scholarly journals The Role of Observability in Futures Markets

2006 ◽  
Vol 6 (1) ◽  
Author(s):  
José Luis Ferreira

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.

2021 ◽  
Vol 9 ◽  
Author(s):  
Yinpeng Zhang ◽  
Panpan Zhu ◽  
Yingying Xu

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.


2016 ◽  
Vol 4 (9) ◽  
pp. 143-150
Author(s):  
Shafeeque Muhammad ◽  
Thomachan

This paper examines the role of commodity futures market as an instrument of hedging against price risk. Hedging is the practice of offsetting the price risk in a cash market by taking an opposite position in the futures market. By taking a position in the futures market, which is opposite to the position held in the spot market, the producer can offset the losses in the latter with the gains in the former. Both static and time varying hedge ratios have been calculated using VECM-MGARCH model. Variance of return from hedge portfolio has been found to be low. Further hedging effectiveness has been observed to be around 12%.


2010 ◽  
Vol 35 (2) ◽  
pp. 49-62 ◽  
Author(s):  
T Mallikarjunappa ◽  
E M Afsal

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.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mincheol Woo ◽  
Meong Ae Kim

The National Pension Service (NPS) of Korea is one of the largest institutional investors in the world and it has been known as the market stabilizer in the Korean stock market. Nevertheless, it is hard to find the research about the impact of the NPS on the futures market. We investigated the effect of the NPS’s trading KOSPI200 futures on the returns, the liquidity and the volatility of the market using the recent ten years’ transaction data. The main findings are as follows. First, the NPS’s net investment flow (NIF) in the KOSPI200 futures market shows the predictability about the returns of both KOSPI200 futures and KOSPI200 spot index. Second, the NPS’s NIF in the KOSPI200 futures market improves the liquidity of the KOSPI market, where the transactions involved in both the spot market and the futures market occur. Third, the NPS’s NIF in the KOSPI200 futures market reduces the volatility of both the KOSPI200 futures market and the KOSPI market. Unlike the prior studies showing that our futures market tends to increase the volatility of the stock market through the volatility transfer, our finding suggests that the NPS’s trading KOSPI200 futures contributes to decreasing the volatility in both markets. To the best of the authors’ knowledge, this paper is the first study that investigates the impact of the NPS’s trading KOSPI200 futures on the KOSPI200 futures market and the stock market. It shows that the NPS plays a role of the market stabilizer in the futures market. In addition, the NPS’s trading KOSPI200 futures also affects the KOSPI stock market, stabilizing it in terms of both the liquidity and the volatility.


2006 ◽  
Vol 11 (2) ◽  
pp. 107-121 ◽  
Author(s):  
Safi Ullah Khan

This paper focuses on the role of the financial futures market in the volatility of Pakistan’s stock market and determines whether the stock futures price is capable of providing some relevant information for predicting the spot price. The Generalized Autoregressive Conditional Heteroscedasticity (GARCH) approach is used to measure volatility in the spot and the futures market and to analyze the relationships between spot and futures market volatility. Causality and feedback relationships between the two markets are analyzed and determined through the Vector Error Correction Model (VECM). Empirical results support the evidence that spot prices generally lead the futures prices in incorporating new information, and that volatility in the futures market does not increase volatility in the spot market. Rather the study finds more consistent support for the alternative hypothesis that volatility in the futures market may be an outgrowth of the volatile spot market.


Author(s):  
Shaik Masood ◽  
T. Satyanarayana Chary

The paper studies the Indian commodity futures market in order to determine the price discovery, long run market efficiency and short run dynamics in futures market using by time series analysis tools. To test the market efficiency and long run equilibrium, tools like Engle and Granger co-integration test (1987) and Johansen co-integration test (1988) have been applied. The Granger Causality (1969) test is used test the market efficiency to infer cause and affect relationship between spot and futures market in India. To examine efficiency of commodity futures and spot market the MCXs1 four spot and futures commodity indices data are used. The paper observes that the role of commodity futures is very significant in price discovery, and improving efficiency of the market.


2011 ◽  
Vol 19 (3) ◽  
pp. 233-249
Author(s):  
Sang Hoon Kang ◽  
Seong-Min Yoon

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.


2020 ◽  
pp. 097265272092762
Author(s):  
M. Thenmozhi ◽  
Shipra Maurya

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


2016 ◽  
Vol 41 (2) ◽  
pp. 132-148 ◽  
Author(s):  
Meenakshi Malhotra ◽  
Dinesh Kumar Sharma

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.


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