A Study on the Correlation between Baltic Dry Index and China’s Nonferrous Metal Futures Market Price

2021 ◽  
Vol 22 (4) ◽  
pp. 271-302
Author(s):  
Eun Jeong Yoo ◽  
Ki Bo Ku
Keyword(s):  
Nonferrous Metal ◽  
Market Price ◽  
Futures Market ◽  
Baltic Dry Index

Crop price insurance in China: pricing and hedging using futures market

2017 ◽  
Vol 9 (4) ◽  
pp. 567-587 ◽  
Author(s):  
Minghua Ye ◽  
Rongming Wang ◽  
Guozhu Tuo ◽  
Tongjiang Wang
Keyword(s):  
Market Price ◽  
Futures Market ◽  
Insurance Premium ◽  
Spot Price ◽  
Agricultural Commodity ◽  
Content Type ◽  
Price Series ◽  
Insurance Firms ◽  
Price Insurance ◽  
S Model

Purpose The purpose of this paper is to demonstrate how crop price insurance premium can be calculated using an option pricing model and how insurers can transfer underwriting risks in the futures market. Design/methodology/approach Based on data from spot and futures market in China, this paper develops an improved B-S model for the calculation of crop price insurance premium and tests the possibility of hedging underwriting risks by insurance firms in the futures market. Findings The authors find that spot price of crops in China can be estimated with agricultural commodity futures prices, and can be taken as the insured price for crop price insurance. The authors also find that improved B-S model yields better estimation of crop price insurance premium than traditional B-S model when spot price does not follow geometric Brownian motion. Finally, the authors find that hedging can be one good alternative for insurance firms to manage underwriting risks. Originality/value This paper develops an improved B-S model that is data-driven in nature. Insured price of the crop price insurance, or the exercise price used in the B-S model, is estimated from a co-integration model built on spot and futures market price series. Meanwhile, distributional patterns of spot price series, one important factor determining the applicability of B-S model, is factored into the improved B-S model so that the latter is more robust and friendly to data with varied distributions. This paper also verifies the possibility of hedging of underwriting risks by insurance firms in the futures market.

A Comparative Analysis of Informational Efficiency of KOSDAQ50 and KOSPI200 Index Futures

2003 ◽  
Vol 11 (2) ◽  
pp. 27-49
Author(s):  
Bae Gi Hong ◽  
Su Jae Jang
Keyword(s):  
Futures Markets ◽  
Market Price ◽  
Futures Market ◽  
Spot Price ◽  
Informational Efficiency ◽  
Information Efficiency ◽  
Index Futures ◽  
Volume Relationship ◽  
Futures Price ◽  
Volume Relation

This paper examines the information efficiency of KOSDAQ50 and KOSPI200 index futures markets. The study analyzes and compares both markets in three respects : 1) price discovery (lead-lag relationship between spot and futures markets.), 2) volatility-volume relationship, and 3) mispricings between spot and futures prices. The first, analysis shows the in the KOSPI200 market, futures price leads spot price. While spot price leads futures price in the KOSDAQ50 market. The second analysis shows that the volatility-volume relation is positive in the KOSPI200 futures market, supporting the hypothesis of mixture of distribution. In contrast, there is little relation between volume and volatility in the KOSDAQ50 futures market. This result casts doubt that the futures market price reflects information. The last analysis shows that the magnitude of mispricing becomes smaller with more volume in the KOSPI200 futures market, while it becomes larger with more volume in the KOSDAQ50 futures market. The overall results imply that the KOSDAQ50 futures market is less informationally efficient that the KOSPI200 market. The inefficiency appears due to the lack of institutional investor participation, especially securities firms, in making up the market.

scholarly journals Nonlinear relationship between carbon market and energy market

2021 ◽  
Vol 275 ◽  
pp. 02046
Author(s):  
Yan Li
Keyword(s):  
Stock Market ◽  
Stock Price ◽  
Market Price ◽  
Futures Market ◽  
Carbon Market ◽  
Var Model ◽  
Energy Market ◽  
Nonlinear Relationship ◽  
Energy Futures ◽  
New Energy

This paper divides the energy market into energy futures market and new energy stock market. At the same time, the closing price of Shenzhen carbon emission rights is used to represent the carbon market price, the energy futures composite index of China Securities Exchange is used to represent the energy futures market price, and the stock price of new energy listed companies is used to represent the new energy stock market price. VAR model and MSVAR model are used to empirically study the relationship between the three variables and the nonlinear relationship between them. VAR model results show that there will be more complex relationship among carbon market price, energy company stock price and energy futures price. MSVAR model shows that the energy futures market, new energy stock market and carbon market present nonlinear and structural changes, and MSVAR model can better explain the nonlinear relationship among the three markets than traditional VAR model.

Cross market price support and agricultural development

2014 ◽  
Vol 15 (1) ◽  
pp. 33-51 ◽  
Author(s):  
Leslie J. Verteramo Chiu ◽  
Calum G. Turvey
Keyword(s):  
Developing Countries ◽  
Exchange Rate ◽  
Market Price ◽  
Futures Market ◽  
Insurance Premium ◽  
Relative Price ◽  
Price Support ◽  
Content Type ◽  
Price Insurance ◽  
Agricultural Price

Purpose – This paper aims to develop a market-driven mechanism for commodity price insurance in developing countries lacking access to futures markets or other forms of hedging products. Design/methodology/approach – The model incorporates futures, exchange rate and local basis risk under the Black-Scholes framework to develop quanto (quantity adjusting option). When the domestic price of a commodity in a developing country is strongly correlated to the price in a futures market, price support premiums can be estimated. The authors use daily corn futures prices, exchange rate MXP/USD, and prices of corn and sorghum at several locations in Mexico. Findings – The authors calculated the price insurance premium at various local markets in Mexico for corn and sorghum. The results are consistent with those for the USA, showing that relative price premiums are similar. Research limitations/implications – The results provide a benchmark to estimate the net welfare effects of government programs for agricultural price support. Practical implications – The model shows that privately provided agricultural price insurance is feasible under certain conditions for developing countries without an established futures market. Originality/value – This paper provides market-based agricultural options in Mexico which contributes to the existing government price support program.

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