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Yingying Xu
School of Economics and Management University of Science and Technology Beijing Beijing China

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Research article
Published: 12 August 2021 in Journal of Forecasting
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This paper compares Generalized Autoregressive Score (GAS) models and GARCH-type models on their forecasting abilities for crude oil and natural gas spot and futures returns from developing and developed markets over multiple horizons. The out-of-sample forecasting results based on two loss functions and the Diebold–Mariano predictive accuracy test for multiple models show that the GAS framework outperforms GARCH and EGARCH models, particularly for crude oil assets. For natural gas, no specific model retains an advantage over the other two models as the predictive accuracy changes over forecasting horizons and varies across markets. Meanwhile, the GAS model performs well in both developed and developing markets. The cumulated sum of squared forecast error differential (CSSFED) graphically monitors the evolution of the relative forecasting performance of different models and shows that the superiority of GARCH is vulnerable to extraordinary event shocks. Over the short-term forecasting (less than or equal to 1 month ahead), the GAS framework shows a prominent advantage over GARCH and EGARCH models for crude oil assets.

ACS Style

Yingying Xu; Donald Lien. Forecasting volatilities of oil and gas assets: A comparison of GAS, GARCH, and EGARCH models. Journal of Forecasting 2021, 1 .

AMA Style

Yingying Xu, Donald Lien. Forecasting volatilities of oil and gas assets: A comparison of GAS, GARCH, and EGARCH models. Journal of Forecasting. 2021; ():1.

Chicago/Turabian Style

Yingying Xu; Donald Lien. 2021. "Forecasting volatilities of oil and gas assets: A comparison of GAS, GARCH, and EGARCH models." Journal of Forecasting , no. : 1.

Journal article
Published: 11 May 2021 in Finance Research Letters
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The COVID-19 has caused dramatic fluctuations in international financial markets. This paper tests the effect of this pandemic on foreign exchange dependences within the BRICS economies. Upon dividing the COVID-19 episode into four stages, we document negative effects of the COVID-19 on dependences between CNY and other currencies in the BRICS across different stages. In addition, USD flows positively affect the dependencies of BRL-CNY, INR-CNY, and RUB-CNY pairs in response to the transition of the pandemic stages.

ACS Style

Yingying Xu; Donald Lien. COVID-19 and currency dependences: Empirical evidence from BRICS. Finance Research Letters 2021, 102119 .

AMA Style

Yingying Xu, Donald Lien. COVID-19 and currency dependences: Empirical evidence from BRICS. Finance Research Letters. 2021; ():102119.

Chicago/Turabian Style

Yingying Xu; Donald Lien. 2021. "COVID-19 and currency dependences: Empirical evidence from BRICS." Finance Research Letters , no. : 102119.

Journal article
Published: 26 April 2021 in Pacific-Basin Finance Journal
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A thorough understanding of the risk spillover from energy market uncertainties to the Chinese carbon market is significant for risk management and the construction of a unified national carbon market in China. Based on the generalized autoregressive score-driving model, this paper measures China's domestic energy market uncertainty using the conditional volatility of Daqing crude oil returns. Through merging copula approach and CoVaR methods, this paper reveals asymmetric risk spillovers from the international and China's domestic energy market uncertainties to Hubei and Shenzhen carbon pilots, which are the most representative carbon markets in China. Although both the international and China's domestic energy market uncertainties exert significant risk spillover effects on Chinese carbon pilots, the magnitudes of their effects are different. Comparing two carbon pilots, the Shenzhen market is more affected by energy market uncertainties than the Hubei market, thus revealing differences between carbon pilots. The findings in this paper provide meaningful information on investment portfolios and policies for constructing a unified national carbon market.

ACS Style

Yingying Xu. Risk spillover from energy market uncertainties to the Chinese carbon market. Pacific-Basin Finance Journal 2021, 67, 101561 .

AMA Style

Yingying Xu. Risk spillover from energy market uncertainties to the Chinese carbon market. Pacific-Basin Finance Journal. 2021; 67 ():101561.

Chicago/Turabian Style

Yingying Xu. 2021. "Risk spillover from energy market uncertainties to the Chinese carbon market." Pacific-Basin Finance Journal 67, no. : 101561.

Journal article
Published: 23 April 2021 in Renewable and Sustainable Energy Reviews
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Emission Trading Scheme (ETS) is one of the most important instruments introduced to meet carbon neutral targets internationally. To reduce carbon emissions, China has established eight regional ETS since 2013 to reduce carbon emissions. However, significant heterogeneities exist across the eight pilots, resulting in distinctively different carbon price movements. Traded as a financial asset, carbon allowance is vulnerable to internal and external shocks. Though carbon prices have been fluctuating fiercely since the inception of the carbon market, little is known about potential carbon price bubbles in any of these pilots. To this end, this paper resorts to the generalized sup Augmented Dickey-Fuller (GSADF) test, which allows the detection of multiple bubbles, as well as the date stamping of bubbles in carbon prices. For the first time, price bubbles are found in the Chinese carbon markets. The empirical results find three bubbles in Guangdong pilot, two bubbles in Tianjin pilot, and one bubble in Hubei pilot. These explosive episodes are closely related to immature market mechanisms and policy implementations. The results provide insightful implications for the upcoming unified national carbon market.

ACS Style

Yingying Xu; Sultan Salem. Explosive behaviors in Chinese carbon markets: are there price bubbles in eight pilots? Renewable and Sustainable Energy Reviews 2021, 145, 111089 .

AMA Style

Yingying Xu, Sultan Salem. Explosive behaviors in Chinese carbon markets: are there price bubbles in eight pilots? Renewable and Sustainable Energy Reviews. 2021; 145 ():111089.

Chicago/Turabian Style

Yingying Xu; Sultan Salem. 2021. "Explosive behaviors in Chinese carbon markets: are there price bubbles in eight pilots?" Renewable and Sustainable Energy Reviews 145, no. : 111089.

Research article
Published: 04 February 2021 in Economic Research-Ekonomska Istraživanja
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The volume–volatility relationship usually ignores possible effects of stock shares. This article proposes a two-phase flow model assuming that capital and stock flows determine stock price and return volatility. Computational simulations suggest that monodirectional capital or stock flows and collective flows exert different effects on stock return volatilities. Considering the impact of stock flows, the positive relationship between capital and return volatility is no longer guaranteed. The inflow of capital and the outflow of stock increase stock price similarly; but exhibit completely different effects on stock return volatilities. A persistent stock inflow (outflow) reduces (intensifies) return volatilities, whereas a monodirectional persistent capital outflow has no such effect. When capital and stock flows’ velocities satisfy critical values determined by the initial state of the market, the market enlargement accompanied with increasing stock and capital shows no impact on market stability because of stable return volatilities. Otherwise, stock flows drive return volatilities with stronger effects than capital flows. Further experimental studies that simulate the real stock market through a trading system provide strong evidence supporting the two-phase flow model. Given similar driving forces of capital and stock flows, the interaction of them should be considered in constructing investment strategies and setting policies.

ACS Style

Limin Wang; Yingying Xu; Sultan Salem. Theoretical and experimental evidence on stock market volatilities: a two-phase flow model. Economic Research-Ekonomska Istraživanja 2021, 1 -25.

AMA Style

Limin Wang, Yingying Xu, Sultan Salem. Theoretical and experimental evidence on stock market volatilities: a two-phase flow model. Economic Research-Ekonomska Istraživanja. 2021; ():1-25.

Chicago/Turabian Style

Limin Wang; Yingying Xu; Sultan Salem. 2021. "Theoretical and experimental evidence on stock market volatilities: a two-phase flow model." Economic Research-Ekonomska Istraživanja , no. : 1-25.

Research article
Published: 26 October 2020 in International Journal of Finance & Economics
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Macroeconomic factors and sentiments affect investors' decisions and thus stock returns. However, do sentiments on macro‐economic news explain stock returns? This article proposes a theoretical model to explain the relationship between stock returns and the market misperception which is driven by investors' sentiments. Then, microblogs regarding the macro‐economy posted on Sina Weibo, a mainstream Chinese Social Network Site, are extracted to measure investors' macroeconomic sentiments (IMSs) through machine learning approaches. A preliminary event study suggests that IMSs capture the development of influential macroeconomic events. Empirical results demonstrate that orthogonalized IMSs including anger, disgust, fear, joy and sadness exert heterogeneously significant effects on the Shanghai Composite Index (SHCI), and no reverse effect is found. Thus, the IMS contains additional information related to the macro‐economy; but cannot be explained by macroeconomic factors. IMSs improve the in‐ and out‐of‐sample predictabilities of SHCI returns. Thereby, investors' sentiment can be an important channel through which the macro‐economy affects the stock market.

ACS Style

Yingying Xu; Jichang Zhao. Can sentiments on macroeconomic news explain stock returns? Evidence form social network data. International Journal of Finance & Economics 2020, 1 .

AMA Style

Yingying Xu, Jichang Zhao. Can sentiments on macroeconomic news explain stock returns? Evidence form social network data. International Journal of Finance & Economics. 2020; ():1.

Chicago/Turabian Style

Yingying Xu; Jichang Zhao. 2020. "Can sentiments on macroeconomic news explain stock returns? Evidence form social network data." International Journal of Finance & Economics , no. : 1.

Journal article
Published: 21 July 2020 in Journal of International Financial Markets, Institutions and Money
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Since March 2018 the United States and China have been locked in a trade confrontation featured by huge retaliatory tariffs. This paper investigates the impact of the U.S.-China trade war on the dynamic dependences of Chinese yuan (CNY) and the currencies of its major trade partners merging a generalized autoregressive score-driving (GAS) model and the copula approach. The GAS framework is used to capture the marginal distributions of each exchange rate return series and then to estimate the dynamic copula correlation between CNY and major trading currencies. We document intra-regional currency contagions that the dependences of KRW-CNY and SGD-CNY have increased and remained at high levels, whereas the dependence of JPY-CNY is reduced after the breakout of the trade war. The dependences of AUD-CNY and EUR-CNY also increase in the post-war period. Appreciations in the USD against target currency and the downside risk of the global economy caused by the trade war are possible factors driving changes in exchange rates and dependences between CNY and currencies of major trade partners.

ACS Style

Yingying Xu; Donald Lien. Dynamic exchange rate dependences: The effect of the U.S.-China trade war. Journal of International Financial Markets, Institutions and Money 2020, 68, 101238 .

AMA Style

Yingying Xu, Donald Lien. Dynamic exchange rate dependences: The effect of the U.S.-China trade war. Journal of International Financial Markets, Institutions and Money. 2020; 68 ():101238.

Chicago/Turabian Style

Yingying Xu; Donald Lien. 2020. "Dynamic exchange rate dependences: The effect of the U.S.-China trade war." Journal of International Financial Markets, Institutions and Money 68, no. : 101238.

Research article
Published: 16 April 2020 in Journal of Futures Markets
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This paper applies generalized autoregressive score‐driven (GAS) models to futures hedging of crude oil and natural gas. For both commodities, the GAS framework captures the marginal distributions of spot and futures returns and corresponding dynamic copula correlations. We compare within‐sample and out‐of‐sample hedging effectiveness of GAS models against constant ordinary least square (OLS) strategy and time‐varying copula‐based GARCH models in terms of volatility reduction and Value at Risk reduction. We show that the constant OLS hedge ratio is not inherently inferior to the time‐varying alternatives. Nonetheless, GAS models tend to exhibit better hedging effectiveness than other strategies, particularly for natural gas.

ACS Style

Yingying Xu; Donald Lien. Optimal futures hedging for energy commodities: An application of the GAS model. Journal of Futures Markets 2020, 40, 1090 -1108.

AMA Style

Yingying Xu, Donald Lien. Optimal futures hedging for energy commodities: An application of the GAS model. Journal of Futures Markets. 2020; 40 (7):1090-1108.

Chicago/Turabian Style

Yingying Xu; Donald Lien. 2020. "Optimal futures hedging for energy commodities: An application of the GAS model." Journal of Futures Markets 40, no. 7: 1090-1108.

Journal article
Published: 06 January 2020 in Energy
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A low-carbon transition requires changes in the energy structure that may affect the financial system. However, little theoretical and empirical evidence has been produced regarding the interaction between different subsystems. This article presents empirical evidence regarding the relationship between energy and financial systems using the wavelet analysis which considers possible cyclical properties that change over time. The wavelet coherence coefficients based on the data for the United States suggest that the electricity price is closely related to shares of different energy-powered electricity production, but has weak relationships with the interbank connectivity and bank failures. The phase differences show that increases in nuclear energy-powered electricity generation reduce the electricity price at less than one and a half years of scale, but rise it at approximately three years of scale. However, different energy shares have little effect on the interbank connectivity. An increase in renewable energy in producing electricity may reduce the number of failed banks, whereas an increase in nuclear energy has an opposite effect. Therefore, the energy transition affects the financial system and excessively fast investment in nuclear energy may threat the bank sector and thus endanger the financial system. The Nuclear Renaissance program should be treated with caution.

ACS Style

Yingying Xu. Will energy transitions impact financial systems? Energy 2020, 194, 116910 .

AMA Style

Yingying Xu. Will energy transitions impact financial systems? Energy. 2020; 194 ():116910.

Chicago/Turabian Style

Yingying Xu. 2020. "Will energy transitions impact financial systems?" Energy 194, no. : 116910.

Journal article
Published: 21 March 2019 in Sustainability
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This paper examines the daily return series of four main indices, including Shanghai Stock Exchange Composite Index (SSE), Shenzhen Stock Exchange Component Index (SZSE), Shanghai Shenzhen 300 Index (SHSE-SZSE300), and CSI Smallcap 500 index (CSI500) in Chinese stock market from 2000 to 2018 by multifractal detrended fluctuation analysis (MF-DFA). The series of the daily return of the indices exhibit significant multifractal properties on the whole time scale and SZSE has the highest multifractal properties among the four indices, indicating the lowest market efficiency. The multifractal properties of four indices are due to long-range correlation and fat-tail characteristics of the non-Gaussian probability density function, and these two factors have different effects on the multifractality of four indices. This paper aims to compare the multifractility degrees of the four indices in three sub-samples divided by the 2015 stock market crash and to discuss its effects on efficiency of the Shanghai and Shenzhen stock market in each sub-sample. Meanwhile, we study the effect of the 2015 stock market crash on market efficiency from the statistical and fractal perspectives, which has theoretical and practical significance in the application of Effective Market Hypothesis (EMH) in China’s stock market, and it thereby affects the healthy and sustainability of the market. The results also provide important implications for further study on the dynamic mechanism and efficiency in stock market and they are relevant to portfolio managers and policy makers in a number of ways to maintain the sustainable development of China’s capital market and economy.

ACS Style

Chenyu Han; Yiming Wang; Yingying Xu. Efficiency and Multifractality Analysis of the Chinese Stock Market: Evidence from Stock Indices before and after the 2015 Stock Market Crash. Sustainability 2019, 11, 1699 .

AMA Style

Chenyu Han, Yiming Wang, Yingying Xu. Efficiency and Multifractality Analysis of the Chinese Stock Market: Evidence from Stock Indices before and after the 2015 Stock Market Crash. Sustainability. 2019; 11 (6):1699.

Chicago/Turabian Style

Chenyu Han; Yiming Wang; Yingying Xu. 2019. "Efficiency and Multifractality Analysis of the Chinese Stock Market: Evidence from Stock Indices before and after the 2015 Stock Market Crash." Sustainability 11, no. 6: 1699.

Journal article
Published: 10 October 2018 in Sustainability
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This paper constructs a theoretical model to analyze the effect of macroprudential policies (MPPs) on bank risk-taking. We collect a data set of 231 commercial banks in China to empirically test whether macroprudential tools, including countercyclical capital buffers, reserve requirements, and caps on loan-to-value, can affect bank risk-taking behaviors by using the dynamic unbalanced panel system generalized method of moment (SYS-GMM). The results provide further evidence on the important role of MPPs in maintaining financial stability, which helps mitigate financial system vulnerabilities. Bank risk-taking will be decreased with the strengthening of macroprudential supervision, which greatly benefits the resilience and the sustainability of bank sector. Moreover, the credit cycle has a magnifying role on MPPs’ effect on bank risk-taking. Reducing risks in bank loans requires a further slowing of credit growth, which is necessary to ensure sustainable growth in a bank system, or more ambitiously, to smooth financial booms and busts. The results survive robustness checks under alternative estimation methods and alternative proxies of bank risk-taking and MPPs.

ACS Style

Xing Zhang; Fengchao Li; Zhen Li; Yingying Xu. Macroprudential Policy, Credit Cycle, and Bank Risk-Taking. Sustainability 2018, 10, 3620 .

AMA Style

Xing Zhang, Fengchao Li, Zhen Li, Yingying Xu. Macroprudential Policy, Credit Cycle, and Bank Risk-Taking. Sustainability. 2018; 10 (10):3620.

Chicago/Turabian Style

Xing Zhang; Fengchao Li; Zhen Li; Yingying Xu. 2018. "Macroprudential Policy, Credit Cycle, and Bank Risk-Taking." Sustainability 10, no. 10: 3620.

Research article
Published: 10 October 2018 in PLOS ONE
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Based on carbon spot prices selected from seven carbon pilots, we assess the financial performances related to carbon volatility in China on the overall perspective. According to the results, the Chinese carbon market fluctuated severely at the beginning of carbon trading, but has stabilised in general, despite several dramatic changes related to ‘yearly compliance events’. Long-term memory exists in the volatility series. Moreover, asymmetry exists in the Chinese carbon market, and volatility reacts more severely to good news than to bad news. Finally, we discuss our empirical results, and make certain suggestions regarding firms’ awareness, international cooperation and individual investors not only for policy makers in China but also for other developing countries who are contemplating either commencing carbon trading or improving the current market.

ACS Style

Yinpeng Zhang; Zhixin Liu; Yingying Xu. Carbon price volatility: The case of China. PLOS ONE 2018, 13, e0205317 .

AMA Style

Yinpeng Zhang, Zhixin Liu, Yingying Xu. Carbon price volatility: The case of China. PLOS ONE. 2018; 13 (10):e0205317.

Chicago/Turabian Style

Yinpeng Zhang; Zhixin Liu; Yingying Xu. 2018. "Carbon price volatility: The case of China." PLOS ONE 13, no. 10: e0205317.

Research article
Published: 03 July 2017 in PLOS ONE
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This study provides new insights into the relationships between social media sentiments and the stock market in China. Based on machine learning, we classify microblogs posted on Sina Weibo, a Twitter’s variant in China into five detailed sentiments of anger, disgust, fear, joy, and sadness. Using wavelet analysis, we find close positive linkages between sentiments and the stock return, which have both frequency and time-varying features. Five detailed sentiments are positively related to the stock return for certain periods, particularly since October 2014 at medium to high frequencies of less than ten trading days, when the stock return is undergoing significant fluctuations. Sadness appears to have a closer relationship with the stock return than the other four sentiments. As to the lead-lag relationships, the stock return causes Weibo sentiments rather than reverse for most of the periods with significant linkages. Compared with polarity sentiments (negative vs. positive), detailed sentiments provide more information regarding relationships between Weibo sentiments and the stock market. The stock market exerts positive effects on bullishness and agreement of microblogs. Meanwhile, agreement leads the stock return in-phase at the frequency of approximately 40 trading days, indicating that less disagreement improves certainty about the stock market.

ACS Style

Yingying Xu; Zhixin Liu; Jichang Zhao; ChiWei Su. Weibo sentiments and stock return: A time-frequency view. PLOS ONE 2017, 12, e0180723 .

AMA Style

Yingying Xu, Zhixin Liu, Jichang Zhao, ChiWei Su. Weibo sentiments and stock return: A time-frequency view. PLOS ONE. 2017; 12 (7):e0180723.

Chicago/Turabian Style

Yingying Xu; Zhixin Liu; Jichang Zhao; ChiWei Su. 2017. "Weibo sentiments and stock return: A time-frequency view." PLOS ONE 12, no. 7: e0180723.