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.

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.

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.

Crude Oil Volatility Transmission Across Food Commodity Markets: A Multivariate BEKK-GARCH Approach

2020 ◽  
pp. 097265272092762
Author(s):  
M. Thenmozhi ◽  
Shipra Maurya
Keyword(s):  
Crude Oil ◽  
Futures Markets ◽  
Spot Market ◽  
Futures Market ◽  
Spot Price ◽  
Volatility Spillover ◽  
Oil Futures ◽  
Long Run ◽  
Short Run ◽  
Crude Oil Futures

This study examines the time-varying price risk transmission in the nexus between crude oil and agricultural commodity prices in the context of non-grain-based biofuel producing country. Analysis of the short- and long-run dynamics of volatility in both spot and futures markets of maize, soybean and wheat and crude oil prices using the multivariate BEKK-GARCH model, indicate volatility spillover from wheat futures to crude oil futures in the short run and from crude oil futures to futures markets of maize, soybean and wheat in the long run. The spot market linkage of selected commodities is weaker compared to futures market, wherein maize spot volatility transmits to crude oil spot market in the longer period and no spillover between crude oil-food spot market is observed in the short run. The hedge ratios indicate that a dynamic hedging strategy is crucial for efficient risk management and the portfolio weights in futures market are more than the spot market. The results reveal that cross-market volatility spillover is more evident in the futures market, while own past conditional volatility is more significant in spot price discovery and risk transmission is evident among food commodities futures markets. JEL Codes: G13, G14, Q11, Q18, Q02

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.

Does Commodity Derivatives Function Effectively? A lengthy Discussion

2021 ◽  
pp. 227797522098574
Author(s):  
Bhabani Sankar Rout ◽  
Nupur Moni Das ◽  
K. Chandrasekhara Rao
Keyword(s):  
Price Discovery ◽  
Spot Market ◽  
Futures Market ◽  
The Other ◽  
Volatility Spillover ◽  
Agricultural Commodities ◽  
Commodity Derivatives ◽  
Derivative Market ◽  
Negative Shock ◽  
Lengthy Discussion

The present work has been designed to intensely investigate the capability of the commodity futures market in achieving the aim of price discovery. Further, the downside of the cash and futures market and transfer of the risk to other markets has also been studied using VaR, and Bivariate EGARCH. The findings of the work point that the metal commodity derivative market helps in the efficient discovery of price in the spot market except for nickel. But, in the case of the agricultural commodities, the spot is found to be leading and thus there is no price discovery except turmeric. On the other hand, the volatility spillover is bidirectional for both agri and metal commodities except copper, where volatility spills only from futures to spot. Further, the effect of negative shock informational bias differs from commodity to commodity, irrespective of metal or agriculture.

Price Discovery Process and Volatility Spillover in Spot and Futures Markets: Evidences of Individual Stocks

2010 ◽  
Vol 35 (2) ◽  
pp. 49-62 ◽  
Author(s):  
T Mallikarjunappa ◽  
E M Afsal
Keyword(s):  
Futures Markets ◽  
Price Discovery ◽  
Spillover Effect ◽  
Spot Market ◽  
Futures Market ◽  
Discovery Process ◽  
Short Term ◽  
Asymmetric Volatility ◽  
Spot Volatility ◽  
Price Discovery Process

This paper analyses information-based superiority of markets mainly with an objective of exploring arbitrage opportunities. It attempts to determine the lead-lag relationship between spot and futures markets in the Indian context by using high frequency price data of twelve individual stocks, observed at one-minute interval. The study applies the concept of co-integration and establishes the spot-futures relationship using Vector Error Correction Mechanism (VECM) represented by EGARCH framework. To study the price discovery process in the two markets, five lags each of one-minute resolution for nine individual stocks and four lags for the remaining three stocks are chosen. The key results of the study are given below: There is a contemporaneous and bi-directional lead-lag relationship between the spot and futures markets. A feedback mechanism of short life is functional between the two markets. Price discovery occurs in both the markets simultaneously. There exists short-term disequilibrium that could be corrected in the next period. Volatility spillover from spot market to futures market is present in such a way that a decrease in spot volatility leads to a decrease in futures volatility. Volatility shocks are asymmetric and persistent in both the markets. Spillover from futures market to spot market is not significant. Neither spot nor futures assume a considerable leading role and neither of the markets is supreme in price discovery. In the case of 33.33 per cent of spot values and 33.33 per cent of futures values, there exists short-term disequilibrium that could be corrected in the next period by decreasing the prices. Spot market volatility spills over to futures market in most of the cases (66.66 %) and a decrease in spot volatility brings about a decrease in futures volatility in 50 per cent of the cases. Spillover effect from futures to spot market is present and significant in 91.66 per cent of stocks and is more than the spillover effect from spot to futures (50% valid cases). The markets are highly integrated. Asymmetric behaviour of volatility shocks is mixed in both the markets. Asymmetric volatility is detected in 50 per cent of the cases of spot market and 58.33 per cent cases of futures market. Stocks exhibiting asymmetric volatility show more sensitivity to negative shocks. There are no cases of market becoming more volatile in response to good news.

Wavelet-based analysis of guar futures in India: did we kill the golden goose?

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Arunava Bandyopadhyay ◽  
Souvik Bhowmik ◽  
Prabina Rajib
Keyword(s):  
Spot Market ◽  
Futures Market ◽  
Shale Oil ◽  
Volatility Spillover ◽  
Short Term ◽  
Content Type ◽  
Business Ecosystem ◽  
Excessive Speculation ◽  
The Impact ◽  
Economic Linkages

PurposeGuar Gum (GG) is used in Shale oil exploration. Excessive price increase in the Guar futures market had a spillover impact on Guar spot prices and affected Guar export from India as Shale oil producers started exploring alternate sources. In this paper, the role of excessive speculation in the futures market, and its adverse impact on the guar-based agri-business ecosystem have been empirically explored.Design/methodology/approachVolatility spillover dynamics between WTI crude oil and Guar futures have been explored using bivariate-Granger Causality, BEKK–GARCH models with Wavelet multi-resolution analysis. The wavelet-based models capture the multi-scale features of mean and volatility spillover to identify the effect of heterogenous investment behavior in the time and frequency domain.FindingsThe results provide evidence that excessive speculation in futures markets increases spot market volatility. The results also suggest that the excess presence of short-term investors can destabilize the futures market.Research limitations/implicationsThe purpose of the commodity futures market is to support price discovery and risk management. However, speculative practices can destabilize these purposes leading to the failure of the business ecosystem.Originality/valueThe novelty of this paper is twofold. First, it explores the economic linkages between the spot and futures market and tests whether the presence of heterogeneous traders affects the economic linkages. Second, it models the impact of short-term speculative investment on the destabilization of the spot market.

scholarly journals The Role of Observability in Futures Markets

2006 ◽  
Vol 6 (1) ◽  
Author(s):  
José Luis Ferreira
Keyword(s):  
Futures Markets ◽  
Spot Market ◽  
Futures Market ◽  
Alternative Formulation ◽  
Competitive Outcomes ◽  
Imperfect Observability

Allaz (1992) and Allaz and Vila (1993) show that in an oligopolistic industry the introduction of a futures market that operates prior to the spot market induces more competitive outcomes. Hughes and Kao (1997) show that this result presumes that firms' future positions are perfectly observed, and that when firms' positions are not observed the Cournot outcome arises. We study an alternative formulation of observability, where the behavior of participants in the futures market is explicitly analyzed, and show that this approach leads to different results. Imperfect observability induces more competitive outcomes than Allaz and Vila's model.

scholarly journals Currency and Index Futures Markets Dynamics: Asymmetric Volatility, Leverage Effects and Long-memory Characteristics

2021 ◽  
Vol 39 (3) ◽  
Author(s):  
John Francis Diaz ◽  
Kai-Hong Goh, Imba Goh
Keyword(s):  
Long Memory ◽  
Futures Markets ◽  
Moving Average ◽  
Memory Models ◽  
Autoregressive Moving Average ◽  
Conditional Heteroskedasticity ◽  
Index Futures ◽  
Asymmetric Volatility ◽  
Autoregressive Conditional Heteroskedasticity ◽  
Asymmetric Power

This research examines the performance of return and volatility models on the long-memory, asymmetric volatility, and leverage effects by comparing the two most active futures markets globally, Currency and Index Futures. The study uses daily data from the database Quandl.com website, from January 2000 to March 2018. This study utilizes two short-memory models, the autoregressive moving average – exponential generalized autoregressive conditional heteroskedasticity (ARMA-EGARCH); and  autoregressive moving average – asymmetric power autoregressive conditional heteroskedasticity (ARMA-APARCH); and two long-memory models, autoregressive fractionally-integrated moving average – fractionally-integrated exponential generalized autoregressive conditional heteroskedasticity (ARFIMA-FIEGARCH); and autoregressive fractionally-integrated moving average – fractionally-integrated asymmetric power autoregressive conditional heteroskedasticity (ARFIMA-FIAPARCH). The paper shows that portfolio managers and traders can benefit in holding Index futures, because of their steady returns, but with a relatively higher risk for the whole sample period. The study also finds that Currency futures has better safe-haven properties during crisis period, but Index futures performs better after crisis period. Findings suggest that both long-memory models are capable of accurate forecast, especially on the volatility of Currency and Index futures. The proper modelling of Currency and Index futures time-series data can provide traders, fund managers and investors in creating well-defined trading strategies, especially in high volatility regimes.

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