Intraday Price Dynamics between EUAs and CERs in the European Carbon Futures Market

2011 ◽  
Author(s):  
Vicente Medina ◽  
Ángel Pardo Tornero ◽  
Roberto Pascual
2015 ◽  
Vol 10 (2) ◽  
Author(s):  
Waldemar Souza ◽  
João Martines Filho ◽  
Claudio Zancan ◽  
Antonio C. S. Costa ◽  
Andreza G. A. Queiróz

World rice production reached 488.4 thousand tons, in 2012. Asian countries are the world’s largest rice producers, followed by Latinamerica, particularly Brazil, where rice is a basic food item. In spite of the clear economic benefits bestowed by commodity futures markets, neither Asia nor Mercosur have implemented a regional rice futures market. In sum, we propose to investigate the feasibility of a Brazilian rice futures contract to serve the Mercosur region by estimating Mercosur rice price dynamics and analyze basis risk and hedging effectiveness for rice market agents in the region, in a simulation framework using a hypothetical regional contract price. Sample data and period was non-probabilistic, for accessibility and convenience. Mercosur rice price dynamics expressed Argentina and Uruguay rice prices moving in synchrony. Brazil rice prices were on lower levels. Also, all three pairs of rice price series are cointegrated, with one cointegrating equation. Again, results can be largely attributed to the different price data used, in Brazil was rough rice, while in Uruguay and Argentina milled white rice with 5%. Despite that, there are preliminary evidences that a Mercosur rice futures market could be feasible.


2014 ◽  
Vol 29 ◽  
pp. 372-379 ◽  
Author(s):  
Meng-Yi Tai ◽  
Chi-Chur Chao ◽  
Shih-Wen Hu ◽  
Ching-Chong Lai ◽  
Vey Wang

2021 ◽  
Vol 96 ◽  
pp. 105149
Author(s):  
Kun Yang ◽  
Yu Wei ◽  
Shouwei Li ◽  
Liang Liu ◽  
Lei Wang

2017 ◽  
Author(s):  
Piyush Tiwari ◽  
Alla Koblyakova ◽  
John Croucher ◽  
Justine Wang

2019 ◽  
Vol 118 (3) ◽  
pp. 137-152
Author(s):  
A. Shanthi ◽  
R. Thamilselvan

The major objective of the study is to examine the performance of optimal hedge ratio and hedging effectiveness in stock futures market in National Stock Exchange, India by estimating the following econometric models like Ordinary Least Square (OLS), Vector Error Correction Model (VECM) and time varying Multivariate Generalized Autoregressive Conditional Heteroscedasticity (MGARCH) model by evaluating in sample observation and out of sample observations for the period spanning from 1st January 2011 till 31st March 2018 by accommodating sixteen stock futures retrieved through www.nseindia.com by considering banking sector of Indian economy. The findings of the study indicate both the in sample and out of sample hedging performances suggest the various strategies obtained through the time varying optimal hedge ratio, which minimizes the conditional variance performs better than the employed alterative models for most of the underlying stock futures contracts in select banking sectors in India. Moreover, the study also envisage about the model selection criteria is most important for appropriate hedge ratio through risk averse investors. Finally, the research work is also in line with the previous attempts Myers (1991), Baillie and Myers (1991) and Park and Switzer (1995a, 1995b) made in the US markets


2020 ◽  
Vol 42 (1) ◽  
pp. 33-46
Author(s):  
Raúl Gómez-Martínez ◽  
Camila Marqués-Bogliani ◽  
Jessica Paule-Vianez

Behavioural finance has shown that investment decisions are the result of not just rational but also emotional brain processes. On the assumption that emotions affect financial markets, it would seem likely that football results might have a measurable effect on financial markets. To test this, this study describes three algorithmic trading systems based exclusively on the results of three top European football teams (Juventus, Bayern München and Paris St Germain) opening long or short positions in the next market season of the futures market of the index of each country (MIB (Milano Italia Borsa), DAX (Deutscher Aktien Index) and CAC (Cotation Assistée en Continu). Depending on the outcome of the last game played a long position was taken after a victory and a short position after a draw or defeat. The results showed that the algorithmic systems were profitable in the case of Juventus and Bayern whereas in the case of PSG, the system was profitable, but in an inverse way. This study shows that investment strategies that take account of sports sentiment could have a profitable outcome.


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