong, and the United States. The Singapore Economic Review, 69(07), 2097–2118. http://dx.doi.org/10.1142/S0217590821500090

Hussain, S., Bhanu Murthy, K. V., & Singh, A. (2019). Stock Market Volatility: A Review of Empirical Literature. IUJ Journal of Management, 7(01), 96–105.

Ineichen, A. M. (2000). Twentieth Century Volatility. The Journal of Portfolio Management, 27(1), 93–101. http://dx.doi.org/10.3905/jpm.2000.319787

Insaidoo, M., Brafu-Insaidoo, W. G., Peprah, J. A., & Cantah, W. G. (2024). The Role of Financial Globalization in the Long-run Volatility Between Forex and Stock Markets During COVID-19: Evidence from Africa. Research in Globalization, 9(January), 100242. http://dx.doi.org/10.1016/j.resglo.2024.100242

Jebabli, I., Kouaissah, N., & Arouri, M. (2022). Volatility spillovers between stock and energy markets during crises: A comparative assessment between the 2008 global financial crisis and the COVID-19 pandemic crisis. Finance Research Letters, 46(Part A), 102363. http://dx.doi.org/10.1016/j.frl.2021.102363

Jeris, S. S., Ur Rahman Chowdhury, A. S. M. N., Akter, M. T., Frances, S., & Roy, M. H. (2022). Cryptocurrency and stock market: Bibliometric and content analysis. Heliyon, 8, e10514. http://dx.doi.org/10.1016/j.heliyon.2022.e10514

Ji, Q., Zhang, D., & Zhao, Y. (2022). Intra-day co-movements of crude oil futures: China and the international benchmarks. Annals of Operations Research, 313(1), 77–103. http://dx.doi.org/10.1007/s10479-021-04097-x

Jindal, N., & Kumar Gupta, R. (2022). The Impact of COVID-19 on Stock Market Returns & Volatility: A Study of Thailand and Indian Bourses. Thailand and The World Economy, 40(2), 145–167.

Jones, C. P., Walker, M. D., & Wilson, J. W. (2004). Analyzing Stock Market Volatility Using Extreme‐Day Measures. Journal of Financial Research, 27(4), 585–601. http://dx.doi.org/10.1111/j.1475-6803.2004.00109.x

José de Oliveira, O., Francisco da Silva, F., Juliani, F., Barbosa, L. C., & Nunhes, T. V. (2019). Bibliometric Method for Mapping the State-of-the-Art and Identifying Research Gaps and Trends in Literature: An Essential Instrument to Support the Development of Scientific Projects. http://dx.doi.org/10.5772/intechopen.85856

Kambouroudis, D. S. (2016). Chapter 3 - Modeling and Forecasting Stock Market Volatility in Frontier Markets: Evidence From Four European and Four African Frontier Markets. In P. Andrikopoulos, G. N. Gregoriou, & V. Kallinterakis (Eds.), Handbook of Frontier Markets (pp. 39–54): Academic Press. http://dx.doi.org/10.1016/B978-0-12-803776-8.00003-3

Kamstra, M. J., Kramer, L. A., & Levi, M. D. (2010). Effects of daylight-saving time changes on stock market volatility: A comment. Psychological Reports, 107(3), 877–887. http://dx.doi.org/10.2466/03.07.PR0.107.6.877-887

Karim, M. M., & Masih, M. (2021). Do the Islamic Stock Market Returns Respond Differently to the Realised and Implied Volatility of Oil Prices? Evidence from the Time–Frequency Analysis. Emerging Markets Finance and Trade, 57(9), 2616–2631. http://dx.doi.org/10.1080/1540496X.2019.1663409

Kartsonakis‐Mademlis, D., & Dritsakis, N. (2020). Asymmetric Volatility Spillovers Between World Oil Prices and Stock Markets of the G7 Countries in the Presence of Structural Breaks. International Journal of Finance & Economics, 26(3), 3930–3944. http://dx.doi.org/10.1002/ijfe.1997

Kartsonakis, I. A., & Charitidis, C. A. (2020). Corrosion Protection Evaluation of Mild Steel: The Role of Hybrid Materials Loaded with Inhibitors. Applied Sciences, 10(18), 6594. http://dx.doi.org/10.3390/app10186594

Kashyap, S. (2023). Review on Volatility and Return Analysis Including Emerging Developments: Evidence from Stock Market Empirics. Journal of Modelling in Management, 18(3), 756–816. http://dx.doi.org/10.1108/JM2-10-2021-0249

Katoch, R., & Peer, U. A. (2026). Navigating Market Risks in Green Investments in India: An Evaluation of Interest Rate, Equity, Commodity, and Forex Market Influences. Computational Economics, 67, 4639–4671. http://dx.doi.org/10.1007/s10614-025-11009-9

Khalfaoui, R., Sarwar, S., & Tiwari, A. K. (2019). Analysing Volatility Spillover Between the Oil Market and the Stock Market in Oil-importing and Oil-exporting Countries: Implications on Portfolio Management. Resources Policy, 62, 22–32. http://dx.doi.org/10.1016/j.resourpol.2019.03.004

Khan, K., Nasir, M. A., & Rossi, M. (2017). The Calendar Anomalies on Performance and Volatility of Stock Market: The effects of Ramadan on Karachi Stock Exchange. Global Business and Economics Review, 19(1), 54–69. http://dx.doi.org/10.1504/GBER.2017.080775

Khiste, G. P., & Paithankar, R. R. (2017). Analysis of Bibliometric term in Scopus. International Journal of Library Science and Information Management, 3(3), 81–88.

Kim, H., & So, K. K. F. (2022). Two Decades of Customer Experience Research in Hospitality and Tourism: A Bibliometric Analysis and Thematic Content Analysis. International Journal of Hospitality Management, 100, 103082. http://dx.doi.org/10.1016/j.ijhm.2021.103082

Kiymaz, H., & Berument, H. (2003). The Day of the Week Effect on Stock Market Volatility and Volume: International Evidence. Review of Financial Economics, 12(4), 363–380. http://dx.doi.org/10.1016/S1058-3300(03)00038-7

Koutmos, G., & Booth, G. G. (1995). Asymmetric Volatility Transmission in International Stock Markets. Journal of International Money and Finance, 14(6), 747–762. http://dx.doi.org/10.1016/0261-5606(95)00031-3

Kyriakou, I., Mousavi, P., Nielsen, J. P., & Scholz, M. (2021). Forecasting Benchmarks of Long-term Stock Returns Via Machine Learning. Annals of Operations Research, 297, 221–240. http://dx.doi.org/10.1007/s10479-019-03338-4

Lahmiri, S., & Bekiros, S. (2021). The effect of COVID-19 on long memory in returns and volatility of cryptocurrency and stock markets. Chaos, Solitons, and Fractals, 151, 111221. http://dx.doi.org/10.1016/j.chaos.2021.111221

Lamoureux, C. G., & Lastrapes, W. D. (1990). Heteroskedasticity in Stock Return Data: Volume Versus GARCH Effects. The Journal of Finance, 45(1), 221–229. http://dx.doi.org/10.1111/j.1540-6261.1990.tb05088.x

Lee, W. Y., Jiang, C. X., & Indro, D. C. (2002). Stock Market Volatility, Excess Returns, and the Role of Investor Sentiment. Journal of Banking & Finance, 26(12), 2277–2299. http://dx.doi.org/10.1016/S0378-4266(01)00202-3

Li, H. (2020). Volatility Spillovers Across European Stock Markets Under the Uncertainty of Brexit. Economic Modelling, 84, 1–12. http://dx.doi.org/10.1016/j.econmod.2019.03.001

Li, R., Li, S., Yuan, D., Chen, H., & Xiang, S. (2023). Spillover Effect of Economic Policy Uncertainty on the Stock Market in the Post-epidemic Era. The North American Journal of Economics and Finance, 64, 101846. http://dx.doi.org/10.1016/j.najef.2022.101846

Li, W. (2021). COVID-19 and Asymmetric Volatility Spillovers Across Global Stock Markets. The North American Journal of Economics and Finance, 58, 101474. http://dx.doi.org/10.1016/j.najef.2021.101474

Li, Y., Zhuang, X., & Wang, J. (2021). Analysis of the Cross-Region Risk Contagion Effect in Stock Market Based on Volatility Spillover Networks: Evidence from China. The North American Journal of Economics and Finance, 56, 101359. http://dx.doi.org/10.1016/j.najef.2020.101359

Lien, D., Lee, G., Yang, L., & Zhang, Y. (2018). Volatility Spillovers Among the US and Asian Stock Markets: A Comparison Between the Periods of Asian Currency Crisis and Subprime Credit Crisis. The North American Journal of Economics and Finance, 46, 187–201. http://dx.doi.org/10.1016/j.najef.2018.04.006

Lin, Y., Zheng, L., Zheng, Z., Wu, Y., Hu, Z., Yan, C., & Yang, Y. (2019). Improving Person Re-identification by Attribute and Identity Learning. Pattern Recognition, 95, 151–161. http://dx.doi.org/10.1016/j.patcog.2019.06.006

Lisée, C., Larivière, V., & Archambault, É. (2008). Conference Proceedings as a Source of Scientific Information: A Bibliometric Analysis. Journal of the American Society for Information Science and Technology, 59(11), 1776–1784. http://dx.doi.org/10.1002/asi.20888

Liu, L., & Zhang, T. (2015). Economic Policy Uncertainty and Stock Market Volatility. Finance Research Letters, 15, 99–105. http://dx.doi.org/10.1016/j.frl.2015.08.009

Luo, J., & Wang, S. (2019). The Asymmetric High-frequency Volatility Transmission Across International Stock Markets. Finance Research Letters, 31, 104–109. http://dx.doi.org/10.1016/j.frl.2019.04.025

Ma, C., Wu, J., Hu, H., Chen, Y. N., & Li, J. Y. (2024). Predicting Stock Prices Using Hybrid LSTM and ARIMA Model. International Journal of Applied Mathematics, 54(3), 424.

Madaleno, M., & Pinho, C. (2014). Wavelet Dynamics for Oil-stock World Interactions. Energy Economics, 45, 120–133. http://dx.doi.org/10.1016/j.eneco.2014.06.024

Mamtha, D., & Srinivasan, K. S. (2016). Stock Market Volatility–Conceptual Perspective through Literature Survey. Mediterranean Journal of Social Sciences, 7(1), 208–212.

Mankiw, N. G., Romer, D., & Shapiro, M. D. (1985). An Unbiased Reexamination of Stock Market Volatility. The Journal of Finance, 40(3), 677–687. http://dx.doi.org/10.1111/j.1540-6261.1985.tb04990.x

Matar, W., Al‐Fattah, S. M., Atallah, T., & Pierru, A. (2013). An Introduction to Oil Market Volatility Analysis. OPEC Energy Review, 37(3), 247–269. http://dx.doi.org/10.1111/opec.12007

Mechri, N., de Peretti, C., & Ben Hamad, S. B. (2021). The Impact of the Exchange Rate Volatility on Stock Markets Dynamics in Tunisia and Turkey: An Artificial Neural Network Analysis. Global Economics Science, 3(1), 1–21. http://dx.doi.org/10.37256/ges.312022798

Mensi, W., Al Rababa’a, A. R., Vo, X. V., & Kang, S. H. (2021). Asymmetric spillover and network connectedness between crude oil, gold, and Chinese sector stock markets. Energy Economics, 98, 105262. http://dx.doi.org/10.1016/j.eneco.2021.105262

Mukhodobwane, R. M., Sigauke, C., Chagwiza, W., & Garira, W. (2020). Volatility modelling of the BRICS stock markets. Statistics, Optimization & Information Computing, 8(3), 749–772. http://dx.doi.org/10.19139/soic-2310-5070-977

Naeem, M. A. (2024). Navigating Median and Extreme Volatility in Stock Markets: Implications for Portfolio Strategies. International Review of Economics & Finance, 95(April), 103507. http://dx.doi.org/10.1016/j.iref.2024.103507

Naifar, N. (2016). Do Global Risk Factors and Macroeconomic Conditions Affect Global Islamic Index Dynamics? A Quantile Regression Approach. The Quarterly Review of Economics and Finance, 61, 29–39. http://dx.doi.org/10.1016/j.qref.2015.10.004

Natarajan, V. K., Robert Raja Singh, A., & Chidham Priya, N. (2014). Examining mean-volatility spillovers across national stock markets. Journal of Economics Finance and Administrative Science, 19(36), 55–62. http://dx.doi.org/10.1016/j.jefas.2014.01.001

Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347–370. http://dx.doi.org/10.2307/2938260

Pagan, A. R., & Schwert, G. W. (1990). Alternative Models for Conditional Stock Volatility. Journal of Econometrics, 45(1-2), 267–290. http://dx.doi.org/10.1016/0304-4076(90)90101-X

Pan, L., & Mishra, V. (2022). International portfolio diversification possibilities: Can BRICS become a destination for US investors? Applied Economics, 54(20), 2302–2319. http://dx.doi.org/10.1080/00036846.2021.1988045

Papadamou, S., Fassas, A. P., Kenourgios, D., & Dimitriou, D. (2023). Effects of the first wave of COVID-19 pandemic on implied stock market volatility: International evidence using a google trend measure. The Journal of Economic Asymmetries, 28, e00317. http://dx.doi.org/https://doi.org/10.1016/j.jeca.2023.e00317

Patton, A. J., & Sheppard, K. (2015). Good Volatility, Bad Volatility: Signed Jumps and the Persistence of Volatility. The Review of Economics and Statistics, 97(3), 683–697. http://dx.doi.org/10.1162/REST_a_00503

Paye, B. S. (2012). ‘Déjà vol’: Predictive Regressions for Aggregate Stock Market Volatility Using Macroeconomic Variables. Journal of Financial Economics, 106(3), 527–546. http://dx.doi.org/10.1016/j.jfineco.2012.06.005

Raghuram, S., Tuertscher, P., & Garud, R. (2010). Research Note-Mapping the Field of Virtual Work: A Co-Citation Analysis. Information Systems Research, 21(4), 983–999. http://dx.doi.org/10.1287/isre.1080.0227

Sadorsky, P. (2009). Renewable Energy Consumption, CO2 Emissions and Oil Prices in the G7 Countries. Energy Economics, 31(3), 456–462. http://dx.doi.org/10.1016/j.eneco.2008.12.010

Salisu, A. A., Demirer, R., & Gupta, R. (2023). Technological Shocks and Stock Market Volatility Over A Century: A GARCH- MIDAS Approach. (202308).

Salisu, A. A., & Gupta, R. (2021). Oil Shocks and Stock Market Volatility of the BRICS: A GARCH-MIDAS Approach. Global Finance Journal, 48, 100546. http://dx.doi.org/10.1016/j.gfj.2020.100546

Saraf, M., & Kayal, P. (2023). How Much Does Volatility Influence Stock Market Returns? Empirical Evidence from India. IIMB Management Review, 35(2), 108–123. http://dx.doi.org/10.1016/j.iimb.2023.05.004

Sarwar, S., Khalfaoui, R., Waheed, R., & Dastgerdi, H. G. (2019). Volatility Spillovers and Hedging: Evidence from Asian Oil-importing Countries. Resources Policy, 61, 479–488. http://dx.doi.org/10.1016/j.resourpol.2018.04.010

Schneider, J. (2021). Continued citation of bad science and what we can do about it. Invited talk, Center for Computational & Data Science, Syracuse University School of Information Studies. Retrieved from https://www.slideshare.net/jodischneider/continued-citation-of-bad-science-and-what-we-can-do-about-it20210219-243064376

Schwert, G. W. (1989). Why Does Stock Market Volatility Change Over Time? The Journal of Finance, 44(5), 1115–1153. http://dx.doi.org/10.1111/j.1540-6261.1989.tb02647.x

Seth, N., & Sidhu, A. (2020). Price Discovery and Volatility Spillovers in Commodity Market: A Review of Empirical Literature. International Journal of Financial Markets and Derivatives, 7(3), 291–314. http://dx.doi.org/10.1504/IJFMD.2020.109197

Shahzad, S. J., Ferrer, R., Ballester, L., & Umar, Z. (2017). Risk Transmission Between Islamic and Conventional Stock Markets: A Return and Volatility Spillover Analysis. International Review of Financial Analysis, 52, 9–26. http://dx.doi.org/10.1016/j.irfa.2017.04.005

Simitis, C. (2016). The European Debt Crisis- The Greek Case. Manchester: University Press. http://dx.doi.org/10.7765/9781526112019

Singh, D. (2018). Stock Price Determinants: Empirical Evidence from Muscat Securities Market, Oman. In P. Saona (Ed.), Firm Value - Theory and Empirical Evidence. London: IntechOpen. http://dx.doi.org/10.5772/intechopen.77343

Small, H. (1973). Co‐citation in the Scientific Literature: A New Measure of the Relationship Between Two Documents. Journal of the American Society for Information Science, 24(4), 265–269. http://dx.doi.org/10.1002/asi.4630240406

Song, Y., Tang, X., Wang, H., & Ma, Z. (2023). Volatility Forecasting for Stock Market Incorporating Macroeconomic Variables Based on GARCH‐MIDAS and Deep Learning Models. Journal of Forecasting, 42(1), 51–59. http://dx.doi.org/10.1002/for.2899

Spulbar, C., Trivedi, J., & Birau, R. (2020). Investigating Abnormal Volatility Transmission Patterns Between Emerging and Developed Stock Markets: A Case Study. Journal of Business Economics and Management, 21(6), 1561–1592. http://dx.doi.org/10.3846/jbem.2020.13507

Sreenu, N. (2022). Impact of Crude Oil Price Uncertainty on Indian Stock Market Returns: Evidence from Oil Price Volatility Index. 44, 101002. http://dx.doi.org/10.1016/j.esr.2022.101002

Sreenu, N. (2023). Effect of Exchange Rate Volatility and Inflation on Stock Market Returns Dynamics: Evidence from India. International Journal of System Assurance Engineering and Management, 14, 836–843. http://dx.doi.org/DOI:10.1007/s13198-023-01914-3

Su, X., & Liu, Z. (2021). Sector Volatility Spillover and Economic Policy Uncertainty: Evidence from China’s Stock Market. Mathematics, 9(12), 1–22. http://dx.doi.org/10.3390/math9121411

Talbi, D., Chaibi, H., & Maoueti, A. (2022). Political Uncertainty, Financial Crises, and Stock Market Volatility: Evidence from MENA Region. Journal of Public Affairs, 22(S1), e2783. http://dx.doi.org/10.1002/pa.2783

Tang, C., & Aruga, K. (2021). Relationships among the Fossil Fuel and Financial Markets during the COVID-19 Pandemic: Evidence from Bayesian DCC-MGARCH Models. Sustainability, 14(1), 51. http://dx.doi.org/10.3390/su14010051

Taylor, S. J. (2008). Modelling Financial Time Series: World Scientific.

Toe, D. L., & Ouedraogo, S. (2022). Dynamic Relationship Between Trading Volume, Returns and Returns Volatility: An Empirical Investigation on the Main African’s Stock Markets. Journal of Asset Management, 23, 429–444. http://dx.doi.org/10.1057/s41260-022-00274-0

Touny, M. A., Radwan, M. A., & Alayis, M. M. (2021). Macro Determinants of Stock Market Volatility: Evidence from Middle East Region. Afro-Asian Journal of Finance and Accounting, 11(3), 376–391. http://dx.doi.org/10.1504/AAJFA.2021.115672

Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a Methodology for Developing Evidence‐informed Management Knowledge By Means of Systematic Review. British Journal of Management, 14(3), 207–222. http://dx.doi.org/10.1111/1467-8551.00375

Tripathy, N. (2022). Long Memory and Volatility Persistence Across BRICS Stock Markets. Research in International Business and Finance, 63, 1–13. http://dx.doi.org/10.1016/j.ribaf.2022.101782

van Dieijen, M., Borah, A., Tellis, G. J., & Franses, P. H. (2020). Big Data Analysis of Volatility Spillovers of Brands Across Social Media and Stock Markets. Industrial Marketing Management, 88, 465–484. http://dx.doi.org/10.1016/j.indmarman.2018.12.006

Walid, C., Chaker, A., Masood, O., & Fry, J. (2011). Stock market volatility and exchange rates in emerging countries: A Markov-state switching approach. Emerging Markets Review, 12(3), 272–292. http://dx.doi.org/10.1016/j.ememar.2011.04.003

Wang, P., & Moore, T. (2009). Sudden Changes in Volatility: The Case of Five Central European Stock Markets. Journal of International Financial Markets, Institutions and Money, 19(1), 33–46. http://dx.doi.org/10.1016/j.intfin.2007.08.006

Wen, D., Wang, G. J., Ma, C., & Wang, Y. (2019). Risk Spillovers Between Oil and Stock Markets: A VAR for VaR Analysis. Energy Economics, 80, 524–535. http://dx.doi.org/10.1016/j.eneco.2019.02.005

Wen, F., Weng, K., & Zhou, W. X. (2020). Measuring the contribution of Chinese financial institutions to systemic risk: an extended asymmetric CoVaR approach. Risk Management, 22(4), 310–337. http://dx.doi.org/10.1057/s41283-020-00064-1

Xu, Y., Guan, B., Lu, W., & Heravi, S. (2024). Macroeconomic Shocks and Volatility Spillovers Between Stock, Bond, Gold and Crude Oil Markets. Energy Economics, 136(June), 107750. http://dx.doi.org/10.1016/j.eneco.2024.107750

Yang, T. (2025). Volatility Characteristics of Stock Markets During the US-China Trade War. International Review of Economics & Finance, 102(April), 104335. http://dx.doi.org/10.1016/j.iref.2025.104335

Yu, P. L., Ng, F. C., & Ting, J. K. (2020). Adjusting Covariance Matrix for Risk Management. Quantitative Finance, 20(10), 1681–1699. http://dx.doi.org/10.1080/14697688.2020.1739737

Zhang, L. (2014, 17–19 Aug. 2014). Testing for long memory volatility of Chinese stock markets with FIGARCH model. Paper presented at the 2014 International Conference on Management Science & Engineering 21th Annual Conference Proceedings.

Zhang, Q., & Jaffry, S. A. (2015). Global Financial Crisis Effects on Volatility Spillover Between Mainland China and Hong Kong Stock Markets. Investment Management and Financial Innovations, 12(1), 26–34.

Zhang, W., Yan, K., & Shen, D. (2021). Can the Baidu Index Predict Realized Volatility in the Chinese Stock Market? Financial Innovation, 7(1), 1–31. http://dx.doi.org/10.1186/s40854-020-00216-y

Zhang, Y., Lei, L., & Wei, Y. (2020). Forecasting the Chinese Stock Market Volatility with International Market Volatilities: The Role of Regime Switching. The North American Journal of Economics and Finance, 52, 101145. http://dx.doi.org/10.1016/j.najef.2020.101145

Zhang, Y. Y., & Zhang, Y. J. (2022). The Impact of Institutional Analyst Forecast Divergence on Crude Oil Market: Evidence From the Mixed Frequency Models. International Review of Financial Analysis, 84, 1–11. http://dx.doi.org/10.1016/j.irfa.2022.102418

Zhang, Z., Xu, Y., & Su, F. (2025). Climate Policy Uncertainty and Dynamic Volatility Spillovers in Chinese Stock Market: Based on Sectoral Evaluation. Journal of Management Science and Engineering, 10(3), 332–347. http://dx.doi.org/10.1016/j.jmse.2025.05.001

Zhong, Y., & Liu, J. (2021). Correlations and Volatility Spillovers Between China and Southeast Asian Stock Markets. The Quarterly Review of Economics and Finance, 81, 57–69. http://dx.doi.org/10.1016/j.qref.2021.04.001

Zhou, X., Zhang, W., & Zhang, J. (2012). Volatility Spillovers Between the Chinese and World Equity Markets. Pacific-Basin Finance Journal, 20(2), 247–270. http://dx.doi.org/10.1016/j.pacfin.2011.08.002

Zhu, K., & Ling, S. (2015). Model-based Pricing for Financial Derivatives. Journal of Econometrics, 187(2), 447–457. http://dx.doi.org/10.1016/j.jeconom.2015.02.030