Using VAR-DCC-GARCH model,the literature on commodity price was extended by exploring the co-movement between Chinese nonferrous metal prices and global nonferrous metal prices represented by the nonferrous metal pric...Using VAR-DCC-GARCH model,the literature on commodity price was extended by exploring the co-movement between Chinese nonferrous metal prices and global nonferrous metal prices represented by the nonferrous metal prices from London Metal Exchange(LME).The results show that LME nonferrous metals prices still have a greater impact on Chinese nonferrous metals prices.However,the impact of Chinese nonferrous metals prices on LME nonferrous metals prices is still weak except for lead price.The co-movement of nonferrous metal prices between LME and China presents hysteretic nature,and it lasts for 7-8trading days.Furthermore,the co-movement between LME nonferrous metals prices and Chinese nonferrous metals prices has the characteristics of time-varying,and the correlation of lead prices between LME and China is the more stable than all other nonferrous metals prices.展开更多
GARCH-M ( generalized autoregressive conditional heteroskedasticity in the mean) model is used to analyse the volatility clustering phenomenon in mobile communication network traffic. Normal distribution, t distributi...GARCH-M ( generalized autoregressive conditional heteroskedasticity in the mean) model is used to analyse the volatility clustering phenomenon in mobile communication network traffic. Normal distribution, t distribution and generalized Pareto distribution assumptions are adopted re- spectively to simulate the random component in the model. The demonstration of the quantile of network traffic series indicates that common GARCH-M model can partially deal with the "fat tail" problem. However, the "fat tail" characteristic of the random component directly affects the accura- cy of the calculation. Even t distribution is based on the assumption for all the data. On the other hand, extreme value theory, which only concentrates on the tail distribution, can provide more ac- curate result for high quantiles. The best result is obtained based on the generalized Pareto distribu- tion assumption for the random component in the GARCH-M model.展开更多
Based on the text of posing on the network forum, the authors establish a set of keyword dictionary to measure the long and short investors' sentiment effectively, then they investigate the mutual relations between i...Based on the text of posing on the network forum, the authors establish a set of keyword dictionary to measure the long and short investors' sentiment effectively, then they investigate the mutual relations between investor sentiment and the trading market through a Multivariable BEKK-GARCH model of abnormal long and short investor sentiment, returns, and abnormal trading volume. The results show that abnormal sentiment of long investor has a negative impact on the returns and a positive impact on the abnormal trading volume; while abnormal sentiment of short investor has no impact on the return and a negative impact on the abnormal trading volume. Otherwise, there is the negative volatility effect from abnormal sentiment of long investor to returns and abnormal trading volume, the positive volatility effects from abnormal sentiment of short investor to returns, and no volatility effects from abnormal sentiment of short investor to abnormal trading volume. In addition, network forum investor sentiment is a factor affecting the trading market. The analysis of forum information plays a certain role in presenting market risk and improving efficiency in making investment decision.展开更多
By using GARCH(1,1)-M and EGARCH(1,1)-M models, the relationships among funds speculation transaction, arbitrage transaction and the fluctuation of international copper future price were studied. The news impact c...By using GARCH(1,1)-M and EGARCH(1,1)-M models, the relationships among funds speculation transaction, arbitrage transaction and the fluctuation of international copper future price were studied. The news impact curve of copper future price fluctuation respectively introduced funds speculation position and arbitrage position was given, and the result is consistent with the empirical study conclusion. The results show that investment funds are not the factor that causes copper future price fluctuation, but can reduce the copper future price fluctuation; the copper future price fluctuation is more sensitive to negative information, and ftmd speculative positions can reduce asymmetric effect of copper price fluctuation, while fimds arbitrage position influences less.展开更多
The GARCH and DCC-GARCH models are used to study the volatility aggregation and dynamic relevance of China’s three kinds of nonferrous metals (copper, aluminum and zinc) pricesincorporating structural changes. The ...The GARCH and DCC-GARCH models are used to study the volatility aggregation and dynamic relevance of China’s three kinds of nonferrous metals (copper, aluminum and zinc) pricesincorporating structural changes. The results show that copper, aluminum and zinc returns have many structure breaks points, and nonferrous metals have the greatvolatilityrisk during financial crisis. From the resultsof GARCH with and without structural changes,it isfoundthat the volatility clustering of single nonferrous metal is overvalued when ignoring the structural mutation, and the return of aluminum isthe most overvalued, indicating that aluminum market is more susceptible to external shock.Furthermore,it is also foundthatdynamic volatility correlation exists in the three prices of nonferrous metals, and the structural changes have no significant effect on the volatility correlation of thethree nonferrous metals.展开更多
The correlation between Renminbi(RMB) internationalization and nonferrous metal prices was studied using the nonlinear Granger causality test and the dynamic conditional correlation-generalized autoregressive conditio...The correlation between Renminbi(RMB) internationalization and nonferrous metal prices was studied using the nonlinear Granger causality test and the dynamic conditional correlation-generalized autoregressive conditional heteroskedastic(DCC-GARCH) model. The results indicate that the relationship between RMB internationalization and nonferrous metal prices reflects a complex nonlinear mechanism. There was no mutual influence between RMB internationalization and nonferrous metal prices prior to the trials of the RMB settlement in the cross-border trade in July 2009. Since then, however, a bidirectional causal relationship between RMB internationalization and the price of copper and a unidirectional causal relationship from the price of aluminum to RMB internationalization were examined. In addition, due to the impact of extreme events, such as economic and financial crises, RMB internationalization and nonferrous metal prices are not always positively correlated but are rather occasionally negatively correlated.展开更多
Natural ventilation is driven by either buoyancy forces or wind pressure forces or their combinations that inherit stochastic variation into ventilation rates. Since the ventilation rate is a nonlinear function of mul...Natural ventilation is driven by either buoyancy forces or wind pressure forces or their combinations that inherit stochastic variation into ventilation rates. Since the ventilation rate is a nonlinear function of multiple variable factors including wind speed, wind direction, internal heat source and building structural thermal mass, the conventional methods for quantifying ventilation rate simply using dominant wind direction and average wind speed may not accurately describe the characteristic performance of natural ventilation. From a new point of view, the natural ventilation performance of a single room building under fluctuating wind speed condition using the Monte-Carlo simulation approach was investigated by incorporating building facade thermal mass effect. Given a same hourly turbulence intensity distribution, the wind speeds with 1 rain frequency fluctuations were generated using a stochastic model, the modified GARCH model. Comparisons of natural ventilation profiles, effective ventilation rates, and air conditioning electricity use for a three-month period show statistically significant differences (for 80% confidence interval) between the new calculations and the traditional methods based on hourly average wind speed.展开更多
This paper discusses the model construction and the association between the Italy and the Germany's stock markets. The period of study data is from January 3, 2000 to June 30, 2008. This paper also utilizes Student'...This paper discusses the model construction and the association between the Italy and the Germany's stock markets. The period of study data is from January 3, 2000 to June 30, 2008. This paper also utilizes Student's t distribution to analyze the proposed model. The empirical results show that the two stock markets are mutually affected each other, and the dynamic conditional correlation (DCC) and the bivariate asymmetric-GARCH (1, 2) model is appropriate in evaluating the relation between them. The empirical result also indicates that Italy and Germany's stock markets show a positive relationship. The average value of correlation coefficient equals to 0.8424, which implies that the two stock markets return volatility have a synchronized influence on each other. In addition, the empirical result also shows that there is an asymmetrical effect between Italy and the Germany's stock markets, and demonstrates that the good news and bad news of the stock returns' volatility will produce the different variation risks for Italy and the Germany's stock price markets.展开更多
This study investigates the relationship between trading volume and returns in SET50 index Futures market in the period from April 2006 to December 2008 using 653 observations. From previous studies, we include three ...This study investigates the relationship between trading volume and returns in SET50 index Futures market in the period from April 2006 to December 2008 using 653 observations. From previous studies, we include three methodologies namely the GARCH model, the Generalized Method of Moments (GMM) to estimate systems of equations and the Granger causality test to investigate the relationship more thoroughly. In addition, we introduce the lagged volume as a new explanatory variable in the GARCH model. Overall, the results show the significant contemporaneous and dynamic relationships between trading volume and returns volatility which support the sequential information arrival hypothesis and imply some degree of market inefficiency. The results from this study also show that past information of trading volume can be used to improve the prediction of price volatility. Therefore, regulators and traders could include past information of trading volume of SET50 index futures in tracking and monitoring the market volatility level and the investment risk in order to make a timely decision.展开更多
In October 1996, The Dhaka Stock Exchange (DSE) adopted trading halts for individual stocks, collectively known as "circuit breakers", to reduce the stock market volatility. This paper reviews the existing circuit...In October 1996, The Dhaka Stock Exchange (DSE) adopted trading halts for individual stocks, collectively known as "circuit breakers", to reduce the stock market volatility. This paper reviews the existing circuit breakers literature and developed five hypothesis--"Magnet Effect", "Cool off-Heating (C-H) Effect", "Information Hypothesis", "Volatility Spillover Hypothesis" and "Trading Interferences Hypothesis"--which could be tested empirically not only in the Dhaka Stock Exchange but any stock exchanges around the world. This paper also suggests most appropriate econometric models for empirical testing. GARCH for inter day data and Event Study methodology for intra day data. Moreover, to test the robustness non-parametric tests need to use along with parametric one. Considering the stock market bubbles in 1996, it has been found that it was optimal for the regulators to adopt this trading halt, but not for the market. It failed to protect the market. However, this might be the consequences of misconceptions about the purpose and effectiveness of circuit breakers. Despite many arguments contrary to this mechanism and absence of any conclusive empirical evidence for a fragile stock exchange like DSE, it may be useful sometimes to replace the "invisible hand of the marketplace" with the "visible hand of the market regulators".展开更多
This paper investigates the influence of exchange rate volatility on the volume of Japanese manufacturing export. The volatility in yen is shown by conditional variance from EGARCH (Exponential Generalized Autoregres...This paper investigates the influence of exchange rate volatility on the volume of Japanese manufacturing export. The volatility in yen is shown by conditional variance from EGARCH (Exponential Generalized Autoregressive Conditional Heteroscedasticity) model, allowing for asymmetric effects that a shock of an appreciation of the yen is different from that of a depreciation of the yen. The export action model including exchange rate volatility is constructed based on VAR (Vector Auto Regressive) model to examine the relationship between exchange rate uncertainty and the volume of export. Tests are performed for typical eight kinds of industry in Japan. Few empirical studies focus on each Japanese industry export. Results indicate significant negative effects of exchange rate volatility on most manufacturing exports. In addition, this paper analyzes the each industry, featurc of the influence of exchange rate on the volume of Japanese export. The authors find that equipment industries occupying 60% or more of total Japanese exports especially tend to receive negative influence of exchange.展开更多
the model in time series analysis are widely used in the field of economy. We often use the model in time series to analyze data, but without regard to the rationality of the model. In this paper, we introduce and ana...the model in time series analysis are widely used in the field of economy. We often use the model in time series to analyze data, but without regard to the rationality of the model. In this paper, we introduce and analyze Ping An Of China(601318) shares at the opening price(2013/01/04-2013/07/04).The model is established by analyzing data. Modeling steps of ARIMA model and GARCH model are presented in this paper. The data whether ARIMA model is suitable by white noise. Or the data whether GARCH model is suitable by since the correlation of variance test. By comparing the analysis, it selects a more reasonable model.展开更多
In this paper, the authors analyze the adequacy of GARCH-type models to analyze oil price behavior by applying two types of non-parametric tests, the Hinich portmanteau test for non-linear dependence and a frequency-d...In this paper, the authors analyze the adequacy of GARCH-type models to analyze oil price behavior by applying two types of non-parametric tests, the Hinich portmanteau test for non-linear dependence and a frequency-dominant test of time reversibility, the reverse test based on the bispectrum, to explore the high-order spectrum properties of the Mexican oil price series. The results suggest strong evidence of a non-linear structure and time irreversibility. Therefore, it does not comply with the i.i.d (independent and identically distributed) property. The non-linear dependence, however, is not consistent throughout the sample period, as indicated by a windowed test, suggesting episodic nonlinear dependence. The results imply that GARCH models cannot capture the series structure.展开更多
Uncertainty analysis and risk analysis are two important areas of modern water resource management,in which accurate variance estimation is required.The traditional runoff model is established under the assumption tha...Uncertainty analysis and risk analysis are two important areas of modern water resource management,in which accurate variance estimation is required.The traditional runoff model is established under the assumption that the variance is a constant or it changes with the seasons.However,hydrological processes in the real world are often heteroscedastic,which can be tested by McLeod-Li test and Engle Lagrange multiplier test.In such cases,the GARCH model of hydrological processes is established in this article.First,the seasonal factors in the sequence are removed.Second,the traditional ARMA model is established.Then,the GARCH model is used to correct the residual.At last,the daily runoff data in 1949-2001 of Yichang Hydrological Station is taken to be an example.The result shows that compared to the traditional ARMA model,the GARCH model has the ability to predict more accurate confidence intervals under the same confidence level.展开更多
This paper investigates the mean-reversion and volatile of credit spread time series by using regression and time series analysis in Chinese bond market. Then the Longstaff-Schwartz model and GARCH model are applied t...This paper investigates the mean-reversion and volatile of credit spread time series by using regression and time series analysis in Chinese bond market. Then the Longstaff-Schwartz model and GARCH model are applied to price credit spread put option. The authors compare the features of these two models by employing daily bond prices of government bonds and corporate bonds for the period 2010–2012 in Chinese bond market. The proposed results show that the higher the credit ratings of the corporate bonds are, the lower the prices of the credit spread options are.展开更多
The threshold GARCH(TGARCH)models have been very useful for analyzing asymmetric volatilities arising from financial time series.Most research on TGARCH has been directed to the stationary case.This paper studies the ...The threshold GARCH(TGARCH)models have been very useful for analyzing asymmetric volatilities arising from financial time series.Most research on TGARCH has been directed to the stationary case.This paper studies the estimation of non-stationary first order TGARCH models.Restricted normal mixture quasi-maximum likelihood estimation(NM-QMLE)for non-stationary TGARCH models is proposed in the sense that we estimate the other parameters with any fixed location parameter.We show that the proposed estimators(except location parameter)are consistent and asymptotically normal under mild regular conditions.The impact of relative leptokursis and skewness of the innovations’distribution and quasi-likelihood distributions on the asymptotic efficiency has been discussed.Numerical results lend further support to our theoretical results.Finally,an illustrated real example is presented.展开更多
The GARCH diffusion model has received much attention in recent years, as it describes financial time series better when compared to many other models. In this paper, the authors study the empirical performance of Ame...The GARCH diffusion model has received much attention in recent years, as it describes financial time series better when compared to many other models. In this paper, the authors study the empirical performance of American option pricing model when the underlying asset follows the GARCH diffusion. The parameters of the GARCH diffusion model are estimated by the efficient importance sampling-based maximum likelihood (EIS-ML) method. Then the least-squares Monte Carlo (LSMC) method is introduced to price American options. Empirical pricing results on American put options in Hong Kong stock market shows that the GARCH diffusion model outperforms the classical constant volatility (CV) model significantly.展开更多
We consider the periodic generalized autoregressive conditional heteroskedasticity(P-GARCH) process and propose a robust estimator by composite quantile regression. We study some useful properties about the P-GARCH mo...We consider the periodic generalized autoregressive conditional heteroskedasticity(P-GARCH) process and propose a robust estimator by composite quantile regression. We study some useful properties about the P-GARCH model. Under some mild conditions, we establish the asymptotic results of proposed estimator.The Monte Carlo simulation is presented to assess the performance of proposed estimator. Numerical study results show that our proposed estimation outperforms other existing methods for heavy tailed distributions.The proposed methodology is also illustrated by Va R on stock price data.展开更多
基金Project(71073177)supported by the National Natural Science Foundation of ChinaProject(12JJ4077)supported by the Natural Science Foundation of Hunan Province of ChinaProject(2012zzts002)supported by the Fundamental Research Funds of Central South University,China
文摘Using VAR-DCC-GARCH model,the literature on commodity price was extended by exploring the co-movement between Chinese nonferrous metal prices and global nonferrous metal prices represented by the nonferrous metal prices from London Metal Exchange(LME).The results show that LME nonferrous metals prices still have a greater impact on Chinese nonferrous metals prices.However,the impact of Chinese nonferrous metals prices on LME nonferrous metals prices is still weak except for lead price.The co-movement of nonferrous metal prices between LME and China presents hysteretic nature,and it lasts for 7-8trading days.Furthermore,the co-movement between LME nonferrous metals prices and Chinese nonferrous metals prices has the characteristics of time-varying,and the correlation of lead prices between LME and China is the more stable than all other nonferrous metals prices.
基金Supported by University and College Doctoral Subject Special Scientific Research Fund( No. 20040056041).
文摘GARCH-M ( generalized autoregressive conditional heteroskedasticity in the mean) model is used to analyse the volatility clustering phenomenon in mobile communication network traffic. Normal distribution, t distribution and generalized Pareto distribution assumptions are adopted re- spectively to simulate the random component in the model. The demonstration of the quantile of network traffic series indicates that common GARCH-M model can partially deal with the "fat tail" problem. However, the "fat tail" characteristic of the random component directly affects the accura- cy of the calculation. Even t distribution is based on the assumption for all the data. On the other hand, extreme value theory, which only concentrates on the tail distribution, can provide more ac- curate result for high quantiles. The best result is obtained based on the generalized Pareto distribu- tion assumption for the random component in the GARCH-M model.
文摘Based on the text of posing on the network forum, the authors establish a set of keyword dictionary to measure the long and short investors' sentiment effectively, then they investigate the mutual relations between investor sentiment and the trading market through a Multivariable BEKK-GARCH model of abnormal long and short investor sentiment, returns, and abnormal trading volume. The results show that abnormal sentiment of long investor has a negative impact on the returns and a positive impact on the abnormal trading volume; while abnormal sentiment of short investor has no impact on the return and a negative impact on the abnormal trading volume. Otherwise, there is the negative volatility effect from abnormal sentiment of long investor to returns and abnormal trading volume, the positive volatility effects from abnormal sentiment of short investor to returns, and no volatility effects from abnormal sentiment of short investor to abnormal trading volume. In addition, network forum investor sentiment is a factor affecting the trading market. The analysis of forum information plays a certain role in presenting market risk and improving efficiency in making investment decision.
基金Project(20090162120086) supported by Research Fund for the Doctoral Program of Higher Education of ChinaProject(10YJCZH123) supported by Humanity and Social Science Foundation of Ministry of Education of China+2 种基金Project(12JJ4077) supported by the National Natural Science Foundation of Hunan Province of ChinaProject(2009ZK3053) supported by Soft Science Research Project of Hunan Province of ChinaProject supported by the Freedom Explore Program of Central South University,China
文摘By using GARCH(1,1)-M and EGARCH(1,1)-M models, the relationships among funds speculation transaction, arbitrage transaction and the fluctuation of international copper future price were studied. The news impact curve of copper future price fluctuation respectively introduced funds speculation position and arbitrage position was given, and the result is consistent with the empirical study conclusion. The results show that investment funds are not the factor that causes copper future price fluctuation, but can reduce the copper future price fluctuation; the copper future price fluctuation is more sensitive to negative information, and ftmd speculative positions can reduce asymmetric effect of copper price fluctuation, while fimds arbitrage position influences less.
基金Project(71072079)supported by the National Natural Science Foundation of China
文摘The GARCH and DCC-GARCH models are used to study the volatility aggregation and dynamic relevance of China’s three kinds of nonferrous metals (copper, aluminum and zinc) pricesincorporating structural changes. The results show that copper, aluminum and zinc returns have many structure breaks points, and nonferrous metals have the greatvolatilityrisk during financial crisis. From the resultsof GARCH with and without structural changes,it isfoundthat the volatility clustering of single nonferrous metal is overvalued when ignoring the structural mutation, and the return of aluminum isthe most overvalued, indicating that aluminum market is more susceptible to external shock.Furthermore,it is also foundthatdynamic volatility correlation exists in the three prices of nonferrous metals, and the structural changes have no significant effect on the volatility correlation of thethree nonferrous metals.
基金Projects(71874210,71633006,71874207,71974208)supported by the National Natural Science Foundation of ChinaProject(2020CX049)supported by Innovation-Driven Foundation of Central South University,China+1 种基金Project(2018dcyj031)supported by Postgraduate Survey Research Foundation of Central South University,ChinaProject(17K103)supported by the Innovation Platform Open Fund Project of Hunan Education Department,China。
文摘The correlation between Renminbi(RMB) internationalization and nonferrous metal prices was studied using the nonlinear Granger causality test and the dynamic conditional correlation-generalized autoregressive conditional heteroskedastic(DCC-GARCH) model. The results indicate that the relationship between RMB internationalization and nonferrous metal prices reflects a complex nonlinear mechanism. There was no mutual influence between RMB internationalization and nonferrous metal prices prior to the trials of the RMB settlement in the cross-border trade in July 2009. Since then, however, a bidirectional causal relationship between RMB internationalization and the price of copper and a unidirectional causal relationship from the price of aluminum to RMB internationalization were examined. In addition, due to the impact of extreme events, such as economic and financial crises, RMB internationalization and nonferrous metal prices are not always positively correlated but are rather occasionally negatively correlated.
文摘Natural ventilation is driven by either buoyancy forces or wind pressure forces or their combinations that inherit stochastic variation into ventilation rates. Since the ventilation rate is a nonlinear function of multiple variable factors including wind speed, wind direction, internal heat source and building structural thermal mass, the conventional methods for quantifying ventilation rate simply using dominant wind direction and average wind speed may not accurately describe the characteristic performance of natural ventilation. From a new point of view, the natural ventilation performance of a single room building under fluctuating wind speed condition using the Monte-Carlo simulation approach was investigated by incorporating building facade thermal mass effect. Given a same hourly turbulence intensity distribution, the wind speeds with 1 rain frequency fluctuations were generated using a stochastic model, the modified GARCH model. Comparisons of natural ventilation profiles, effective ventilation rates, and air conditioning electricity use for a three-month period show statistically significant differences (for 80% confidence interval) between the new calculations and the traditional methods based on hourly average wind speed.
文摘This paper discusses the model construction and the association between the Italy and the Germany's stock markets. The period of study data is from January 3, 2000 to June 30, 2008. This paper also utilizes Student's t distribution to analyze the proposed model. The empirical results show that the two stock markets are mutually affected each other, and the dynamic conditional correlation (DCC) and the bivariate asymmetric-GARCH (1, 2) model is appropriate in evaluating the relation between them. The empirical result also indicates that Italy and Germany's stock markets show a positive relationship. The average value of correlation coefficient equals to 0.8424, which implies that the two stock markets return volatility have a synchronized influence on each other. In addition, the empirical result also shows that there is an asymmetrical effect between Italy and the Germany's stock markets, and demonstrates that the good news and bad news of the stock returns' volatility will produce the different variation risks for Italy and the Germany's stock price markets.
文摘This study investigates the relationship between trading volume and returns in SET50 index Futures market in the period from April 2006 to December 2008 using 653 observations. From previous studies, we include three methodologies namely the GARCH model, the Generalized Method of Moments (GMM) to estimate systems of equations and the Granger causality test to investigate the relationship more thoroughly. In addition, we introduce the lagged volume as a new explanatory variable in the GARCH model. Overall, the results show the significant contemporaneous and dynamic relationships between trading volume and returns volatility which support the sequential information arrival hypothesis and imply some degree of market inefficiency. The results from this study also show that past information of trading volume can be used to improve the prediction of price volatility. Therefore, regulators and traders could include past information of trading volume of SET50 index futures in tracking and monitoring the market volatility level and the investment risk in order to make a timely decision.
文摘In October 1996, The Dhaka Stock Exchange (DSE) adopted trading halts for individual stocks, collectively known as "circuit breakers", to reduce the stock market volatility. This paper reviews the existing circuit breakers literature and developed five hypothesis--"Magnet Effect", "Cool off-Heating (C-H) Effect", "Information Hypothesis", "Volatility Spillover Hypothesis" and "Trading Interferences Hypothesis"--which could be tested empirically not only in the Dhaka Stock Exchange but any stock exchanges around the world. This paper also suggests most appropriate econometric models for empirical testing. GARCH for inter day data and Event Study methodology for intra day data. Moreover, to test the robustness non-parametric tests need to use along with parametric one. Considering the stock market bubbles in 1996, it has been found that it was optimal for the regulators to adopt this trading halt, but not for the market. It failed to protect the market. However, this might be the consequences of misconceptions about the purpose and effectiveness of circuit breakers. Despite many arguments contrary to this mechanism and absence of any conclusive empirical evidence for a fragile stock exchange like DSE, it may be useful sometimes to replace the "invisible hand of the marketplace" with the "visible hand of the market regulators".
文摘This paper investigates the influence of exchange rate volatility on the volume of Japanese manufacturing export. The volatility in yen is shown by conditional variance from EGARCH (Exponential Generalized Autoregressive Conditional Heteroscedasticity) model, allowing for asymmetric effects that a shock of an appreciation of the yen is different from that of a depreciation of the yen. The export action model including exchange rate volatility is constructed based on VAR (Vector Auto Regressive) model to examine the relationship between exchange rate uncertainty and the volume of export. Tests are performed for typical eight kinds of industry in Japan. Few empirical studies focus on each Japanese industry export. Results indicate significant negative effects of exchange rate volatility on most manufacturing exports. In addition, this paper analyzes the each industry, featurc of the influence of exchange rate on the volume of Japanese export. The authors find that equipment industries occupying 60% or more of total Japanese exports especially tend to receive negative influence of exchange.
文摘the model in time series analysis are widely used in the field of economy. We often use the model in time series to analyze data, but without regard to the rationality of the model. In this paper, we introduce and analyze Ping An Of China(601318) shares at the opening price(2013/01/04-2013/07/04).The model is established by analyzing data. Modeling steps of ARIMA model and GARCH model are presented in this paper. The data whether ARIMA model is suitable by white noise. Or the data whether GARCH model is suitable by since the correlation of variance test. By comparing the analysis, it selects a more reasonable model.
文摘In this paper, the authors analyze the adequacy of GARCH-type models to analyze oil price behavior by applying two types of non-parametric tests, the Hinich portmanteau test for non-linear dependence and a frequency-dominant test of time reversibility, the reverse test based on the bispectrum, to explore the high-order spectrum properties of the Mexican oil price series. The results suggest strong evidence of a non-linear structure and time irreversibility. Therefore, it does not comply with the i.i.d (independent and identically distributed) property. The non-linear dependence, however, is not consistent throughout the sample period, as indicated by a windowed test, suggesting episodic nonlinear dependence. The results imply that GARCH models cannot capture the series structure.
基金supported by the National Hi-Tech Research and Development Program of China ("863" Project) (Grant No. 2012BAB02B04)
文摘Uncertainty analysis and risk analysis are two important areas of modern water resource management,in which accurate variance estimation is required.The traditional runoff model is established under the assumption that the variance is a constant or it changes with the seasons.However,hydrological processes in the real world are often heteroscedastic,which can be tested by McLeod-Li test and Engle Lagrange multiplier test.In such cases,the GARCH model of hydrological processes is established in this article.First,the seasonal factors in the sequence are removed.Second,the traditional ARMA model is established.Then,the GARCH model is used to correct the residual.At last,the daily runoff data in 1949-2001 of Yichang Hydrological Station is taken to be an example.The result shows that compared to the traditional ARMA model,the GARCH model has the ability to predict more accurate confidence intervals under the same confidence level.
基金supported by the National Natural Science Foundation of China under Grant Nos.71171012and 70901019Humanity and Social Science Foundation of Ministry of Education of China under Grant No.14YJA790075
文摘This paper investigates the mean-reversion and volatile of credit spread time series by using regression and time series analysis in Chinese bond market. Then the Longstaff-Schwartz model and GARCH model are applied to price credit spread put option. The authors compare the features of these two models by employing daily bond prices of government bonds and corporate bonds for the period 2010–2012 in Chinese bond market. The proposed results show that the higher the credit ratings of the corporate bonds are, the lower the prices of the credit spread options are.
基金supported by National Natural Science Foundation of China (Grant No.11101448)the Program for New Century Excellent Talents in University+3 种基金the Program for Young Talents of Beijing (Grant No.YETP0955)the Program for National Statistics Science Research Plan (Grant No.2013LY015)the "Project 211" of the Central University of Finance and Economicsthe Central University of Finance Young Scholar Innovation Fund
文摘The threshold GARCH(TGARCH)models have been very useful for analyzing asymmetric volatilities arising from financial time series.Most research on TGARCH has been directed to the stationary case.This paper studies the estimation of non-stationary first order TGARCH models.Restricted normal mixture quasi-maximum likelihood estimation(NM-QMLE)for non-stationary TGARCH models is proposed in the sense that we estimate the other parameters with any fixed location parameter.We show that the proposed estimators(except location parameter)are consistent and asymptotically normal under mild regular conditions.The impact of relative leptokursis and skewness of the innovations’distribution and quasi-likelihood distributions on the asymptotic efficiency has been discussed.Numerical results lend further support to our theoretical results.Finally,an illustrated real example is presented.
基金supported by the National Natural Science Foundations of China under Grant No.71201013the National Science Fund for Distinguished Young Scholars of China under Grant No.70825006+1 种基金the Program for Changjiang Scholars and Innovative Research Team in University under Grant No.IRT0916the National Natural Science Innovation Research Group of China under Grant No.71221001
文摘The GARCH diffusion model has received much attention in recent years, as it describes financial time series better when compared to many other models. In this paper, the authors study the empirical performance of American option pricing model when the underlying asset follows the GARCH diffusion. The parameters of the GARCH diffusion model are estimated by the efficient importance sampling-based maximum likelihood (EIS-ML) method. Then the least-squares Monte Carlo (LSMC) method is introduced to price American options. Empirical pricing results on American put options in Hong Kong stock market shows that the GARCH diffusion model outperforms the classical constant volatility (CV) model significantly.
基金supported by National Natural Science Foundation of China(Grant No.11371354)Key Laboratory of Random Complex Structures and Data Science+2 种基金Chinese Academy of Sciences(Grant No.2008DP173182)National Center for Mathematics and Interdisciplinary SciencesChinese Academy of Sciences
文摘We consider the periodic generalized autoregressive conditional heteroskedasticity(P-GARCH) process and propose a robust estimator by composite quantile regression. We study some useful properties about the P-GARCH model. Under some mild conditions, we establish the asymptotic results of proposed estimator.The Monte Carlo simulation is presented to assess the performance of proposed estimator. Numerical study results show that our proposed estimation outperforms other existing methods for heavy tailed distributions.The proposed methodology is also illustrated by Va R on stock price data.