References
Aastveit, K. A., Furlanetto, F., & Loria, F. (2023). Has the Fed responded to house and stock prices? A time-varying analysis. Review of Economics and Statistics, 105(5), 1314-1324. doi.org/10.1162/rest_a_01120.
Akay, E., & Hirshleifer, D. (2021). Social finance as cultural evolution, transmission bias, and market dynamics. Proceedings of the National Academy of Sciences, 118. doi.org/10.1073/pnas.2015568118
Albulescu, C. T. (2021). COVID-19 and the United States financial markets’ volatility. Finance research letters, 38, 101699. doi.org/10.1016/j.frl.2020.101699.
Baker, M., & Wurgler, J. (2006). Investor sentiment and the cross-section of stock returns. Journal of Finance, 61(4), 1645-1680. doi.org/10.1111/j.1540-6261.2006.00885.x
Barry, P. J., & Lee, W. F. (1983). Financial stress in agriculture: Implications for agricultural lenders. American Journal of Agricultural Economics, 65(5), 945-952. doi.org/10.2307/1240396.
Barry, P. J., Baker, C. B., & Sanint, L. R. (1981). Farmers' credit risks and liquidity management. American Journal of Agricultural Economics, 63(2), 216-227. doi.org/10.2307/1239557.
Bennani, H. (2019). Does People's Bank of China communication matter? Evidence from stock market reaction. Emerging Markets Review, 40, 100617. doi.org/10.1016/j.ememar.2019.05.002.
Bernanke, B. & Blinder, A. (1988). Credit, Money, and Aggregate Demand. American Economic Review, 78, 435-439. DOI 10.3386/w2534.
Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Eeri Research Paper, 31(3), 307-327. doi.org/10.1016/0304-4076(86)90063-1
Bourveau, T., & Schoenfeld, J. (2017). Shareholder activism and voluntary disclosure. Review of Accounting Studies, 22, 1307-1339. doi.org/10.1007/s11142-017-9408-0.
Breitenlechner, M., & Nuutilainen, R. (2023). China’s Monetary Policy and the Loan Market: How Strong is the Credit Channel in China?. Open Economies Review, 34(3), 555-577. doi.org/10.1007/s11079-022-09705-2.Clapp, J., Isakson, S. R., & Visser, O. (2017). The complex dynamics of agriculture as a financial asset: Introduction to symposium. Agriculture and Human Values, 34, 179-183. doi.org/10.1007/s10460-016-9682-7.
Corbet, S., Hou, Y. G., Hu, Y., Oxley, L., & Xu, D. (2021). Pandemic-related financial market volatility spillovers: Evidence from the Chinese COVID-19 epicentre. International Review of Economics & Finance, 71, 55-81. doi.org/10.1016/j.iref.2020.06.022.
Cui, H., & Zhao, H. (2023). Economic policy uncertainty, entrepreneur confidence, and export trade: An empirical analysis based on the TVP-SV-VAR model. Research on Technology Economics and Management, (10), 94-99. doi.org/10.3969/j.issn.1004-6033.2023.10.018.
Drabenstott, M., & Heffernan, P. (1984). Financial futures: a useful tool for transferring interest rate risk away from farm borrowers or lenders? American journal of agricultural economics, 66(5), 614-619. doi.org/10.2307/1240964.
Du, X., Cheng, J., Zhu, D., & Xing, M. (2023). Does central bank communication on financial stability work?——An empirical study based on Chinese stock market. International Review of Economics & Finance, 85, 390-407. doi.org/10.1016/j.iref.2023.02.003
Fang, T., & Su, Z. (2021). Does uncertainty matter for US financial market volatility spillovers? Empirical evidence from a nonlinear Granger causality network. Applied Economics Letters, 28(21), 1877-1883. doi.org/10.1080/13504851.2020.1854656
Fang, Z., Ni, Y., & Zhuang, J. (2011). The impact of monetary policy shocks on stock market liquidity: An empirical study based on the Markov regime-switching VAR model. Financial Research, (07), 43-56. doi.org/10.3969/j.issn.1001-1070.2011.07.006
Fernández-Amador, O., Gächter, M., Larch, M., & Peter, G. (2013). Does monetary policy determine stock market liquidity? New evidence from the euro zone. Journal of Empirical Finance, 21, 54-68. doi.org/10.1016/j.jempfin.2012.12.008
Fischer, S., & Merton, R. C. (1984). Macroeconomics and finance: The role of the stock market. In Carnegie-Rochester conference series on public policy (Vol. 21, pp. 57-108). North-Holland. doi.org/10.1016/0167-2231(84)90005-8
Gao, Z., & Liang, X. (2023). Research on the impact of investor sentiment on stock market returns based on VAR and EGARCH models. Journal of Zhejiang University (Science Edition), (04), 434-441+454. doi.org/10.3969/j.issn.1673-5650.2023.04.007
Ghosh, S. (2020). Bank lending and monetary transmission: Does politics matter? Journal of Quantitative Economics, 18(2), 359-381. doi.org/10.1007/s40953-019-00190-y
Giglio, S., Maggiori, M., Stroebel, J., & Utkus, S. (2020). Inside the mind of a stock market crash (No. w27272). National Bureau of Economic Research. DOI 10.3386/w27272
Gu, Y., & Wang, Y. (2023). Can macroprudential tools manage RMB exchange rate expectations? An empirical examination based on the TVP-SV-VAR model. International Finance Research, 06, 47-59. doi.org/10.16475/j.cnki.1006-1029.2023.06.008
Guo, W., Lu, L., & Zhong, Y. (2024). How does investor sentiment affect stock market bubbles?—With suggestions on regulating stock market bubbles. Financial Regulation Research, 01, 61-78. doi.org/10.13490/j.cnki.frr.2024.01.004
Haitsma, R., Unalmis, D., & De Haan, J. (2016). The impact of the ECB's conventional and unconventional monetary policies on stock markets. Journal of Macroeconomics, 48, 101-116. doi.org/10.1016/j.jmacro.2016.02.004
Hayo, B., & Neuenkirch, M. (2015). Self-monitoring or reliance on media reporting: How do financial market participants process central bank news? Journal of Banking & Finance, 59, 27-37. doi.org/10.1016/j.jbankfin.2015.06.004
He, Y., Liu, S., & Jiang, H. (2024). Investor structure and stock market fluctuations: a quantitative analysis. Applied Economics Letters, 1-5. doi.org/10.1080/13504851.2023.2300958
Hu, Y. (2018). Research on the transmission path of monetary policy through the stock market (Doctoral dissertation, Northwestern Polytechnical University). https://kns.cnki.net/KCMS/detail/detail.aspx?dbname=CDFDLAST2022&filename=1020706855.nh
Huang, D. S., Jiang, F. W., Tu, J., & Zhou, G. F. (2015). Investor sentiment aligned: A powerful predictor of stock returns. Review of Financial Studies, 28(3), 791-837. doi.org/10.1093/rfs/hhu080
Huang, K., Chen, Y., Liu, S., & Wen, Z. (2021). "Black Swan" events and the dynamic network of volatility transmission in China's financial markets. Journal of Financial Economics Research, (05), 31-47. doi.org/CNKI:SUN:JIRO.0.2021-05-003
Hubbs, T., & Kuethe, T. (2017). A disequilibrium evaluation of public intervention in agricultural credit markets. Agricultural Finance Review, 77(1), 37-49. doi.org/10.1108/AFR-04-2016-0032
Hughes, D. W. (1981). Impacts of regulatory change on financial markets for agriculture: discussion. American journal of agricultural economics, 63(5). doi.org/10.2307/1241270
Hung, K. C., & Ma, T. (2017). Does monetary policy have any relationship with the expectations of stock market participants? Journal of Multinational Financial Management, 39, 100-117. doi.org/10.1016/j.mulfin.2016.11.004
Jiang, F., Meng, L., & Tang, G. (2021). Media text sentiment and stock return prediction. Economics (Quarterly), 04, 1323-1344. doi.org/10.13821/j.cnki.ceq.2021.04.10
Kahneman, D. A. N. I. E. L., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 363-391. doi.org/10.2307/1914185
Kassouri, Y., & Kacou, K. Y. T. (2022). Does the structure of credit markets affect agricultural development in West African countries?. Economic Analysis and Policy, 73, 588-601. doi.org/10.1016/j.eap.2021.12.015
Khan, M., Kayani, U. N., Khan, M., Mughal, K. S., & Haseeb, M. (2023). COVID-19 Pandemic & Financial Market Volatility; Evidence from GARCH Models. Journal of Risk and Financial Management, 16(1), 50. doi.org/10.3390/jrfm16010050
Kuethe, T., & Hubbs, T. (2021). Credit booms and financial instability in US agriculture. Agricultural Finance Review, 81(1), 1-20. doi.org/10.1108/AFR-04-2020-0055
LaDue, E. L., & Leatham, D. J. (1984). Floating versus fixed-rate loans in agriculture: effects on borrowers, lenders, and the agriculture sector. American Journal of Agricultural Economics, 66(5), 607-613. doi.org/10.2307/1240963
LEE, C. M. C., Shleifer, A., & Thaler, R. H. (1991). Investor sentiment and the closed-end fund puzzle. The Journal of Finance, 46(1), 75-109. doi.org/10.1111/j.1540-6261.1991.tb03746.x
Li, C., & Zheng, K. (2022). The internal logic of China's economic policy and financial market volatility: From the perspective of big data mining. Modern Economic Research, (09), 49-61. doi.org/10.13891/j.cnki.mer.2022.09.002
Li, L., Cao, X., & Ding, W. L. (2023). The indirect time-varying impact of interest rates on stock prices: An empirical study based on the TVP-SV-VAR model. Accounting Friend, (09), 16-22. doi.org/10.3969/j.issn.1004-5937.2023.09.003
Li, R., Qian, Z., & Sun, T. (2017). The effectiveness of China's monetary policy and its interaction with the stock market: An empirical study based on the SVAR model. Economic Theory and Economic Management, 03, 48-60. doi.org/10.3969/j.issn.1004-1804.2017.03.005
Liu, J., & Shen, Y. (2022). Can central bank communication mitigate financial market volatility? Modern Economic Research, (03), 36-43. doi.org/10.13891/j.cnki.mer.2022.03.011
Liu, T. (2020). An empirical analysis of the impact of economic policy uncertainty on stock market volatility (Doctoral dissertation, Central University of Finance and Economics). https://kns.cnki.net/KCMS/detail/detail.aspx?dbname=CDFDLAST2022&filename=1020830853.nh
Lu, M. (2008). Crisis management of the stock market and commercial banks. Research on Financial Issues, (08), 119-123. doi.org/10.3969/j.issn.1000-2854.2008.08.020
Lü, Z., Xu, J., & Liu, L. (2023). The interest rate transmission mechanism and transmission efficiency of monetary policy in China: empirical analysis based on TVP-SV-VAR model. Journal of the Asia Pacific Economy, 1-35. doi.org/10.1080/13547860.2023.2206691
Luo, J., & Hu, J. (2023). Agricultural credit guarantees, credit supply, and agricultural economic development. Finance & Trade Research, 03, 68-79. doi.org/10.19337/j.cnki.34-1093/f.2023.03.006
Luo, X. (2020). Research on stock market price and volatility forecasting in China based on deep learning (Doctoral dissertation, Zhongnan University of Economics and Law). https://kns.cnki.net/KCMS/detail/detail.aspx?dbname=CDFDLAST2022&filename=1021511449.nh
Mckibbin, W. J., Wang, Z., & Coyle, W. (2001). The asian financial crisis and global adjustments: implications for us agriculture. Japanese Economic Review, 52(4), 471-490. doi.org/10.1111/1468-5876.00207
Moessner, R. (2014). Effects of explicit FOMC policy-rate guidance on equities and risk measures. Applied Economics, 46(18), 2139-2153. doi.org/10.1080/00036846.2014.894668
Morck, R., Yeung, B., & Yu, W. (2000). The information content of stock markets: why do emerging markets have synchronous stock price movements? Journal of financial economics, 58(1-2), 215-260. doi.org/10.1016/S0304-405X(00)00071-4
Nakajima, J. (2011). Time-varying parameter VAR model with stochastic volatility: An overview of methodology and empirical applications. Monetary and Economic Studies, 29, 107-142.
Pietola, K., Myyrä, S., & Heikkilä, A. M. (2011). The penetration of financial instability in agricultural credit and leveraging. Brussels, Belgium: Centre for European Policy Studies (CEPS).
Primiceri, G. E. (2005). Time varying structural vector autoregressions and monetary policy. The Review of Economic Studies, 72(3), 821-852. doi.org/10.1111/j.1467-937X.2005.00353.x
Qian, Z., Wang, F., & Sun, T. (2021). The impact of financial cycles on real estate prices: An empirical study based on the SV-TVP-VAR model. Financial Research, 03, 58-76. doi.org/10.3969/j.issn.1002-2563.2021.03.004
Regmi, M., & Featherstone, A. M. (2022). Competition, performance and financial stability in US agricultural banking. Agricultural Finance Review, 82(1), 67-88. doi.org/10.1108/AFR-12-2020-0185
Reif, M. (2022). Time‐Varying Dynamics of the German Business Cycle: A Comprehensive Investigation. Oxford Bulletin of Economics and Statistics, 84(1), 80-102. doi.org/10.1111/obes.12464
Rodriguez, G., Castillo B, P., & Ojeda Cunya, J. A. (2023). Time-Varying Effects of External Shocks on Macroeconomic Fluctuations in Peru: An Empirical Application using TVP-VAR-SV Models. Open Economies Review, 1-36. doi.org/10.1007/s11079-023-09742-5
Schwert, G. W. (1989). Why does stock market volatility change over time? Journal of finance, 44(5), 1115-1153. doi.org/10.1111/j.1540-6261.1989.tb02647.x
Schwert, G. W. (1990). Stock market volatility. Financial analysts journal, 23-34. doi.org/10.2469/faj.v46.n3.23
Shan, J., & Wang, H. (2024). Financial risk spillover between capital markets and the real sector and the effect of macro policy regulation. Journal of Central University of Finance and Economics, (04), 3-17. doi.org/10.19681/j.cnki.jcufe.2024.04.007
Shane, M. D., & Liefert, W. M. (2000). The international financial crisis: macroeconomic linkages to agriculture. American Journal of Agricultural Economics, 82(3), 682-687. http://www.jstor.org/stable/1244624
Song, C., & Zhang, Y. (2023). Economic policy uncertainty, financial stability, and economic fluctuations: A dynamic analysis based on the TVP-SV-VAR model. Finance Theory and Practice, (02), 32-37. doi.org/10.16339/j.cnki.hdxbcjb.2023.02.005
Sun, L., & Zhu, Y. (2022). The risk spillover effect of the Chinese stock market on commercial banks. Applied Probability and Statistics, (02), 285-302. doi.org/10.3969/j.issn.1000-0215.2022.02.006
Tang, C., & Liu, X. (2023). Bitcoin speculation, investor attention and major events. Are they connected?. Applied Economics Letters, 30(8), 1033-1041. doi.org/10.1080/13504851.2022.2033677
Thiem, C. (2020). Cross-Category, Trans-Pacific Spillovers of Policy Uncertainty and Financial Market Volatility. Open Economies Review, 31(2), 317-342. doi.org/10.1007/s11079-019-09559-1
Wang, L., & Liu, H. (2022). Can central bank communication effectively respond to sudden “tests”?: A text analysis of People’s Bank of China communication events. Journal of Beijing Institute of Technology (Social Sciences Edition), (01), 77-89. doi.org/10.15918/j.jbitss1009-3370.2022.1900
Wang, Y., & Wang, Y. (2014). The role of investor sentiment in asset pricing. Management Review, (06), 42-55. doi.org/10.14120/j.cnki.cn11-5057/f.2014.06.039
Wang, Y., Liu, H., & Wu, L. (2009). Information transparency, institutional investors, and stock price synchronicity. Financial Research, (12), 162-174. doi.org/10.1016/j.jfineco.2005.01.003
Wang, Y., Yuan, J., & Liu, T. (2023). The dynamic spillover effects of U.S. fiscal and monetary policy adjustments on the Chinese economy: An empirical study based on the TVP-SV-VAR model. International Trade Issues, (07), 54-68. doi.org/10.13687/j.cnki.gjjmts.2023.07.007
Wang, Z. L., & Liu, N. (2024). High goodwill impairment and stock price crash risk: A study based on investor sentiment. Finance and Accounting Monthly, (14), 80-84. doi.org/10.16144/j.cnki.issn1002-8072.2024.14.015
Wen, X. C. (2017). The impact of changes in investor sentiment and monetary policy adjustments on stock market cycles: Evidence from a stock market DSGE model with heterogeneous expectations. Journal of Central University of Finance and Economics, (08), 23-36+46. doi.org/10.19681/j.cnki.jcufe.2017.08.004
Xie, S., & Mo, T. (2014). Index futures trading and stock market volatility in China: a difference‐in‐difference approach. Journal of Futures Markets, 34(3), 282-297. doi.org/10.1002/fut.21650
Xing, D., & Guan, Z. (2020). Stock market volatility, economic policy uncertainty, and household participation in financial markets: An empirical analysis based on CFPS panel data. New Finance, (11), 57-64. doi.org/CNKI:SUN:XJRO.0.2020-11-011
Xing, T., & Wang, X. (2022). The impact of economic policy uncertainty on the development of China's capital market and its countermeasures. Zhongzhou Academic Journal, (06), 14-20. doi.org/10.3969/j.issn.1000-0105.2022.06.003
Xu, A., & Zheng, X. (2023). Impact of the COVID-19 pandemic, investor sentiment, and corporate financing constraints. Fiscal Science, (02), 76-86. doi.org/10.19477/j.cnki.10-1368/f.2023.02.013
Xu, B. (2018). Speculators in stock index futures and stock market volatility: Empirical evidence from the CSI 300 index futures. Economic Survey, (02), 151-157. doi.org/10.15931/j.cnki.1006-1096.20180105.008
Xue, F. (2005). A study of investor behavior based on emotions (Doctoral dissertation, Fudan University). https://kns.cnki.net/KCMS/detail/detail.aspx?dbname=CDFD9908&filename=2005121470.nh
Yang, S., Niu, D., Liu, T., & Wang, Z. (2021). The impact of investor sentiment on the financialization of real enterprises from a behavioral finance perspective. Management Review, (06), 3-15. doi.org/10.14120/j.cnki.cn11-5057/f.2021.06.001
Yang, X. (2016). Research on volatility and options of the Chinese stock market (Doctoral dissertation, University of International Business and Economics). https://kns.cnki.net/KCMS/detail/detail.aspx?dbname=CDFDLAST2017&filename=1017002338.nh
Yi, H. (2020). Interview with the Chairman of the China Securities Regulatory Commission on China's capital market opening to the world and U.S.-China cross-border regulatory cooperation issues. Retrieved from http://www.csrc.gov.cn/csrc/c100028/c1000757/content.shtml
You, W., Chen, S., Chen, J., & Ren, Y. (2023). The impact of "speak much, act little" environmental responsibility performance on stock price crash risk: The mediating effect of investor sentiment. China Management Science. doi.org/10.16381/j.cnki.issn1003-207x.2023.1361
Yu, X. W. (2013). A study on the relationship between government bond market volatility and stock market volatility. Commercial Times, (04), 57-58. doi.org/CNKI:SUN:SYJJ.0.2013-04-026
Yu, Y., Wei, H., & Chen, T. (2022). Applications of the Investor Sentiment Polarization Model in Sudden Financial Events. Systems, 10(3), 75. doi.org/10.3390/systems10030075
Zhang, C., & Yu, T. (2023). Rural credit investment, service outsourcing level, and urban-rural income gap. Economic System Reform, (01), 89-98. doi.org/CNKI:SUN:JJTG.0.2023-01-010
Zhang, X., Zhou, H., & Lee, C. C. (2022). Systemic risk of China’s financial industry during the spread of the COVID-19 epidemic and the breakdown of crude oil negotiation. Emerging Markets Finance and Trade, 58(1), 56-69. doi.org/10.1080/1540496X.2021.1968824
Zhao, Y., Mou, D., Li, Z. H., & Ma, J. M. (2024). The impact of economic policy uncertainty on the IPO underpricing rate of the Science and Technology Innovation Board. Investment Research, (04), 120-144. doi.org/10.15932/j.cnki.tzyj.2024.04.008
Zheng, M., Ni, Y., & Liu, L. (2010). The impact of monetary policy on stock prices in China: An empirical analysis based on the Markov regime-switching VAR model. Economic Management, (11), 7-15. doi.org/10.19616/j.cnki.bmj.2010.11.004
Zhou, D., Siddik, A. B., Guo, L., & Li, H. (2023). Dynamic relationship among climate policy uncertainty, oil price and renewable energy consumption—Findings from TVP-SV-VAR approach. Renewable Energy, 204, 722-732. doi.org/10.1016/j.renene.2023.01.018
Zhu, N., Chen, Y., & Xu, Y. (2019). Can new monetary policy tools stabilize the capital market?—Empirical evidence based on China's stock index returns. Systems Engineering, (01), 86-100. doi.org/CNKI:SUN:GCXT.0.2019-01-009
Zou, W., Wang, X., & Xie, X. (2020). Financial market response to central bank communication: An event study based on the stock market. Financial Research, (02), 34-50. doi.org/10.16381/j.cnki.issn1001-8004.2020.02.003