chicago mercantile exchange
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2021 ◽  
Vol 10 ◽  
pp. 48-57
Author(s):  
S. Thomas Kim ◽  
Svetlana Orlova

This study examines how Bitcoin’s trading characteristics react to the COVID-19 pandemic, using detailed futures trading data from the Chicago Mercantile Exchange. The results show that volume-weighted Bitcoin futures return responds positively to the spikes of public interest. Meanwhile, the surges of pandemic information do not harm market quality. Volume, bid-ask spread, and trading frequency remain stable, indicating that the positive price reaction is not a result of a few small uninformed trades. Bitcoin's conditional beta on the S&P 500 index drops to near zero, while the conditional beta on gold more than doubles. These results indicate that traders have been using Bitcoin as a safe-haven asset after the pandemic outbreak.


Risks ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 111
Author(s):  
Jatin Malhotra ◽  
Angelo Corelli

This paper examines the relative contribution of regular and e-mini futures market to price discovery of EUR/USD futures contracts on the Chicago Mercantile Exchange (CME), using intraday data in 2010.The relative contribution to price discovery is estimated using the information share approach proposed by Hasbrouck and Gonzalo-Granger. Empirical findings indicate that regular futures market contributes significantly to the price discovery, accounting for approximately 66.5% of price discovery in the EURO/USD market. This study also examines if the regular future’s information share (IS) can be explained by the positioning of commercial and non-commercial traders. We find a positive significant relationship between IS and both the speculative trade position and hedgers trade position. The results support the conclusion that the IS of regular futures can be better explained by speculators than hedgers.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Omid Sabbaghi ◽  
Min Xu

PurposeThe study systematically investigates persistence in performance for simulated trading among non-professional traders in the futures market.Design/methodology/approachIn this study, the authors employ a novel data set from the Chicago Mercantile Exchange (CME) Group's Trading Challenges for years 2014 through 2018 and expand upon the empirical methodology of Malkiel (1995) through improved interval estimations in testing for persistence in performance. The authors implement Fama-MacBeth style regressions to understand the degree of persistence in performance and the extent to which non-professionals extrapolate from prior returns. They adjust returns for risk through the Fama and French (2015) five-factor model in understanding whether the sample of non-professionals is able to produce excess returns after expenses and whether there is evidence of excess gross to cover expenses.FindingsThe empirical analysis suggests strong evidence for performance persistence among non-professionals participating in the Preliminary Rounds. In the Championship Rounds, the authors find that the persistence effect becomes stronger in economic and statistical significance after accounting for expenses. The results suggest that competition and transaction costs help to distinguish between winners and losers. When conducting Fama-MacBeth style regressions, the authors present evidence that strongly supports the persistence effect and over-extrapolation. While the results of the multi-factor model analysis suggest that, after adjusting for risk, most teams are experiencing negative excess returns prior to expenses, the authors also uncover evidence of teams earning returns sufficient to cover their expenses.Originality/valueThe authors bridge the gap between the literature on performance persistence and the emerging literature on non-professionals in the financial markets. Data from the CME Group’s Trading Challenge provide a rich source in studying the beliefs of non-professionals, and this study is helpful for understanding how beliefs, operationalized in simulated trades, perform over short time horizons, thereby providing insights into the behavioral dynamics of the financial markets. The results provide new empirical evidence for performance persistence among non-professionals.


2019 ◽  
Vol 11 (15) ◽  
pp. 4144 ◽  
Author(s):  
Zofia Gródek-Szostak ◽  
Gabriela Malik ◽  
Danuta Kajrunajtys ◽  
Anna Szeląg-Sikora ◽  
Jakub Sikora ◽  
...  

The purpose of the article is to identify and estimate the dependency model for the extreme prices of agricultural products listed on the Chicago Mercantile Exchange. The article presents the results of the first stage of research covering the time interval 1975–2010. The selected products are: Corn, soybean and wheat. The analysis of the dependency between extreme price values on the selected futures was based on the estimation of five models of two-dimensional extreme value copulas, namely, the Galambos copula, the Gumbel copula, the Husler–Reiss copula, the Tawn asymmetric copula and the t-EV copula. The next stage of the analysis was to test whether the structure of the dependency described with the estimated copulas is a sufficient approximation of reality, and whether it is suitable for modeling empirical data. The quality of matching the estimated copulas to empirical data of return rates of agricultural products was assessed. For this purpose, the Kendall coefficient was calculated, and the methodology of the empirical combining function was used. The conducted research allowed for the determination of the conduct for this kind of phenomena as it is crucial in the process of investing in derivatives markets. The analyzed phenomena are highly dependent on e.g., financial crises, war, or market speculation but also on drought, fires, rainfall, or even crop oversupply. The conducted analysis is of key importance in terms of balancing agricultural production on a global scale. It should be emphasized that conducting market analysis of agricultural products at the Chicago Mercantile Exchange in the context of competition with the agricultural market of the European Union is of significant importance.


2018 ◽  
Vol 9 (1) ◽  
pp. 32-40 ◽  
Author(s):  
Chengyi Pu ◽  
Yueyun (Bill) Chen ◽  
Xiaojun Pan

This paper compares the weather insurance, weather index insurance and index futures and focuses on why China needs to develop weather indexes and adopt and trade weather index futures. It further discusses how to construct the indexes and futures and how to price them. Different from the Heating Degree Days (HDDs) and Cooling Degree Days (CDDs) used at Chicago Mercantile Exchange (CME), it develops the Extremely Heating Days (EHDs) and Extremely Cooling Days (ECDs) to derive relevant temperature-based weather index futures. Recently China has started using weather index insurance to cover farmers’ risk. Through comparisons of weather index futures with index insurance, this study shows the necessity and importance of using the weather index futures to better protect farmers and better develop China’s financial markets.


2018 ◽  
Vol 20 (4) ◽  
pp. 443-460 ◽  
Author(s):  
Ahmad Kameel Mydin Meera

Cryptocurrencies’ popularity has surged during the last few years. This isespecially the case of bitcoin, one among cryptocurrencies which price has soaredfrom USD1,000 in the first quarter of 2017 to USD20,000 by the end of 2017. Ithas now being used by merchants as a medium of exchange. Upon realizing itspopularity, the CME Group that owns the Chicago Mercantile Exchange launcheda futures contract on bitcoin. Yet, there are cases where bitcoin is banned bythe country. This article examines the implication of bitcoin on Islamic financeand questions its acceptance as a medium of exchange (money) based on itscompliancy with shari’ah. By analyzing its nature and characteristics, the paperconcludes that, strictly speaking, cryptocurrencies that are not backed with realassets are not shari’ah-compliant. However, the majority of shari’ah scholarsare leaning towards approving bitcoin on maslahah basis. Bitcoin is neither fiatmoney nor real money. The absence of an intrinsic value coupled with lack orzero supervision by the central bank will result in misusing bitcoin. Furthermore,we content that it has the elements of maysir and gharar. This can contributetowards socio-economic injustices, thereby jeopardizing the maqasid al-shari’ah.Hence, based on a thorough analysis, we conclude that fiat cryptocurrencies arenot shari’ah compliant. However, gold-backed cryptocurrencies are argued to bedesirable and consistent with the maqasid al shari’ah.


Author(s):  
Karl Schmedders ◽  
Patrick Johnston ◽  
Charlotte Snyder

The financial success of dairy farms depends critically on the price of their main output, milk. Large volatility in the price of milk poses a considerable business risk to dairy farms. This is particularly true for family-run dairy farms. The question then arises: how can a farm owner hedge the milk price risk? The standard approach to establish a price floor for a commodity such as milk is to purchase put options on commodity futures. At the Chicago Mercantile Exchange, farmers can buy put options on the price of a variety of milk products. However, the price a farm receives for its milk depends on many factors and is unique to the farm. Thus, a farmer cannot directly buy put options on the price he receives for the milk his farm produces. Instead the farmer needs to determine which of the options available for trade at the Chicago Mercantile Exchange offer the best hedge for his own milk price. The assignment in this case is to examine historical data on several prices of milk products and the milk price received by a family-run dairy farm in California. Students need to find the price that is most closely correlated to the farm's milk price and to then choose options with the appropriate strike price that serve as the best hedge for the farm's price risk.The objective is to expose students to an interesting but simple finance application of linear regression analysis. To solve the case, students must run several simple linear regressions, then use the best regression model they find to make a prediction for the dependent price variable and analyze the prediction interval in order to achieve the desired objective outlined in the case. By completing the case, students will acquire a good understanding of their regression model and its usefulness.


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