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| 1 | Return and Volatility Spillovers Effects:Study of Asian Emerging Stock Markets显示文摘This paper examines the extent of contagion and interdependence across the six Asian emerging countries stock markets(e.g., Bangladesh, China, India, Malaysia, the Philippine, and South Korea) and then try to quantify the extent of the Asian emerging market fluctuations which are described by intra-regional contagion effect. These markets experienced both fast growth and key upheaval during the sample period, and thus, provide potentially rich information on the nature of border market interactions. Using the daily stock market index data from January 2002 to December 2016(breaking the 15 years data set into three sub periods; pre-crisis, crisis, and post crisis periods);particularly make attention to the global financial crisis of 2007~2008. The return and volatility spillovers are modeled through the GARCH(generalized autoregressive conditional heteroscedasticity),pairwise Granger causality tests, and the forecast error variance decomposition in a generalized VAR(vector auto regression) models. This paper shows that volatility and return spillovers behave very differently over time, during the pre-crisis, crisis, and post crisis periods. Importantly, Asian emerging stock markets interaction is less before the global financial crisis period. The return and volatility spillover indices touch their respective historical peaks during the global financial crisis 2007~2008,however Bangladeshi market faces this condition in 2009~2010. | Bhowmik RONI Ghulam ABBAS Shouyang WANG | 2018 | Journal of Systems Science and Information2018，9，2： | 6 |
| 2 | Quantitative method for evaluating detailed volatility of wind power at multiple temporal-spatial scales显示文摘With the increasing proportion of wind power integration, the volatility of wind power brings huge challenges to the safe and stable operation of the electric power system. At present, the indexes commonly used to evaluate the volatility of wind power only consider its overall characteristics, such as the standard deviation of wind power, the average of power variables, etc., while ignoring the detailed volatility of wind power, that is, the features of the frequency distribution of power variables. However, how to accurately describe the detailed volatility of wind power is the key foundation to reduce its adverse influences. To address this, a quantitative method for evaluating the detailed volatility of wind power at multiple temporal-spatial scales is proposed. First, the volatility indexes which can evaluate the detailed fluctuation characteristics of wind power are presented, including the upper confidence limit, lower confidence limit and confidence interval of power variables under the certain confidence level. Then, the actual wind power data from a location in northern China is used to illustrate the application of the proposed indexes at multiple temporal(year–season–month–day) and spatial scales(wind turbine–wind turbines–wind farm–wind farms) using the calculation time windows of 10 min, 30 min, 1 h, and 4 h. Finally, the relationships between wind power forecasting accuracy and its corresponding detailed volatility are analyzed to further verify the effectiveness of the proposed indexes. The results show that the proposed volatility indexes can effectively characterize the detailed fluctuations of wind power at multiple temporal-spatial scales. It is anticipated that the results of this study will serve as an important reference for the reserve capacity planning and optimization dispatch in the electric power system which with a high proportion of renewable energy. | Yongqian Liu Han Wang Shuang Han Jie Yan Li Li Zixin Chen | 2019 | Global Energy Interconnection2019，2，4： | 5 |
| 3 | Exchange Rate Volatility,Heterogeneous Firms and Market Concentration显示文摘With the gradual promotion of market-oriented reform of the RMB exchange rate,the fluctuation range of the RMB exchange rate is increasing.How to deal with the impact of exchange rate volatility on Chinese exports is an important challenge faced by China.This paper finds that although exchange rate volatility,as a whole,has a negative impact on exports,high-productivity exporters are less prone to exchange rate volatility shock in both intensive and extensive margins.As high-productivity firms are less affected by exchange rate risk,they account for larger market shares.This paper,from a new perspective,provides evidence that increasing productivity helps mitigate the negative impact of exchange volatility on exports. | Bing Lu Yaqi Wang Xiaofen Tan | 2020 | China & World Economy2020，28，4： | 3 |
| 4 | Investor sentiments and stock marketsduring the COVID-19 pandemic显示文摘This study examines the relationship between positive and negative investor sentiments and stock market returns and volatility in Group of 20 countries using variousmethods, including panel regression with fixed effects, panel quantile regressions, apanel vector autoregression (PVAR) model, and country-specific regressions. We proxyfor negative and positive investor sentiments using the Google Search Volume Indexfor terms related to the coronavirus disease (COVID-19) and COVID-19 vaccine, respectively. Using weekly data from March 2020 to May 2021, we document significantrelationships between positive and negative investor sentiments and stock marketreturns and volatility. Specifically, an increase in positive investor sentiment leads toan increase in stock returns while negative investor sentiment decreases stock returnsat lower quantiles. The effect of investor sentiment on volatility is consistent acrossthe distribution: negative sentiment increases volatility, whereas positive sentimentreduces volatility. These results are robust as they are corroborated by Granger causalitytests and a PVAR model. The findings may have portfolio implications as they indicatethat proxies for positive and negative investor sentiments seem to be good predictorsof stock returns and volatility during the pandemic. | Emre Cevik Buket Kirci Altinkeski Emrah Ismail Cevik Sel Dibooglu | 2022 | Financial Innovation2022，8，1： | 2 |
| 5 | Performance Volatility and Wage Elasticity:An Examination of Listed Chinese A-share Enterprises显示文摘The management of future financial risk on the part of managers and changes in firm finances are two of the fundamental reasons for upward and downward rigidity of wages.The proxy variable for firm financial risk is volatility,the past performance of which is among the principal indicators of wage rigidity.In firms whose current performance is on the upswing,the greater the volatility in past performance,the smaller the elasticity ratio and the more acute the upward rigidity;the more stable past performance,the larger the elasticity ratio and the more acute the upward elasticity.In firms in which current performance is declining,greater past performance volatility leads to a larger elasticity ratio and more acute downward rigidity,whereas more stable such performance leads to a smaller elasticity ratio and more acute downward rigidity. | Donghua Chen Yongjian Shen Lihua Chen | 2009 | China Journal of Accounting Research2009，，2： | 2 |
| 6 | Effect of occurrence mode of heavy metal elements in a low rank coal on volatility during pyrolysis显示文摘The harmful trace elements will be released during coal utilization, which can cause environment pollution and further endangering human health, especially for heavy metal elements. Compared to combustion, the release of heavy metal elements during coal pyrolysis process, as a critical initial reaction stage of combustion, has not received sufficient attention. In the present paper, a low rank coal, from Xinjiang province in China, was pyrolyzed in a fixed bed reactor from room temperature, at atmospheric pressure, with the heating rate of 10 °C/min, and the final pyrolysis temperature was from 400 to 800℃ with the interval of 100℃. The volatility of heavy metal elements (including As, Hg, Cd and Pb) during pyrolysis process was investigated. The results showed the volatility of all heavy metal elements increased obviously with increasing temperature, and followed the sequence as Hg > Cd > As > Pb, which was mainly caused by their thermodynamic property and occurrence modes in coal. The occurrence modes of heavy metals were studied by sink-andfloat test and sequential chemical extraction procedure, and it can be found that the heavy metal elements were mainly in the organic and residual states (clay minerals) in the raw coal. And most of the organic heavy metals escaped during the pyrolysis process, the remaining elements were mainly in the residual state, and the elements in Fe-Mn state also tended to remain in the char. | Lingmei Zhou Hao Guo Xiaobing Wang Mo Chu Guanjun Zhang Ligang Zhang | 2019 | International Journal of Coal Science & Technology2019，6，2： | 2 |
| 7 | Characterization of Organic Aerosol at a Rural Site in the North China Plain Region:Sources,Volatility and Organonitrates显示文摘The North China Plain(NCP)is a region that experiences serious aerosol pollution.A number of studies have focused on aerosol pollution in urban areas in the NCP region;however,research on characterizing aerosols in rural NCP areas is comparatively limited.In this study,we deployed a TD-HR-AMS(thermodenuder high-resolution aerosol mass spectrometer)system at a rural site in the NCP region in summer 2013 to characterize the chemical compositions and volatility of submicron aerosols(PM_(1)).The average PM_(1)mass concentration was 51.2±48.0μg m^(−3) and organic aerosol(OA)contributed most(35.4%)to PM_(1).Positive matrix factorization(PMF)analysis of OA measurements identified four OA factors,including hydrocarbon-like OA(HOA,accounting for 18.4%),biomass burning OA(BBOA,29.4%),lessoxidized oxygenated OA(LO-OOA,30.8%)and more-oxidized oxygenated OA(MO-OOA,21.4%).The volatility sequence of the OA factors was HOA>BBOA>LO-OOA>MO-OOA,consistent with their oxygen-to-carbon(O:C)ratios.Additionally,the mean concentration of organonitrates(ON)was 1.48−3.39μg m−3,contributing 8.1%-19%of OA based on cross validation of two estimation methods with the high-resolution time-of-flight aerosol mass spectrometer(HRToF-AMS)measurement.Correlation analysis shows that ON were more correlated with BBOA and black carbon emitted from biomass burning but poorly correlated with LO-OOA.Also,volatility analysis for ON further confirmed that particulate ON formation might be closely associated with primary emissions in rural NCP areas. | Qiao ZHU Li-Ming CAO Meng-Xue TANG Xiao-Feng HUANG Eri SAIKAWA Ling-Yan HE | 2021 | Advances in Atmospheric Sciences2021，38，7： | 2 |
| 8 | On the volatility of daily stock returns of Total Nigeria Plc: evidence from GARCH models, value-at-risk and backtesting显示文摘This study investigates the volatility in daily stock returns for Total Nigeria Plc using nine variants of GARCH models:sGARCH,girGARCH,eGARCH,iGARCH,aGARCH,TGARCH,NGARCH,NAGARCH,and AVGARCH along with value at risk estimation and backtesting.We use daily data for Total Nigeria Plc returns for the period January 2,2001 to May 8,2017,and conclude that eGARCH and sGARCH perform better for normal innovations while NGARCH performs better for student t innovations.This investigation of the volatility,VaR,and backtesting of the daily stock price of Total Nigeria Plc is important as most previous studies covering the Nigerian stock market have not paid much attention to the application of backtesting as a primary approach.We found from the results of the estimations that the persistence of the GARCH models are stable except for few cases for which iGARCH and eGARCH were unstable.Additionally,for student t innovation,the sGARCH and girGARCH models failed to converge;the mean reverting number of days for returns differed from model to model.From the analysis of VaR and its backtesting,this study recommends shareholders and investors continue their business with Total Nigeria Plc because possible losses may be overcome in the future by improvements in stock prices.Furthermore,risk was reflected by significant up and down movement in the stock price at a 99%confidence level,suggesting that high risk brings a high return. | Ngozi G.Emenogu Monday Osagie Adenomon Nwaze Obini Nweze | 2020 | Financial Innovation2020，6，1： | 2 |
| 9 | Modeling and forecasting exchange rate volatility in Bangladesh using GARCH models:a comparison based on normal and Student's t-error distribution显示文摘Background:Modeling exchange rate volatility has remained crucially important because of its diverse implications.This study aimed to address the issue of error distribution assumption in modeling and forecasting exchange rate volatility between the Bangladeshi taka(BDT)and the US dollar($).Methods:Using daily exchange rates for 7 years(January 1,2008,to April 30,2015),this study attempted to model dynamics following generalized autoregressive conditional heteroscedastic(GARCH),asymmetric power ARCH(APARCH),exponential generalized autoregressive conditional heteroscedstic(EGARCH),threshold generalized autoregressive conditional heteroscedstic(TGARCH),and integrated generalized autoregressive conditional heteroscedstic(IGARCH)processes under both normal and Student’s t-distribution assumptions for errors.Results and Conclusions:It was found that,in contrast with the normal distribution,the application of Student’s t-distribution for errors helped the models satisfy the diagnostic tests and show improved forecasting accuracy.With such error distribution for out-of-sample volatility forecasting,AR(2)–GARCH(1,1)is considered the best. | S.M.Abdullah Salina Siddiqua Muhammad Shahadat Hossain Siddiquee Nazmul Hossain | 2017 | Financial Innovation2017，3，1： | 2 |
| 10 | Return and Volatility Connectedness between Stock Markets and Macroeconomic Factors in the G-7 Countries显示文摘We examine the relationship between return and volatility of the stock markets and macroeconomic fundamentals for the G-7 countries by using monthly data ranging from July 1985 to June 2015. To meet this end, we apply the spillover index approach based on the generalized VAR framework developed by Diebold and Yilmaz (2012, 2014). The empirical analysis shows strong interactions between the returns and volatilities of the G-7 stock markets and the considered set of corresponding macroeconomic factors including industrial production, money supply, interest rates, inflation, oil prices and exchange rates. The return and volatility spillover transmission/reception dynamics of the relationships between these stock markets and the macroeconomic fundamentals have changed after the global financial crisis of 2008. Our findings provide useful insights for investors and policy makers concerned with the unprecedented swings in the stock markets of G-7 countries. | Ghulam Abbas Shawkat Hammoudeh Syed Jawad Hussain Shahzad Shouyang Wang Yunjie Wei | 2019 | Journal of Systems Science and Systems Engineering2019，28，1： | 2 |
| 11 | Forecasting volatility in oil prices with a class of nonlinear volatility models:smooth transition RBF and MLP neural networks augmented GARCH approach显示文摘In this study, the forecasting capabilities of a new class of nonlinear econometric models, namely, the LSTAR-LST-GARCH-RBF and MLP models are evaluated. The models are utilized to model and to forecast the daily returns of crude oil prices. Many financial time series are subjected to leptokurtic distribution, heavy tails, and nonlinear conditional volatility. This characteristic feature leads to deterioration in the forecast capabilities of traditional models such as the ARCH and GARCH models.According to the empirical findings, the oil prices and their daily returns could be classified as possessing nonlinearity in the conditional mean and conditional variance processes.Several model groups are evaluated:(i) the models proposed in the first group are the LSTAR-LST-GARCH models that are augmented with fractional integration and asymmetric power terms(FIGARCH, APGARCH, and FIAPGARCH);(ii) the models proposed in the second group are the LSTAR-LST-GARCH models further augmented with MLP and RBF type neural networks. The models are compared in terms of MSE, RMSE, and MAE criteria for in-sample and out-of-sample forecast capabilities. The results show that the LSTAR based and neural network augmented models provide important gains over the single-regime baseline GARCH models, followed by the LSTAR-LST-GARCH type models in terms of modeling and forecasting volatility in crude oil prices. | Melike Bildirici zgÖrü Ersin | 2015 | Petroleum Science2015，12，3： | 1 |
| 12 | High-Frequency Trading:Deception and Consequences显示文摘This commentary is based on the work of Cooper,Davis,and Van Vliet(2016)and the commentary focuses on what problem high-frequency trading poses.It lists key literature on high-frequency trading that is missing and points out that the poker analogy to defend deception in financial markets is weak and misleading.The article elaborates on the negative impact created by spoofing and quote stuffing,the two typical deceptive practices used by high-frequency traders.The recent regulations regarding high-frequency trading,in response to the“Flash Crash”of 2010,are preventive,computerized and more effective.They reflect ethical requirements to maintain fair and stable financial markets. | Viktoria Dalko Michael H.Wang | 2018 | Journal of Modern Accounting and Auditing2018，14，5： | 1 |
| 13 | Windows系统环境下基于内存分析的木马病毒取证显示文摘木马病毒是网络犯罪的重要载体,动态内存取证分析研究能够确定木马病毒在计算机的位置、木马运行时的DLL、木马对注册表和系统的改变情况,从而实现木马病毒攻击的证据固定。笔者在Windows系统虚拟环境下开展仿真实验,利用木马病毒对目标计算机进行模拟攻击,使用占用内存最小的DumpIt取证软件对内存在线提取数据,并使用volatility分析内存中的注册表、进程等,对木马攻击行为进行分析研究。实验结果表明,通过内存数据分析能够获取木马病毒进程位置、通信端口、功能等信息。本文还将内存分析数据与注册表文件进行对比分析,进一步实现了木马病毒攻击计算机的线索发现或证据固定。 | 郑文庚 李凌崴 廖广军 | 2020 | 刑事技术2020，45，6： | 1 |
| 14 | Price Discovery Function of Agricultural Futures Market in China--Based on VECM-PT-IS and DCC-MGARCH-t models显示文摘Agricultural futures market plays an important role in financial system,and its function of price discovery and hedging is of great significance to the long-term price stability for agricultural products.However,in China,agricultural futures market is still in construction stage,and scholars have not fully studied its price discovery function.Hence,this study will investigate the price discovery function of China agricultural futures market.The causal relationship,price contribution degree and volatility spillover effect of futures and spot markets are studied by comparing the price discovery function of soybean,yellow corn and soybean oil futures and spot.Taking the average daily settlement price of futures and spot in Dalian Commodity Exchange as study objects,the VECM and PT-IS model is used to investigate the causal relationship and the difference in price contribution between them.Then DDC-MGARCH-t model is used to analyze their volatility spillover effect.The empirical results show that there is obvious mutual guiding relationship between agricultural futures and spot market,and the price contribution of futures is significantly higher than that of spot,proving that agricultural futures have the function of price discovery.Meanwhile,the volatility spillover effect between agricultural futures and spot is bidirectional.The impact of internal fluctuations is often greater than that of external shocks. | Yangkai Guo | 2018 | 经济管理学刊(中英文版)2018，7，2： | 1 |
| 15 | Forecasting China′s Stock Market Volatility Using Non-Linear GARCH Models | WEI Wei\|xian Institute of Finance, Xiamen University, Xiamen 361005,China | 2000 | Systems Science and Systems Engineering2000，10，4： | 1 |
| 16 | 基于Volatility的内存信息调查方法研究显示文摘随着反取证技术的发展,调查人员越来越难于在磁盘介质中寻找到有价值的证据或线索。针对内存信息的调查分析研究由此成为计算机法庭科学领域日益关注的焦点。通过以内存调查取证开源软件Volatility为背景,从进程及DLL、内存及VAD、驱动程序及内核对象、网络连接与注册表等多个角度描述内存信息的调查方法,并结合实例说明所述方法在实际工作中的具体应用。 | 罗文华 汤艳君 | 2012 | 中国司法鉴定2012，，4： | 1 |
| 17 | Investors Thinking and Stock Price Excess Volatility | LI Honggang(Department of Systems Science, Beijing Normal University, Beijing 100875, China) | 1999 | Systems Science and Systems Engineering1999，9，1： | 0 |
| 18 | Long memory and nonlinear dependence structure in crude oil futures returns and volatility显示文摘In order to investigate the nature of international crude oil futures and present evidence of long memory and nonlinear dependence for crude oil futures volatility as well as returns, a certain number of recent statistical tests, such as the powerful BDS test, the fractional integration test and other known statistics, are applied. The results show that though the returns themselves contain little serial correlation, the market volatility series have significant long-term dependence structures which may have important implications for volatility forecasts and derivative pricing. On the other hand, evidence of strong ARCH effect is also presented, and, moreover, the BDS statistics on the standardized residuals of the fitted GARCH model indicate that the ARCH-type process may generally explain the nonlinearities in the data. It seems that the crude oil futures market can be appropriately modeled by ARCH and fractal processes. These findings indicate that it would be beneficial to assess the behavior of the crude oil and price the oil derivative contracts by encompassing long memory and nonlinear structure. | Li, Hongquan Wang, Shouyang Ma, Chaoqun | 2008 | Journal of Southeast University(English Edition)2008，24，S1： | 0 |
| 19 | Direct Determination of Trace Silicon in Lanthanum Oxide by Using a Selective Volatility and Slurry Sampling-FETV-ICP-AES显示文摘DirectDeterminationofTraceSiliconinLanthanumOxidebyUsingaSelectiveVolatilityandSlurrySampling┐FETV┐ICP┐AESQinYongchao,PengTi... | Qin Yongchao, Peng Tianyou, Jiang Zucheng ** , Zeng Yun′e Department of Chemistry, Wuhan University, Wuhan 430072, China | 1997 | Wuhan University Journal of Natural Sciences1997，2，1： | 0 |
| 20 | Market reactions to trade friction between China and the United States:Evidence from the soybean futures market显示文摘In March 2018,the US used an immense trade deficit as an excuse to provoke trade friction with China.This study uses the EGARCH model and event study methods to study the impact of the major risk event of Sino-US trade friction on soybean futures markets in China and the United States.Results indicate that the Sino-US trade friction weakened the return spillover effect between the soybean futures markets in China and the US,and significantly increased market volatilities.As the scale of additional tariffs increased,the volatility of the Chinese soybean futures market declined;however,the volatility of the US soybean futures market did not weaken.In addition,expanding the sources of soybean imports helped ease the impact of tariffs on China's soybean futures market,while the decline in US soybean exports to China intensified the volatility of the US soybean futures market.In addition,while the release of multiple tariff increases has had a short-termimpact on the returns of soybean futures markets,the impact of trade friction has grad-ually decreased. | Tian Wen Ping Li Lei Chen Yunbi An | 2023 | Journal of Management Science and Engineering2023，8，3： | 0 |
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