scholarly journals The Linkages of Carbon Spot-Futures: Evidence from EU-ETS in the Third Phase

2020 ◽  
Vol 12 (6) ◽  
pp. 2517 ◽  
Author(s):  
Hao Chen ◽  
Zhixin Liu ◽  
Yinpeng Zhang ◽  
You Wu
Keyword(s):  
Phase Ii ◽  
Futures Markets ◽  
Garch Model ◽  
Futures Market ◽  
Phase Iii ◽  
Volatility Spillover ◽  
Dynamic Correlation ◽  
Third Phase ◽  
Highly Correlated ◽  
The Relationship

Based on the prices selected from European Energy Exchange (EEX) from 2013 to 2018, we investigate the inter-correlation of carbon spot and futures markets. Specifically, we adopt the widely used DCC-GARCH model and VAR-BEKK-GARCH model to conduct a comprehensive analysis on the carbon market, i.e., the dynamic correlation and volatility spillover between carbon spot and carbon futures. Moreover, we develop a hedge strategy based on the VAR-BEKK-GARCH model and calculate the hedging effectiveness (HE) value to evaluate the strategy performance. The empirical results show that (i) during our sample period, carbon spot and futures markets are highly correlated, (ii) carbon spot overflows to the futures market and vice versa, and (iii) the HE value is equal to 0.9370, indicating a good performance for the hedging strategy. Then, we provide further discussion on the relationship between carbon spot and futures markets by replacing our dataset with the data of phase II. The results do not change our conclusions on the dynamic correlation and volatility spillover. However, the HE value of phase III is higher than that of phase II, which indicates that the carbon futures market of phase III is not only an available market to hedge risk from the contemporaneous carbon spot market but also has a better hedge effectiveness than phase II.

scholarly journals Has COVID-19 Changed the Hedge Effectiveness of Bitcoin?

2021 ◽  
Vol 9 ◽  
Author(s):  
Yinpeng Zhang ◽  
Panpan Zhu ◽  
Yingying Xu
Keyword(s):  
Futures Markets ◽  
Vector Autoregression ◽  
Spot Market ◽  
Futures Market ◽  
Conditional Heteroskedasticity ◽  
Volatility Spillover ◽  
Empirical Results ◽  
Dynamic Correlation ◽  
Autoregressive Conditional Heteroskedasticity ◽  
Gold Futures

The Bitcoin market has become a research hotspot after the outbreak of Covid-19. In this paper, we focus on the relationships between the Bitcoin spot and futures. Specifically, we adopt the vector autoregression-dynamic correlation coefficient-generalized autoregressive conditional heteroskedasticity (VAR-DCC-GARCH) model and vector autoregression-Baba, Engle, Kraft, and Kroner-generalized autoregressive conditional heteroskedasticity (VAR-BEKK-GARCH) models and calculate the hedging effectiveness (HE) value to investigate the dynamic correlation and volatility spillover and assess the risk reduction of the Bitcoin futures to spot. The empirical results show that the Bitcoin spot and futures markets are highly connected; second, there exists a bi-directional volatility spillover between the spot and futures market; third, the HE value is equal to 0.6446, which indicates that Bitcoin futures can indeed hedge the risks in the Bitcoin spot market. Furthermore, we update the data to the post-Covid-19 period to do the robustness checks. The results do not change our conclusion that Bitcoin futures can hedge the risks in the Bitcoin spot market, and besides, the post-Covid-19 results indicate that the hedging ability of Bitcoin futures increased. Finally, we test whether the gold futures can be used as a Bitcoin spot market hedge, and we further control other cryptocurrencies to illustrate the hedging ability of the Bitcoin futures to the Bitcoin spot. Overall, the empirical results in this paper will surely benefit the related investors in the Bitcoin market.

scholarly journals Volatility Dynamics in Oil and Oilseeds Spot and Futures Market in India

2016 ◽  
Vol 41 (2) ◽  
pp. 132-148 ◽  
Author(s):  
Meenakshi Malhotra ◽  
Dinesh Kumar Sharma
Keyword(s):  
Futures Markets ◽  
Garch Model ◽  
Price Volatility ◽  
Spot Market ◽  
Futures Market ◽  
Spot Price ◽  
Volatility Spillover ◽  
Trading Activity ◽  
Futures Trading ◽  
The Impact

Executive Summary India occupies the fifth position in the vegetable oil economy of the world. The demand for oilseeds and vegetable oil has far exceeded the domestic output necessitating huge imports. Futures market helps to bring price stability for the development of the underlying physical market. The present study investigates the volatility dynamics in spot and futures markets of select oil and oilseeds commodities. The objectives of this article are to study (a) the information transmission process between spot and futures markets, also called volatility spillover and (b) the impact of futures trading activity on the volatility of physical market prices. The commodities selected from oil and oilseeds segment are refined soya oil, mustard seed, crude palm oil, and mentha oil. The study uses basic Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model to capture volatility in prices of the selected commodities. Bivariate GARCH model makes use of information in the history of two different markets for testing volatility spillover between two markets of the same underlying commodity. The relationship between futures trading activity and spot price volatility is investigated for examining the impact of futures trading activity on the volatility of underlying spot market. Two variables, viz., futures trading volume and open interest are decomposed into expected and unexpected components and are taken as a proxy for the level of trading activity. The contemporaneous and dynamic relationships are studied with the help of augmented GARCH model and Granger causality, respectively. It is observed that there is an efficient transmission of information between spot and futures markets but it is the spot market which leads to the flow of information to futures and hence causes greater spillover of volatility. The spot market has a greater impact on the volatility of futures market, indicating that informational efficiency of oilseeds spot market is stronger than that of the futures market. The contemporaneous and dynamic relationship between spot price volatility and futures trading activity tested with econometric models provide evidence of the destabilizing impact of an unexpected increase in futures trading activity (volume or open interest) on the spot price volatility in three out of four commodities studied. This indicates that badly informed traders present in futures market are destabilizing the underlying spot market by inducing noise and lowering the information content of prices.

Volatility Spillover between the KOSPI 200 Spot and Futures Markets Using the VECM-DCC-GARCH Model

2011 ◽  
Vol 19 (3) ◽  
pp. 233-249
Author(s):  
Sang Hoon Kang ◽  
Seong-Min Yoon
Keyword(s):  
Information Flow ◽  
Futures Markets ◽  
Price Discovery ◽  
Spillover Effects ◽  
Spot Market ◽  
Futures Market ◽  
Market Volatility ◽  
Futures Contracts ◽  
Volatility Spillover ◽  
Asymmetric Volatility

This paper investigates the price discovery, volatility spillover, and asymmetric volatility spillover effects between the KOSPI 200 market and its futures contracts market. The investigation was performed using the VECM-DCC-GARCH approach. In the case of returns, we found a significant unidirectional information flow from the futures market to the spot market; this implies that the KOSPI 200 futures market plays an important role on the price discovery in the spot market. In addition, we found a strong bi-directional casualty involving the volatility interaction between the spot and futures markets; this implies that market volatility originating in the spot market will influence the volatility of the futures market and vice versa. We also found strong asymmetric volatility spillover effects between the two markets.

Price discovery and volatility spillover: an empirical evidence from spot and futures agricultural commodity markets in India

2020 ◽  
Vol 10 (4) ◽  
pp. 447-473 ◽  
Author(s):  
Manogna R L ◽  
Aswini Kumar Mishra
Keyword(s):  
Granger Causality ◽  
Futures Markets ◽  
Price Discovery ◽  
Spillover Effects ◽  
Futures Market ◽  
Commodity Markets ◽  
Volatility Spillover ◽  
Agricultural Commodity ◽  
Content Type ◽  
Spot Prices

PurposePrice discovery and spillover effect are prominent indicators in the commodity futures market to protect the interest of consumers, farmers and to hedge sharp price fluctuations. The purpose of this paper is to investigate empirically the price discovery and volatility spillover in Indian agriculture spot and futures commodity markets.Design/methodology/approachThis study uses Granger causality, vector error correction model (VECM) and exponential generalized autoregressive conditional heteroskedasticity (EGARCH) to examines the price discovery and spillover effects for nine most liquid agricultural commodities in spot and futures markets traded on National Commodity and Derivatives Exchange (NCDEX).FindingsThe VECM results show that price discovery exists in all the nine commodities with futures market leading the spot in case of six commodities, namely soybean seed, coriander, turmeric, castor seed, guar seed and chana. Whereas in case of three commodities (cotton seed, rape mustard seed and jeera), price discovery takes place in the spot market. The Granger causality tests indicate that futures markets have stronger ability to predict spot prices. Supporting these, the results from EGARCH volatility test reveal that there exist mutual spillover effects on futures and spot markets. Thus, it could be inferred that futures market is more efficient in price discovery of agricultural commodities in India.Research limitations/implicationsThese results can help the market participants to benefit by hedging out the uncertainty and the policymakers to design futures contracts to improve the efficiency of the agricultural commodity derivatives market.Practical implicationsThe findings provide fresh view on lead–lag relationship between future and spot prices using the latest data confirming that futures market indeed is dominant in price discovery.Originality/valueThere are very few studies that have explored the efficiency of the agricultural commodity spot and futures markets in India using both price discovery and volatility spillover in a detailed manner, especially at the individual agriculture commodity level.

scholarly journals PRICE DISCOVERY AND VOLATILITY TRANSMISSION IN AUSTRALIAN REIT CASH AND FUTURES MARKETS

2016 ◽  
Vol 20 (2) ◽  
pp. 113-129 ◽  
Author(s):  
Ming-Te LEE ◽  
Shew-Huei KUO ◽  
Ming-Long LEE ◽  
Chyi Lin LEE
Keyword(s):  
Futures Markets ◽  
Price Discovery ◽  
Futures Market ◽  
Real Estate Investment Trust ◽  
Real Estate Investment ◽  
Index Futures ◽  
Volatility Transmission ◽  
Volatility Spillovers ◽  
Cash Market ◽  
The Relationship

This study examines the price discovery function and volatility spillovers in australian real estate investment trust (A-REIT) index futures and also investigates the effects of the global fi- nancial crisis (gfc) on these two features. as opposed to the general understanding of the relationship between the cash and the futures markets, the current study finds that the A-REIT cash market led the a-reIt futures market in price discovery and volatility transmission processes before the gfc. However, during the GFC, the two markets interacted bilaterally in terms of information flow, i.e., in- formation flowed in both directions. Furthermore, after the GFC, the futures market followed the cash market again, but less closely. These findings have broad implications for investors in property assets.

Generation of phases I and II of migrating myoelectric complex in the dog

1986 ◽  
Vol 251 (2) ◽  
pp. G201-G207 ◽  
Author(s):  
I. M. Lang ◽  
S. K. Sarna ◽  
R. E. Condon
Keyword(s):  
Small Intestine ◽  
Phase I ◽  
Phase Ii ◽  
Migration Time ◽  
Phase Iii ◽  
Myoelectric Activity ◽  
Migrating Myoelectric Complex ◽  
Fasted State ◽  
Intestinal Length ◽  
Highly Correlated

The mechanisms of generation of most of the phases of the migrating myoelectric complex (MMC) are unclear. Except for phase III activity, this issue has not been investigated directly. We have qualitatively examined the relations between different phases of the MMC cycle in order to provide an objective basis for the formation of theories. Eight dogs of either sex were implanted with 10 bipolar electrodes distributed along the gastrointestinal tract. Myoelectric activity was recorded during the fasted state or after feeding until the return of the MMC cycle. The relations between phase I duration, phase II duration, phase III migration time, and phase III period were examined using simple linear-regression methods. We found that only phase I duration was highly correlated (r = 0.87, P less than 0.01) with phase III migration time and that only phase II duration was highly correlated (r = 0.90, P less than 0.01) with phase III period. In either the fed or fasted state, phase III activity that began in the midjejunum was accompanied concurrently with phase I activity of the duodenum and upper jejunum, where phase III activity had not occurred. Also, the position of phase III activity in the lower small intestine when phase I activity of the upper small intestine ended was 277 +/- 24 cm (83 +/- 5% of the small intestinal length) from the pylorus, and the coefficient of variation of this position was significantly smaller (P less than 0.01) than that of the other cycle variables.(ABSTRACT TRUNCATED AT 250 WORDS)

VOLATILITY AND LIQUIDITY ON HIGH-FREQUENCY ELECTRICITY FUTURES MARKETS: EMPIRICAL ANALYSIS AND STOCHASTIC MODELING

2020 ◽  
Vol 23 (04) ◽  
pp. 2050027
Author(s):  
MARCEL KREMER ◽  
FRED ESPEN BENTH ◽  
BJÖRN FELTEN ◽  
RÜDIGER KIESEL
Keyword(s):  
Monte Carlo ◽  
Stochastic Models ◽  
Continuous Time ◽  
High Frequency ◽  
Futures Markets ◽  
A Priori ◽  
Futures Market ◽  
Futures Prices ◽  
Volatility Function ◽  
The Relationship

This paper investigates the relationship between volatility and liquidity on the German electricity futures market based on high-frequency intraday prices. We estimate volatility by the time-weighted realized variance acknowledging that empirical intraday prices are not equally spaced in time. Empirical evidence suggests that volatility of electricity futures decreases as time approaches maturity, while coincidently liquidity increases. Established continuous-time stochastic models for electricity futures prices involve a growing volatility function in time and are thus not able to capture our empirical findings a priori. In Monte Carlo simulations, we demonstrate that incorporating increasing liquidity into the established models is key to model the decreasing volatility evolution.

scholarly journals MODELLING VOLATILITY SPILLOVER BETWEEN CONVENTIONAL AND ISLAMIC STOCK INDEX IN MALAYSIA

2020 ◽  
Vol 10 (2) ◽  
pp. 26-32
Author(s):  
Edin Djedović ◽  
◽  
Ugur Ergun ◽  
Irfan Djedović ◽  
◽  
...  
Keyword(s):  
Garch Model ◽  
Stock Index ◽  
Cointegration Test ◽  
Volatility Spillover ◽  
Long Run ◽  
Johansen Cointegration ◽  
Short Run ◽  
Two Indices ◽  
Johansen Cointegration Test ◽  
The Relationship

This paper analyzes the vollatility spillover between the conventional index in Malaysia FTSE Malaysia KLCI (KLSE) and the Islamic index in Malaysia FTSE Bursa Malaysia Shariah Index (FTFBMHS). Monthly observations spanning in a period from 2002 to 2018 are obtained from investing.com database. GARCH model and Johansen cointegration test are used to investigate volatility spillover and the relationship between two indices. The results of the analysis indicate that in the short-run there is volatility spillover between FTSE Malaysia KLCI and FTSE Bursa Malaysia Shariah Index, while in the long-run there is no relationship between the two indices. The methodology of compiling Islamic indeces is based on Shariah law. Keywords: Conventional

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