The impacts of liquidity dynamics on emissions allowances price: Different evidence from China's emissions trading pilots

The liquidities of China's emissions trading markets have significant impacts on emissions allowances price movement and pricing efficiency. Liquidity measures on illiquidity ratio and trade values indicate Hubei emissions allowances (HBEA) product has the highest liquidity, Shenzhen allowances...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Chang, Kai [verfasserIn] Lu, Shibao [verfasserIn] Song, Xiayun [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2018

Schlagwörter:	Liquidity dynamics Emissions allowances Pricing efficiency Illiquidity ratio Trade-based liquidity Volatility clustering

Übergeordnetes Werk:	Enthalten in: Journal of cleaner production - Amsterdam [u.a.] : Elsevier Science, 1993, 183, Seite 786-796
Übergeordnetes Werk:	volume:183 ; pages:786-796

DOI / URN:	10.1016/j.jclepro.2018.02.150

Katalog-ID:	ELV001710400

Internformat


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520			\|a The liquidities of China's emissions trading markets have significant impacts on emissions allowances price movement and pricing efficiency. Liquidity measures on illiquidity ratio and trade values indicate Hubei emissions allowances (HBEA) product has the highest liquidity, Shenzhen allowances (SZA) and Guangdong emissions allowances(GDEA) products have the higher liquidity than Beijing emissions allowances (BEA) and Shanghai emissions allowances (SHEA) products, while Tianjin emissions allowances (TJEA) product has the lowest market liquidity in considered China's emissions trading pilots. The dynamics of the illiquidity ratios for all selected emissions allowances products are negatively related with emissions allowances returns, and trade volumes for BEA, TJEA, SZA and HBEA products are also negatively related with emissions allowances returns. The dynamics of daily illiquidity ratios and trade-based liquidity in Beijing, Tianjin, Guangdong, Shenzhen, Hubei emissions pilots have significant volatility clustering impacts on the variances of regional emissions allowances returns. Previous market shocks of overnight and intraday price variations have the more persistent influences on the GDEA returns than HBEA returns, reflecting greater inter-day price ranges clustering effect.
650		4	\|a Liquidity dynamics
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matchkey_str	article:09596526:2018----::hipcsfiudtdnmcoeisosloacsrcdfeetvdnermh
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publishDate	2018
allfields	10.1016/j.jclepro.2018.02.150 doi (DE-627)ELV001710400 (ELSEVIER)S0959-6526(18)30463-3 DE-627 ger DE-627 rda eng 690 330 DE-600 43.35 bkl 85.35 bkl Chang, Kai verfasserin aut The impacts of liquidity dynamics on emissions allowances price: Different evidence from China's emissions trading pilots 2018 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The liquidities of China's emissions trading markets have significant impacts on emissions allowances price movement and pricing efficiency. Liquidity measures on illiquidity ratio and trade values indicate Hubei emissions allowances (HBEA) product has the highest liquidity, Shenzhen allowances (SZA) and Guangdong emissions allowances(GDEA) products have the higher liquidity than Beijing emissions allowances (BEA) and Shanghai emissions allowances (SHEA) products, while Tianjin emissions allowances (TJEA) product has the lowest market liquidity in considered China's emissions trading pilots. The dynamics of the illiquidity ratios for all selected emissions allowances products are negatively related with emissions allowances returns, and trade volumes for BEA, TJEA, SZA and HBEA products are also negatively related with emissions allowances returns. The dynamics of daily illiquidity ratios and trade-based liquidity in Beijing, Tianjin, Guangdong, Shenzhen, Hubei emissions pilots have significant volatility clustering impacts on the variances of regional emissions allowances returns. Previous market shocks of overnight and intraday price variations have the more persistent influences on the GDEA returns than HBEA returns, reflecting greater inter-day price ranges clustering effect. Liquidity dynamics Emissions allowances Pricing efficiency Illiquidity ratio Trade-based liquidity Volatility clustering Lu, Shibao verfasserin aut Song, Xiayun verfasserin aut Enthalten in Journal of cleaner production Amsterdam [u.a.] : Elsevier Science, 1993 183, Seite 786-796 Online-Ressource (DE-627)324655878 (DE-600)2029338-0 (DE-576)252613988 0959-6526 nnns volume:183 pages:786-796 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 43.35 Umweltrichtlinien Umweltnormen 85.35 Fertigung AR 183 786-796
spelling	10.1016/j.jclepro.2018.02.150 doi (DE-627)ELV001710400 (ELSEVIER)S0959-6526(18)30463-3 DE-627 ger DE-627 rda eng 690 330 DE-600 43.35 bkl 85.35 bkl Chang, Kai verfasserin aut The impacts of liquidity dynamics on emissions allowances price: Different evidence from China's emissions trading pilots 2018 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The liquidities of China's emissions trading markets have significant impacts on emissions allowances price movement and pricing efficiency. Liquidity measures on illiquidity ratio and trade values indicate Hubei emissions allowances (HBEA) product has the highest liquidity, Shenzhen allowances (SZA) and Guangdong emissions allowances(GDEA) products have the higher liquidity than Beijing emissions allowances (BEA) and Shanghai emissions allowances (SHEA) products, while Tianjin emissions allowances (TJEA) product has the lowest market liquidity in considered China's emissions trading pilots. The dynamics of the illiquidity ratios for all selected emissions allowances products are negatively related with emissions allowances returns, and trade volumes for BEA, TJEA, SZA and HBEA products are also negatively related with emissions allowances returns. The dynamics of daily illiquidity ratios and trade-based liquidity in Beijing, Tianjin, Guangdong, Shenzhen, Hubei emissions pilots have significant volatility clustering impacts on the variances of regional emissions allowances returns. Previous market shocks of overnight and intraday price variations have the more persistent influences on the GDEA returns than HBEA returns, reflecting greater inter-day price ranges clustering effect. Liquidity dynamics Emissions allowances Pricing efficiency Illiquidity ratio Trade-based liquidity Volatility clustering Lu, Shibao verfasserin aut Song, Xiayun verfasserin aut Enthalten in Journal of cleaner production Amsterdam [u.a.] : Elsevier Science, 1993 183, Seite 786-796 Online-Ressource (DE-627)324655878 (DE-600)2029338-0 (DE-576)252613988 0959-6526 nnns volume:183 pages:786-796 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 43.35 Umweltrichtlinien Umweltnormen 85.35 Fertigung AR 183 786-796
allfields_unstemmed	10.1016/j.jclepro.2018.02.150 doi (DE-627)ELV001710400 (ELSEVIER)S0959-6526(18)30463-3 DE-627 ger DE-627 rda eng 690 330 DE-600 43.35 bkl 85.35 bkl Chang, Kai verfasserin aut The impacts of liquidity dynamics on emissions allowances price: Different evidence from China's emissions trading pilots 2018 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The liquidities of China's emissions trading markets have significant impacts on emissions allowances price movement and pricing efficiency. Liquidity measures on illiquidity ratio and trade values indicate Hubei emissions allowances (HBEA) product has the highest liquidity, Shenzhen allowances (SZA) and Guangdong emissions allowances(GDEA) products have the higher liquidity than Beijing emissions allowances (BEA) and Shanghai emissions allowances (SHEA) products, while Tianjin emissions allowances (TJEA) product has the lowest market liquidity in considered China's emissions trading pilots. The dynamics of the illiquidity ratios for all selected emissions allowances products are negatively related with emissions allowances returns, and trade volumes for BEA, TJEA, SZA and HBEA products are also negatively related with emissions allowances returns. The dynamics of daily illiquidity ratios and trade-based liquidity in Beijing, Tianjin, Guangdong, Shenzhen, Hubei emissions pilots have significant volatility clustering impacts on the variances of regional emissions allowances returns. Previous market shocks of overnight and intraday price variations have the more persistent influences on the GDEA returns than HBEA returns, reflecting greater inter-day price ranges clustering effect. Liquidity dynamics Emissions allowances Pricing efficiency Illiquidity ratio Trade-based liquidity Volatility clustering Lu, Shibao verfasserin aut Song, Xiayun verfasserin aut Enthalten in Journal of cleaner production Amsterdam [u.a.] : Elsevier Science, 1993 183, Seite 786-796 Online-Ressource (DE-627)324655878 (DE-600)2029338-0 (DE-576)252613988 0959-6526 nnns volume:183 pages:786-796 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 43.35 Umweltrichtlinien Umweltnormen 85.35 Fertigung AR 183 786-796
allfieldsGer	10.1016/j.jclepro.2018.02.150 doi (DE-627)ELV001710400 (ELSEVIER)S0959-6526(18)30463-3 DE-627 ger DE-627 rda eng 690 330 DE-600 43.35 bkl 85.35 bkl Chang, Kai verfasserin aut The impacts of liquidity dynamics on emissions allowances price: Different evidence from China's emissions trading pilots 2018 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The liquidities of China's emissions trading markets have significant impacts on emissions allowances price movement and pricing efficiency. Liquidity measures on illiquidity ratio and trade values indicate Hubei emissions allowances (HBEA) product has the highest liquidity, Shenzhen allowances (SZA) and Guangdong emissions allowances(GDEA) products have the higher liquidity than Beijing emissions allowances (BEA) and Shanghai emissions allowances (SHEA) products, while Tianjin emissions allowances (TJEA) product has the lowest market liquidity in considered China's emissions trading pilots. The dynamics of the illiquidity ratios for all selected emissions allowances products are negatively related with emissions allowances returns, and trade volumes for BEA, TJEA, SZA and HBEA products are also negatively related with emissions allowances returns. The dynamics of daily illiquidity ratios and trade-based liquidity in Beijing, Tianjin, Guangdong, Shenzhen, Hubei emissions pilots have significant volatility clustering impacts on the variances of regional emissions allowances returns. Previous market shocks of overnight and intraday price variations have the more persistent influences on the GDEA returns than HBEA returns, reflecting greater inter-day price ranges clustering effect. Liquidity dynamics Emissions allowances Pricing efficiency Illiquidity ratio Trade-based liquidity Volatility clustering Lu, Shibao verfasserin aut Song, Xiayun verfasserin aut Enthalten in Journal of cleaner production Amsterdam [u.a.] : Elsevier Science, 1993 183, Seite 786-796 Online-Ressource (DE-627)324655878 (DE-600)2029338-0 (DE-576)252613988 0959-6526 nnns volume:183 pages:786-796 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 43.35 Umweltrichtlinien Umweltnormen 85.35 Fertigung AR 183 786-796
allfieldsSound	10.1016/j.jclepro.2018.02.150 doi (DE-627)ELV001710400 (ELSEVIER)S0959-6526(18)30463-3 DE-627 ger DE-627 rda eng 690 330 DE-600 43.35 bkl 85.35 bkl Chang, Kai verfasserin aut The impacts of liquidity dynamics on emissions allowances price: Different evidence from China's emissions trading pilots 2018 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The liquidities of China's emissions trading markets have significant impacts on emissions allowances price movement and pricing efficiency. Liquidity measures on illiquidity ratio and trade values indicate Hubei emissions allowances (HBEA) product has the highest liquidity, Shenzhen allowances (SZA) and Guangdong emissions allowances(GDEA) products have the higher liquidity than Beijing emissions allowances (BEA) and Shanghai emissions allowances (SHEA) products, while Tianjin emissions allowances (TJEA) product has the lowest market liquidity in considered China's emissions trading pilots. The dynamics of the illiquidity ratios for all selected emissions allowances products are negatively related with emissions allowances returns, and trade volumes for BEA, TJEA, SZA and HBEA products are also negatively related with emissions allowances returns. The dynamics of daily illiquidity ratios and trade-based liquidity in Beijing, Tianjin, Guangdong, Shenzhen, Hubei emissions pilots have significant volatility clustering impacts on the variances of regional emissions allowances returns. Previous market shocks of overnight and intraday price variations have the more persistent influences on the GDEA returns than HBEA returns, reflecting greater inter-day price ranges clustering effect. Liquidity dynamics Emissions allowances Pricing efficiency Illiquidity ratio Trade-based liquidity Volatility clustering Lu, Shibao verfasserin aut Song, Xiayun verfasserin aut Enthalten in Journal of cleaner production Amsterdam [u.a.] : Elsevier Science, 1993 183, Seite 786-796 Online-Ressource (DE-627)324655878 (DE-600)2029338-0 (DE-576)252613988 0959-6526 nnns volume:183 pages:786-796 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 43.35 Umweltrichtlinien Umweltnormen 85.35 Fertigung AR 183 786-796
language	English
source	Enthalten in Journal of cleaner production 183, Seite 786-796 volume:183 pages:786-796
sourceStr	Enthalten in Journal of cleaner production 183, Seite 786-796 volume:183 pages:786-796
format_phy_str_mv	Article
bklname	Umweltrichtlinien Umweltnormen Fertigung
institution	findex.gbv.de
topic_facet	Liquidity dynamics Emissions allowances Pricing efficiency Illiquidity ratio Trade-based liquidity Volatility clustering
dewey-raw	690
isfreeaccess_bool	false
container_title	Journal of cleaner production
authorswithroles_txt_mv	Chang, Kai @@aut@@ Lu, Shibao @@aut@@ Song, Xiayun @@aut@@
publishDateDaySort_date	2018-01-01T00:00:00Z
hierarchy_top_id	324655878
dewey-sort	3690
id	ELV001710400
language_de	englisch
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author	Chang, Kai
spellingShingle	Chang, Kai ddc 690 bkl 43.35 bkl 85.35 misc Liquidity dynamics misc Emissions allowances misc Pricing efficiency misc Illiquidity ratio misc Trade-based liquidity misc Volatility clustering The impacts of liquidity dynamics on emissions allowances price: Different evidence from China's emissions trading pilots
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topic_title	690 330 DE-600 43.35 bkl 85.35 bkl The impacts of liquidity dynamics on emissions allowances price: Different evidence from China's emissions trading pilots Liquidity dynamics Emissions allowances Pricing efficiency Illiquidity ratio Trade-based liquidity Volatility clustering
topic	ddc 690 bkl 43.35 bkl 85.35 misc Liquidity dynamics misc Emissions allowances misc Pricing efficiency misc Illiquidity ratio misc Trade-based liquidity misc Volatility clustering
topic_unstemmed	ddc 690 bkl 43.35 bkl 85.35 misc Liquidity dynamics misc Emissions allowances misc Pricing efficiency misc Illiquidity ratio misc Trade-based liquidity misc Volatility clustering
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title	The impacts of liquidity dynamics on emissions allowances price: Different evidence from China's emissions trading pilots
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title_full	The impacts of liquidity dynamics on emissions allowances price: Different evidence from China's emissions trading pilots
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title_sort	the impacts of liquidity dynamics on emissions allowances price: different evidence from china's emissions trading pilots
title_auth	The impacts of liquidity dynamics on emissions allowances price: Different evidence from China's emissions trading pilots
abstract	The liquidities of China's emissions trading markets have significant impacts on emissions allowances price movement and pricing efficiency. Liquidity measures on illiquidity ratio and trade values indicate Hubei emissions allowances (HBEA) product has the highest liquidity, Shenzhen allowances (SZA) and Guangdong emissions allowances(GDEA) products have the higher liquidity than Beijing emissions allowances (BEA) and Shanghai emissions allowances (SHEA) products, while Tianjin emissions allowances (TJEA) product has the lowest market liquidity in considered China's emissions trading pilots. The dynamics of the illiquidity ratios for all selected emissions allowances products are negatively related with emissions allowances returns, and trade volumes for BEA, TJEA, SZA and HBEA products are also negatively related with emissions allowances returns. The dynamics of daily illiquidity ratios and trade-based liquidity in Beijing, Tianjin, Guangdong, Shenzhen, Hubei emissions pilots have significant volatility clustering impacts on the variances of regional emissions allowances returns. Previous market shocks of overnight and intraday price variations have the more persistent influences on the GDEA returns than HBEA returns, reflecting greater inter-day price ranges clustering effect.
abstractGer	The liquidities of China's emissions trading markets have significant impacts on emissions allowances price movement and pricing efficiency. Liquidity measures on illiquidity ratio and trade values indicate Hubei emissions allowances (HBEA) product has the highest liquidity, Shenzhen allowances (SZA) and Guangdong emissions allowances(GDEA) products have the higher liquidity than Beijing emissions allowances (BEA) and Shanghai emissions allowances (SHEA) products, while Tianjin emissions allowances (TJEA) product has the lowest market liquidity in considered China's emissions trading pilots. The dynamics of the illiquidity ratios for all selected emissions allowances products are negatively related with emissions allowances returns, and trade volumes for BEA, TJEA, SZA and HBEA products are also negatively related with emissions allowances returns. The dynamics of daily illiquidity ratios and trade-based liquidity in Beijing, Tianjin, Guangdong, Shenzhen, Hubei emissions pilots have significant volatility clustering impacts on the variances of regional emissions allowances returns. Previous market shocks of overnight and intraday price variations have the more persistent influences on the GDEA returns than HBEA returns, reflecting greater inter-day price ranges clustering effect.
abstract_unstemmed	The liquidities of China's emissions trading markets have significant impacts on emissions allowances price movement and pricing efficiency. Liquidity measures on illiquidity ratio and trade values indicate Hubei emissions allowances (HBEA) product has the highest liquidity, Shenzhen allowances (SZA) and Guangdong emissions allowances(GDEA) products have the higher liquidity than Beijing emissions allowances (BEA) and Shanghai emissions allowances (SHEA) products, while Tianjin emissions allowances (TJEA) product has the lowest market liquidity in considered China's emissions trading pilots. The dynamics of the illiquidity ratios for all selected emissions allowances products are negatively related with emissions allowances returns, and trade volumes for BEA, TJEA, SZA and HBEA products are also negatively related with emissions allowances returns. The dynamics of daily illiquidity ratios and trade-based liquidity in Beijing, Tianjin, Guangdong, Shenzhen, Hubei emissions pilots have significant volatility clustering impacts on the variances of regional emissions allowances returns. Previous market shocks of overnight and intraday price variations have the more persistent influences on the GDEA returns than HBEA returns, reflecting greater inter-day price ranges clustering effect.
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title_short	The impacts of liquidity dynamics on emissions allowances price: Different evidence from China's emissions trading pilots
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up_date	2024-07-06T22:18:36.509Z
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