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跳跃的估计、股市波动率的预测以及预测精度评价

, PP. 50-60

Keywords: 波动率预测,已实现波动率,C_TMPV,MIDAS模型,SPA检验

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Abstract:

?本文基于C_TMPV理论估计已实现波动率的跳跃成分,在此基础上构建考虑跳跃的AHAR-RV-CJ模型和MIDAS-RV-CJ模型来预测中国股市的已实现波动率,并评价和比较各类波动率模型的预测精度。实证结果表明:基于C_TMPV估计的波动率跳跃成分对日、周以及月波动率的预测有显著的正向影响;AHAR-RV-CJ模型和MIDAS-RV-CJ模型的样本内和样本外预测精度在不同的预测时域上都是最高的,尤其是对数形式的模型;MIDAS族模型的样本外预测精度在中长期预测时域上比HAR族模型高;AHAR-RV-CJ模型和MIDAS-RV-CJ模型的样本外预测能力在中长期预测时域上比基于低频数据的Jump-GARCH模型、SV-CJ模型和SV-IJ模型好。

References

[1]  Andersen T G, Bollerslev T, Diebod F X,et.al. Modelling and forecasting realized volatility [J]. Econometrica, 2003, 71(2): 579-625.
[2]  Corsi F. A simple approximate long memory model of realized volatility[J]. Journal of Financial Econometrics, 2009, 7(2): 174-196.
[3]  徐正国,张世英. 调整"已实现"波动率与GARCH及SV模型对波动的预测能力的比较研究[J]. 系统工程,2004, 22(8): 60-63.
[4]  郭名媛,张世英. 赋权已实现波动及其长记忆、最优抽样频率选择 [J]. 系统工程学报, 2006, 21(6): 568-573.
[5]  魏宇,余怒涛. 中国股票市场的波动率预测模型及其SPA检验 [J]. 金融研究, 2007, 28(7): 138-150.
[6]  魏宇. 中国股票市场的最优波动率预测模型研究[J]. 管理学报, 2010, 7(6): 936-942.
[7]  Andersen T G, Bollerslev T, Diebod F X. Roughing it up: Including jump components in the measurement, modeling, and forecasting of return volatility [J]. The Review of Economics and Statistics, 2007, 89(4): 701-720.
[8]  Giot P, Laurent S. The information content of implied volatility in the light of the jump/continuous decomposition of realized volatility [J]. Journal of Future Markets, 2007, 27(3): 337-359.
[9]  王春峰,姚宁,房振明,等. 中国股市已实现波动率的跳跃行为研究 [J]. 系统工程, 2008, 26(2): 1-6.
[10]  Shalen C T. Volume, volatility and dispersion of beliefs [J]. Review of Financial Studies, 1993, 6(2):405-434.
[11]  Wang Jiang. A model of competitive stock trading volume [J]. Journal of Political Economy, 1994, 102(1):127-168.
[12]  Buraschi A, Trojani F, Vedolin A. The joint behavior of credit spreads, stock options and equity returns when investors disagree [R]. Working Paper, Imperial College,2007.
[13]  杨科,陈浪南. 跳跃对中国股市波动率预测的影响研究[J]. 山西财经大学学报, 2010, 32(8): 39-48.
[14]  Hansen P R, Lunde A. Realized variance and market microstructure noise[J]. Journal of Business and Economic Statistics, 2006, 24(2): 127-218.
[15]  Barndor-Nielsen O E, Shephard N. Realized power variation and stochastic volatility [J]. Bernoulli, 2003, 9(2): 243-265.
[16]  Barndor-Nielsen O E, Shephard N. Econometric analysis of realised covariation: high frequency covariance, regression and correlation in financial economics[J]. Econometrica, 2004, 72(3): 885-925.
[17]  Barndor-Nielsen O E, Shephard N. Impact of jumps on returns and realized variances: econometric analysis of time-deformed levy process[J]. Journal of Econometrics, 2006, 131(1): 217-252.
[18]  Huang Xin, Tauchen G. The relative contribution of jumps to total price variance[J]. Journal of Financial Econometrics, 2005, 3(4):456-499.
[19]  Corsi F, Pirino D, Reno R. Threshold bipower variation and the impact of jumps on volatility forecasting[J]. Journal of Econometrics, 2010, 159(2):276-288.
[20]  Forsberg L, Ghysels, E. Why do absolute returns predict volatility so well?[J]. Journal of Financial Econometrics, 2007, 5(1): 31-67.
[21]  Ghysels E, Valkanov R. Linear time-series processes with mixed data sampling and MIDAS regression models [R]. Discussion paper, UNC and UCSD, 2006.
[22]  Ghysels E, Santa-Clara P, Valkanov R. Predicting volatility: getting the most out of return data sampled at different frequencies[J]. Journal of Econometrics, 2006b, 131(1): 59-95.
[23]  Ghysels E., Santa-Clara P, Valkanov R. MIDAS regressions: further results and new directions [J]. Econometric Reviews, 2007, 26(1): 53-90.
[24]  Ghysels E, Santa-Clara P, Valkanov R. The MIDAS touch: mixed data sampling regression models[R]. Discussion paper, UNC and UCLA, 2010.
[25]  Potton A J. Volatility forecast comparison using imperfect volatility proxies[J]. Journal of Econometrics, 2011, 160(1): 246-256.
[26]  Hansen P R, Lunde A. A forecast comparison of volatility models: Does anything beat a GARCH(1,1)?[J]. Journal of Applied Econometrics, 2005, 20(7): 873-889.
[27]  Maheu J M, Mc Curdy H. New arrival, jump dynamics and volatility components for individual stock returns[J]. Journal of Finance, 2004, 59(2): 755-793.
[28]  Duffie D, Pan J, Singleton K. Transform analysis and asset pricing for affine jump-diffusions[J]. Econometrica, 2000, 68(6):1343-1376.
[29]  Eraker B, Johannes M S, Polson N G. The impact of jumps in volatility and return[J]. Journal of Finance, 2003, 58(3):1269-1300.

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