信息冲击对股票市场影响的建模与检验
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参考文献

[1] 谢海滨,范奎奎,周末.中国股市对利好和利空信息反应的差异研究[J].系统工程理论与实践,2015,35(7):1777-1783.

[2] B. G. Malkiel, F. Fama. Efficient capital markets: A review of theory and empirical work [J]. Journal of Finance, 1970, 25(2): 383-417.

[3] R. J. Shiller. Do stock prices move too much to be justified by subsequent changes in dividends [J]. American Economic Review, 1981(71): 421-436.

[4]W. F. M. Debondt, R. Thaler. Does the stock market overreact [J]. Journal of Finance, 1995(40):793-805.

[5]N. Jegadeesh, S. Titmamn. Returns to buying winners and selling losers: Implications for stock market efficiency [J]. Journal of Finance, 1993(48): 65-91.

[6] J. Chen, F. Jiang, G. S. Tong. Economic policy uncertainty in China and stock market expected returns [J]. Accounting and Finance, 2017, 57(5): 1265-1286.

[7] F. X. Diebold, K. Yilmaz. On the network topology of variance decompositions: Measuring the connectedness of financial firms [J]. Journal of Econometrics, 2014, 182(1): 119-134.

[8] R. Maderitsch. Information transmission between stock markets in Hong Kong, Europe and the US: New evidence on time-and state-dependence [J]. Pacific-Basin Finance Journal, 2015(35): 13-36.

[9] R. S. Pindyck. Risk, inflation, and the stock market [J]. American Economic Review, 1984, 74(3): 335-351.

[10] K. R. French, G. W. Schwert, R. F. Stambugh. Expected stock returns and volatility [J]. Journal of Financial Economics, 1987, 19(1): 3-29.

[11] D. B. Nelson. Conditional heteroskedasticity in asset returns: A new approach [J]. Econometrica, 1991, 59(2): 347-370.

[12] L. R. Glosten, R. Jagannathan, D. E. Runkle. On the relation between the expected value and the volatility of the nominal excess return on stocks [J]. The Journal of Finance, 1993, 48(5): 1779-1801.

[13] Z. Ding, C. W. J. Granger, R. F. Engle. A long memory property of stock market returns and a new model [J]. Journal of Empirical Finance, 1993, 1(1): 83-106.

[14] M. K. P. So, W. K. Li, K. Lam. A threshold stochastic volatility model [J]. Journal of Forecasting, 2002, 21(7): 473-500.

[15] H. Tanizaki, S. Hamori. Volatility transmission between Japan, UK and USA in daily stock returns [J]. Empirical Economics, 2009, 36(1): 27-54.

[16] F. X. Diebold, K. Yilmaz. Better to give than to receive: Predictive directional measurement of volatility spillovers [J]. International Journal of Forecasting, 2012, 28(1): 57-66.

[17] O. E. Barndorff-Nielsen, S. Kinnebrock, N. Shephard. Measuring downside risk-realised semivariance [A]//T. Bollerslev, J. Russell, and M. Watson. Volatility and time series econometrics: essays in honor of robert engle [M]. Cambridge, MA: Oxford University Press, 2010: 117-136.

[18] K. H. Bae, G. A. Karolyi. Good news, bad news and international spillovers of stock re-turn volatility between Japan and the US [J]. Pacific-Basin Finance Journal, 1994, 2(1): 405-438.

[19] J. Campbell, L. Hentschel. No news is good information: An asymmetric model of changing volatility in stock returns [J]. Journal of Financial Economics, 1992, 31(3): 281-318.

[20]L. Yarovaya, M. C. K. Lau. Stock market comovements around the global financial crisis: Evidence from the UK, BRICS and MIST markets [J]. Research in International Business and Finance, 2016(37): 605-619.

[21] S. Radchenko. Oil price volatility and the asymmetric response of gasoline prices to oil price increases and decreases [J]. Energy Economics, 2005, 27(5): 708-730.

[22] Q. Ji, J. F. Guo. Market interdependence among commodity prices based on information transmission on the Internet [J]. Physica A: Statistical Mechanics and its Applications, 2015(426): 35-44.

[23] J. S. Kim, D. Ryu. Intraday price dynamics in spot and derivatives markets [J]. Physica A: Statistical Mechanics and its Applications, 2014(394): 247-253.

[24] T. Chikashi. Return transmission and asymmetric volatility spillovers between oil futures and oil equities: New DCC-MEGARCH analyses [J]. Economic Modelling, 2018(74): 167-185.

[25] M. S. Sanusi, D. Mcmillan. Investigating the sources of Black’s leverage effect in oil and gas stocks [J]. Cogent Economics and Finance, 2017, 5(1): 1-13.

[26] J. BaruníK, E. KoíEnda, L. Vácha. Asymmetric connectedness on the US. stock market: Bad and good volatility spillovers [J]. Journal of Financial Markets, 2016(27).

[27] P. Srinivasan, K. Srinivasan, M. Deo. Impact of derivatives and asymmetric effect on Indian stock market volatility [J]. Asia Pacific Business Review, 2009, 5(3): 11-18.

[28] G. G. Booth, T. Martikainen, Y. Tse. Price and volatility spillovers in Scandinavian stock markets [J]. Journal of Banking and Finance, 1997, 21(6): 811-823.

[29] D. Gjika, R. Horvath. Stock market comovements in Central Europe: Evidence from asymmetric DCC model [J]. Economic Modelling, 2013, 33(2): 55-64.

[30] A. Worthington, H. Higgs. Transmission of equity returns and volatility in Asian developed and emerging markets: A multivariate GARCH analysis [J]. International Journal of Finance and Economics, 2004, 9(1): 71-80.

[31]S. Kundu, N. Sarkar. Return and volatility interdependences in up and down markets across developed and emerging countries [J]. Research in International Business and Finance, 2016(36): 297-311.

[32]H. H. Lean, K. T. Teng. Integration of world leaders and emerging powers into the Malaysian stock market: A DCC-MGARCH approach[J]. Economic Modelling, 2013(32): 333-342.

[33] S. Celik. The more contagion effect on emerging markets: The evidence of DCCGARCH model [J]. Economic Modelling, 2012, 29(5): 1946-1959.

[34] H. Li. The impact of China’s stock market reforms on its international stock market linkages [J]. Quarterly Review of Economics and Finance, 2012, 52(4): 358-368.

[35] F. Black. Studies of stock market volatility changes [J]. Proceedings of the American Statistical Association Bisiness and Economic Statistics Section, 1976: 177-181.

[36] T. Bollerslev, J. Litvinova, G. Tauchen. Leverage and volatility feedback effects in high frequency data [J]. Journal of Financial Econometrics, 2006, 4(3): 353-384.

[37] K. A. Tversky. Prospect Theory: An analysis of decision under risk [J]. Econometrica, 1979, 47(2): 263-292.

[38] 张维,张海峰,张永杰,等.基于前景理论的波动不对称性[J].系统工程理论与实践,2012(3):458-465.

[39] L. Long, A. K. Tsui, Z. Zhang. Conditional heteroscedasticity with leverage effect in stock returns: Evidence from the Chinese stock market [J]. Economic Modelling, 2014(37): 89-102.

[40] Y. H. Yeh, T. S. Lee. The interaction and volatility asymmetry of unexpected returns in the greater China stock markets [J]. Global Finance Journal, 2000(11): 129-149.

[41] 张维,张小涛,熊熊.上海股票市场波动不对称性研究——GJR与VS-GARCH模型的比较[J].数理统计与管理,2005(6):96-102.

[42] 李红权,洪永淼,汪寿阳.我国A股市场与美股、港股的互动关系研究:基于信息溢出视角[J].经济研究,2011(8):15-25.

[43] 何兴强,李涛.不同市场态势下股票市场的非对称反应——基于中国上证股市的实证分析[J].金融研究,2007(8):131-140.

[44] 陆蓉,徐龙炳.“牛市”和“熊市”对信息的不平衡性反应研究[J].经济研究,2004(3):65-72.

[45] 刘烨,方立兵,李冬昕.融资融券交易与市场稳定性:基于动态视角的证据[J].管理科学学报,2016,19(1):102-116.

[46] 许红伟,陈欣.我国推出融资融券交易促进了标的股票的定价效率吗?——基于双重差分模型的实证研究[J].管理世界,2012(5):52-61.

[47] 蔡向高,邓可斌.无消息即坏消息:中国股市的信息不对称[J].管理科学学报,2019,22(4):75-91.

[48] 邹永杰,李红刚.上证综合指数弱式有效性的时变性研究[J].系统工程理论与实践,2014(34):32-39.

[49] 王永宏,赵学军.中国股市“惯性策略”和“反转策略”的实证分析[J].经济研究,2001(6):56-61.

[50] 朱战宇,吴冲锋,王承炜.不同检验周期下中国股市价格动量的盈利性研究[J].世界经济,2003(8):62-67.

[51] 陈蓉,陈焕华,郑振龙.动量效应的行为金融学解释[J].系统工程理论与实践,2014(3):71-80.

[52] R. Aloui, M. S. B. Aissa, D. K. Nguyen. Global financial crisis, extreme interdependences, and contagion effects [J]. Journal of Banking and Finance, 2011(35): 130-141.

[53]R. Bhuyana, M. G. Robbanib, B. Talukarc, et al. Information transmission and dynamics of stock price movements: An empirical analysis of BRICS and US stock markets [J]. International Review of Economics and Finance, 2016(46): 180-195.

[54]P. Singh, B. Kumar, A. Pandey. Price and volatility spillovers across? North American, European and Asian stock markets [J]. International Review of Financial Analysis, 2010(19): 55-64.

[55]H. Lehkonen, K. Heimonen. Timescale-dependent stock market comovement: BRICs vs. developed markets [J]. Journal of Empirical Finance, 2014(28): 90-103.

[56] T. J. George, C. Hwang. The 52-week high and momentum investing [J]. Journal of Finance, 2004, 59(5): 2145-2176.

[57] S. Huddart, M. Lang, M. H. Yetman. Volume and price patterns around a stock’s 52-week highs and lows: Theory and evidence [J]. Management Science, 2009, 5(1): 16-31.

[58] S. A. Corwin, P. Schultz. A simple way to estimate bid-ask spreads from daily high and low prices [J]. Journal of Finance, 2012, 67(2): 719-760.

[59] 唐勇,刘徽.加权以实现极差四次幂变差分析及其应用[J].系统工程理论与实践,2013,33(11):2766-2775.

[60] J. Li, J. F. Yu. Investor attention, psychological anchors, and stock return predictability [J]. Journal of Financial Economics, 2012, 104(2): 401-419.

[61] 谢海滨,顾霞,魏云捷.基于信息分解视角的香港股市运行效率研究[J].系统工程理论与实践,2017,37(6):1432-1440.

[62] M. E. J. Newman. The structure and function of complex networks [J]. SIAM Review, 2003, 45(2): 167-256.

[63] X. Y. Liu, H. Z. An, H. J. Li, et al. Features of spillover networks in international financial markets: Evidence from the G20 countries[J]. Physica A: Statistical Mechanics and its Applications, 2017(479): 265-278.

[64] M. Billio, M. Getmansky, A. W. Lo, et al. Econometric measures of connectedness and systemic risk in the finance and insurance sectors [J]. Journal of Financial Economics, 2012, 104(3): 535-559.

[65]李政,梁琪,涂晓枫.我国上市金融机构关联性研究——基于网络分析法[J].金融研究,2016(8):95-110.

[66]S. Lyócsa, T. Výrost, E. Baumohl. Return spillovers around the globe: A network approach [J]. Economic Modelling, 2019(77): 133-146.

[67]G. J. Wang, C. Xie, K. He, et al. Extreme risk spillover network: Application to financial institutions [J]. Quantitative Finance, 2017, 17(9): 1-23.

[68] F. Betz, N. Hautsch, T. A. Peltonen, et al. Systemic risk spillovers in the European banking and sovereign network [J]. Journal of Financial Stability, 2016(25): 206-224.

[69] W. Hardle, W. Wang, L. Yu. Tenet: Tail-Event driven network risk [J]. Journal of E-conometrics, 2016(46): 62-69.

[70] W. Q. Huang, X. T. Zhuang, S. Yao, et al. A financial network perspective of financial institutions’systemic risk contributions [J]. Physica A: Statistical Mechanics and Its Applications, 2016(456): 183-196.

[71] M. Anufriev, V. Panchenko. Connecting the dots: Econometric methods for uncovering networks with an application to the Australian financial institutions [J]. Journal of Banking and Finance, 2015, 61(2): S241-S255.

[72] A. Gandy, L. A. M. Veraart. A bayesian methodology for systemic risk assessment in financial networks [J]. Management Science, 2017, 63(12): 4428-4446.

[73] K. D. Yin, Z. Liu, P. D. Liu. Trend analysis of global stock market linkage based on a dynamic conditional correlation network [J]. Journal of Business Economics and Management, 2017, 18(4): 779-800.

[74] D. Acemoglu, V. M. Carvalho, A. E. Ozdaglar, et al. The network origins of aggregate fluctuations [J]. Econometrica, 2012, 80(5): 1977-2016.

[75]W. Mensi, F. Z. Boubaker, K. H. Ai-Yahyaee, et al. Dynamic volatility spillovers and connectedness between global, regional, and GIPSI stock markets [J]. Finance Research Letters, 2018(25): 230-238.

[76]F. X. Diebold, K. Yilmaz. Trans-Atlantic equity volatility connectedness: US. and European financial institutions, 2004-2014[J]. Journal of Financial Econometrics, 2016, 14(1): 81-127.

[77] I. Aldasoro, D. Delli Gatti, E. Faia. Bank networks: Contagion, systemic risk and prudential policy [J]. Journal of Economic Behavior and Organization, 2017(142): 164-188.

[78] P. Gai, A. Haldane, S. Kapadia. Complexity, concentration and contagion [J]. Journal of Monetary Economics, 2011, 58(5): 453-470.

[79] S. Lahmiri. Asymmetric and persistent responses in price volatility of fertilizers through stable and unstable periods [J]. Physica A: Statistical Mechanics and its Applications, 2016(466): 405-414.

[80] N. Ai Rahahleh, M. I. Bhatti. Co-movement measure of information transmission on international equity markets [J]. Physica A: Statistical Mechanics and its Applications, 2017(470): 119-131.

[81] T. Odean. Are investors reluctant to realize their losses? [J]. The Journal of Finance, 1998, 53(5): 1775-1798.

[82] 史永东,李竹薇,陈炜.中国证券投资者交易行为的实证研究[J].金融研究,2009(11):133-146.

[83] 陈浪南,陈文博.中国股市非对称V字形处置效应的实证研究[J].管理工程学报,2020,1(34):63-78.

[84] 孙培源,施东晖.基于CAPM的中国股市“羊群行为”研究[J].经济研究,2002(2):64-70.

[85] 卞曰瑭,李金生,何建敏,等.网络近邻择优策略下的股市“羊群行为”演化模型及仿真[J].中国管理科学,2013,21(3):40-49.

[86] 姚禄仕,吴宁宁.基于LSV模型的机构与个人“羊群行为”研究[J].中国管理科学,2018,226(7):55-62.

[87] A. Christie. The stochastic behavior of common stock variances: Value, leverage and interest rate effects [J]. Joural of Financial Economics, 1982(10): 407-432.

[88] 陈永伟.股市波动的杠杆效应检验:一种新的方法[J].中国管理科学,2012,10(20):31-36.

[89] C. A. Sims. Macroeconomics and reality [J]. Econometrica, 1980, 48(1): 1-48.

[90] C. W. J. Granger. Investigating causal relations by econometric models and cross-spectral methods [J]. Econometrica, 1969, 37(3): 424-438.

[91] S. Borjigin, Y. Yang, X. Yang, et al. Econometric testing on linear and nonlinear dynamic relation between stock prices and macroeconomy in China[J]. Physica A: Statistical Mechanics and its Applications, 2017(493): 107-115.

[92] F. H. Wen, J. H. Xiao, C. X. Xia, et al. Interaction between oil and US dollar exchange rate: nonlinear causality, time-varying influence and structural breaks in volatility [J]. Applied E-conomics, 2018, 50(3): 319-334.

[93] E. W. Dijkstra. A note on two problems in connexion with graphs [J]. Numerische Mathematik, 1959, 1(1): 269-271.

[94] M. Xu, S. Llang. Input-output networks offer new insights of economic structure [J]. Physica A: Statistical Mechanics and its Applications, 2019(527): 121-178.

[95] A. J. Patton, K. Sheppard. Good volatility, bad volatility: Signed jumps and the persistence of volatility [J]. Review of Economics and Statistics, 2015, 97(3): 683-697.

[96] 何诚颖,陈锐,蓝海平,等.投资者非持续性过度自信与股市反转效应[J].管理世界,2014(8):44-54.


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