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1. Estimation of Equilibrium Term Structure Models: EKF and UKF Based Approaches | |||
SU Yunpeng,YANG Baochen | |||
Economics 06 December 2016 | |||
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Abstract:In a general framework, this paper introduces approaches of estimation for equilibrium models of term structure of interest rates based on the extended Kalman filter (hereafter EKF) and unscented Kalman filter (hereafter UKF). This paper treats the estimation of the equilibrium models as a nonlinear filtering problem, and adopts EKF and the UKF respectively to estimate the model via the maximum likelihood method. Using fourteen years of daily Canadian zero-coupon bond price data, we apply the estimator to Vasicek and Cox-Ingersoll-Ross models based on EKF and UKF respectively. It is found that the EKF-based algorithm offers generally the same performance with the UKF-based one in model estimation when the system is linear or weak linear and the Gaussian distribution assumption is satisfied. But when it comes to the strong nonlinear system with a non-Gaussian distribution, the UKF-based algorithm does a better job than the EKF-based one in model estimation. However the UKF-based algorithm is about 50% slower than the EKF-based one in actual computation, though it is regarded in literature that they both have the same order of computational complexity. | |||
TO cite this article:SU Yunpeng,YANG Baochen. Estimation of Equilibrium Term Structure Models: EKF and UKF Based Approaches[OL].[ 6 December 2016] http://en.paper.edu.cn/en_releasepaper/content/4712769 |
2. Based on spatial analysis to study transmission from Chinese stock market to others | |||
Zhu Manling,Hui Xiaofeng | |||
Economics 29 April 2010 | |||
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Abstract:Chinese stock market has got more and more influence from other regions, since China began QFII and many stocks were back from Hong Kong stock market. Many scholars begin to study this. But they only study time series and don’t think about and ignore these regions spatial character. This paper use spatial analysis to study SSE composite index, Dow Jones Index, Nikkei-225, Singapore straits time index, TWII , HS index and FTSE 100 from January 1, 2006 to January 1, 2007 and from January 1 2007 to January 1 2008. This paper first will build spatial weights and decompose these stock index yield rate. And then quantify the relations between Chinese stock markets and other stock markets. It will compare the influences of Chinese stock market to these stock markets in these two periods. At last this paper constructs spatial transmission model of close price of Chinese SSE and open price of other regions’ stock markets. And this paper found in 2006 chinese stock market had no influence on others, but in 2007 Chinese stock market only influence United States’ stock market. To other markets, Chinese effects are very small. Chinese influence on the world line is: China →United States → other markets. | |||
TO cite this article:Zhu Manling,Hui Xiaofeng. Based on spatial analysis to study transmission from Chinese stock market to others[OL].[29 April 2010] http://en.paper.edu.cn/en_releasepaper/content/42477 |
3. Intraday pattern in bid-ask spreads and its power-law relaxation for Chinese A-share stocks | |||
Xiao-Hui Ni,Wei-Xing Zhou | |||
Economics 16 October 2007 | |||
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Abstract:We use high-frequency data of 1364 Chinese A-share stocks traded on the Shanghai Stock Exchange and Shenzhen Stock Exchange to investigate the intraday patterns in the bid-ask spreads. The daily periodicity in the spread time series is confirmed by Lomb analysis and the intraday bid-ask spreads are found to exhibit $L$-shaped pattern with idiosyncratic fine structure. The intraday spread of individual stocks relaxes as a power law within the first hour of the continuous double auction from 9:30AM to 10:30AM with exponents $\\\\\\\\\\\\\\\\beta_{\\\\\\\\\\\\\\\\rm{SHSE}}=0.20\\\\\\\\\\\\\\\\pm0.067$ for the Shanghai market and $\\\\\\\\\\\\\\\\beta_{\\\\\\\\\\\\\\\\rm{SZSE}}=0.19\\\\\\\\\\\\\\\\pm0.069$ for the Shenzhen market. The power-law relaxation exponent $\\\\\\\\\\\\\\\\beta$ of individual stocks is roughly normally distributed. There is evidence showing that the accumulation of information widening the spread is an endogenous process. | |||
TO cite this article:Xiao-Hui Ni,Wei-Xing Zhou. Intraday pattern in bid-ask spreads and its power-law relaxation for Chinese A-share stocks[OL].[16 October 2007] http://en.paper.edu.cn/en_releasepaper/content/15690 |
4. Relaxation dynamics of aftershocks after large volatility shocks in the SSEC index | |||
Guo-Hua Mu,Wei-Xing Zhou | |||
Economics 17 September 2007 | |||
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Abstract:The relaxation dynamics of aftershocks after large volatility shocks are investigated based on two high-frequency data sets of the Shanghai Stock Exchange Composite (SSEC) index. Compared with previous relevant work, we have defined main financial shocks based on large volatilities rather than large crashes. We find that the occurrence rate of aftershocks with the magnitude exceeding a given threshold for both daily volatility (constructed using 1-minute data) and minutely volatility (using intra-minute data) decays as a power law. The power-law relaxation exponent increases with the volatility threshold and is significantly greater than 1. Taking financial volatility as the counterpart of seismic activity, the power-law relaxation in financial olatility deviates remarkably from the Omori law in Geophysics. | |||
TO cite this article:Guo-Hua Mu,Wei-Xing Zhou. Relaxation dynamics of aftershocks after large volatility shocks in the SSEC index[OL].[17 September 2007] http://en.paper.edu.cn/en_releasepaper/content/15122 |
5. Empirical distributions of Chinese stock returns at different microscopic timescales | |||
Gao-Feng Gu,Wei Chen,Wei-Xing Zhou | |||
Economics 28 August 2007 | |||
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Abstract:We study the distributions of event-time returns and clock-time returns at different microscopic timescales using ultra-high-frequency data extracted from the limit-order books of 23 stocks traded in the Chinese stock market in 2003. We find that the returns at the one-trade timescale obey the inverse cubic law. For larger timescales (2-32 trades and 1-5 minutes), the returns follow the Student distribution with power-law tails. With the decrease of timescale, the tail becomes fatter, which is consistent with the vibrational theory. | |||
TO cite this article:Gao-Feng Gu,Wei Chen,Wei-Xing Zhou. Empirical distributions of Chinese stock returns at different microscopic timescales[OL].[28 August 2007] http://en.paper.edu.cn/en_releasepaper/content/14737 |
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