VOLATILITY CONTAGION AMONG STOCK, CURRENCY, AND BULK SHIPPING MARKET DURING THE CHINA’S STOCK MARKET CRASH CRISIS

Six financial markets were verified contagious to Shanghai Stock Exchange Composite (SSEC): domestic equity market (SSEC and China COSCO Shipping Co.), domestic currency market, international currency market, global shipping market, commodity future market and bulk shipping market (BDI) which regarded as a leading indicator of future economic growth instead of Li Keqiang index. This research analyzed intermarket contagion from March 14, 2008 to March 31, 2018. MIDAS-GARCH model was adopted to identify the spillover effect among the Shanghai Stock market and inter-market indices. The findings of this study were concluded as follows: (1) The commodity, global shipping market had significant volatility transmission to SSEC both before and after the crash crisis. (2) The volatility of domestic currency market was significantly contagious to SSEC only after the crash.

Relationship between Commodity Future Trading with Spot Prices Variation and Inflation with special reference to Indian Agriculture Market

Environmental education is very important issue. It is duty of teacher to inculcate environmental awareness among students. Students in Indian school come from diverse background .Some may not have easy access to technology. As 21st century educators it is our duty to find strategies that level the educational playing field for all learners. Teachers can foster the student engagement in activities that support appreciation of the environment and natural resources in understanding the environmental issues. Across the nation ,schools are increasing access to technologies in the classroom. Therefore, providing education with appropriate resources and strategies supports environmental literacy should be essential component of all technology plans.

Forecasting of Commodity Future Index using a Hybrid Regression Model based on Support Vector Machine and Grey Wolf Optimization Algorithm

The forecasting and investigation of finance time series data are hard, and are the most confounded works pertained with investor decision. In this paper, an economic derivative instrument for Multi Commodity Exchange (MCX) index of CRUDEOIL is estimated by utilizing forecasting models based on recently formulated artificial intelligence (AI) approaches. These approaches have been appeared to perform astoundingly well in different optimization problems. Specifically, a novel hybrid forecasting model is designed by combining the support vector machine (SVM) and grey wolf optimization (GWO) and it is named as hybrid SVM-GWO. The presented hybrid SVM-GWO model eliminates the user determined control parameter, which is needed for other AI techniques. The practicality and proficiency of the presented SVM-GWO regression method is evaluated by predicting the everyday close price of CRUDEOIL index traded in the MCX of India Limited. The exploratory outcomes depicts that the present hybrid SVM-GWO technique is viable and outperforms superior to the conventional SVM, hybrid SVM-TLBO and SVM-PSO regression models

Attitude of Individual Investors towards Commodity Trading in Disruptive Technological Era

The commodity future trading is one of the major investment avenues. But, still the people are preferred to conventional investment avenues like gold and real assets. At this juncture, the present study has focused on attitude and satisfaction of investors towards commodity market. Thus, this study helpful to understand the preferred commodity, objectives of investment, techniques for managing risks, reasons for investing in commodities and problems in commodity trading. The study identified that investors are invested in commodities as well as other diversified investment avenues. Low risk is a prime reason for investing in the commodities. The investors are highly satisfied with the return from the commodity trading. The study results helpful to the financial planners and brokers for understanding pulse of the investors.

Commodity Future Money Flows Trading Strategies Based on HMM

This paper aims to establish a quantitative trading strategy of commodity futures based on market money flows. Firstly, we use Accumulation/Distribution index to respectively construct the CMF index which represents the ratio of total capital flows to total volume, and the CHO index which represents the exponential moving average of the cumulative capital flows. In view of the different flows of money between buyers and sellers, the establishment of the transaction net volume index VTL is used to describe respectively the flow of money between buyers and sellers. On this basis, the HMM model is introduced, and the above three kinds of indexes are combined to choose the time, at which we execute the stop-loss operation and risk control. Finally, all performance index values of the strategy are as follows: the rate of initial capital return is 193.77%, the annual rate of return is 99.86%, the maximum retracement rate is 15.73%, the Sharpe rate is 2.05 and the price earnings ratio is 4.01.