• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• Journal of the Korean Geographical Society
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• v.44 no.6
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• pp.723-744
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• 2009

The purpose of this paper is to clarify the prospects and problems in the study of geography related to the concept of commodity, transport, and supply chains. The geography studies related to commodity chains are expanded to each field of industry focusing on the subjects and economic difference which lead the commodity chain in core and periphery regions. These vertical connection are studied with the political economy approach that gives attention to geographical pattern of agricultural products and foods. But in viewpoint of commodity circuit and commodity network, the culture or subjects of micro regions and interaction are also studied. The contents of these study are to clarify the importance of cultural turn and local. And the study of chain standpoint appears that the series of transport process by transportation modes can be understood by transport chains and the physical distribution process of sea freight is to be grasped by supply chains.

• International Commerce and Information Review
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• v.9 no.4
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• pp.67-89
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• 2007

The purpose of this study is to find out current problems facing the Commodity Trust of Internet Shopping Mall and to suggest proper solutions. the Commodity Trust of Internet Shopping Mall recently emerged as ubiquitous business environment that is not this only sales promotion but the Commodity Trust. Now we should have focused on the cooperation among the organizations in the Commodity Trust of Internet Shopping Mall; need various kind of government aids; need marketing-oriented and professional skills to build and enhance the growth of trade show exhibition industry. Accordingly, the important thing is an exploratory study of assessing the Commodity Trust of Internet Shopping Mall etc.

• The KIPS Transactions:PartD
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• v.10D no.7
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• pp.1225-1230
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• 2003

Many cyber-shopping malls use various commodity recommendation methods. Although the detailed algorithms are not disclosed to the public, they mostly rely on relatively simple and straightforward methods. This paper intends to improve the commodity recommendation by using a multi-stage algorithm which considers factors that are characteristics of the commodity itself, of the consumer group, and of the individual customer. A comparison table is provided which shows whether there is a change in commodity recommendation as we consider more factors about the customer.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.11
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• pp.107-120
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• 2021

The development of the ethnic minorities and mountainous areas (EMMA) is currently receiving the attention of countries around the world. This is demonstrated through a large number of studies, in many respects, in many different countries. The objective of the study is to find out the current situation of the commodity market in the ethnic minorities and mountainous areas (EMMA) of Vietnam. In particular, the authors will study whether there is a link between the ability to access governmental policies and the characteristics of this commodity market. To achieve the goal, the authors employed the secondary data collection method to gather the relevant information on government policies for EMMA and conducted an interview of seventy (70) enterprises in the Northern midlands and mountainous regions and the Central Coast to clarify the characteristics of commodity market. By Levene's test, the results showed that the accessibility to governmental policies has a certain influence on the development of the commodity market patterns in the EMMA in terms of diversification of distribution forms and sales method of the business. These findings brought some basic solutions to further enhance the role of the government in developing commodity markets in the EMMA of Vietnam.

• International Commerce and Information Review
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• v.16 no.1
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• pp.91-116
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• 2014

This study reviews the methodology for utilizing information technology by which even non-professionalists in FTAs and commodity classification area can perform the determination of commodity classification, with ease and by themselves, by means of easy utilization of the information on commodity classification and FTAs, of importing and exporting goods. This article examines the technological elements and logics, etc. which simulate the commodity classification for utilizing FTAs. To achieve this, the author has developed the technology to support the determination of commodity classification numbers by accumulating the database of examples for classification after analyzing the classification factors by each commodity item. Utilizing this Commodity Classification Determination Supporting System, users can enjoy effects of education as well as consulting. In this regards, the advantages of this system can be enumerated as followings : Firstly, self-checking on commodity classification can be performed. Secondly, time and cost for classification can be saved. Thirdly, comprehensive competitiveness will be enhanced by allowing traders to achieve the benefit of FTA preferential tariff, for they will be able to issue the Certificate of Origins on a more accurate and precise basis of commodity classification.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.179-185
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• 2016

This study verifies whether speculative trading in commodity markets acted as the primary cause of the increase in commodity prices after the global financial crisis using the Structural Vector Autoregressive (SVAR) model. The effects of speculative trading on commodity prices increased by a factor of 3 to 6 after the crisis compared to those before the crisis. Although the demand related variables, such as industrial production, affected commodity prices significantly before the crisis, their effects decreased after the crisis. Consequently, the rebound of commodity prices after the crisis was mainly caused by the increase in speculative money, fortified by the expansion of the global liquidity supply. The global liquidity may well increase in the future, because the U.S. Federal Reserve Board is likely to continue to increase its interest rate. This study claims that when global liquidity shrinks as a result of a change in the Fed's monetary policy stance, speculative trading will slow down, leading to a decline in commodity prices.

• Journal of Korea Trade
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• v.27 no.5
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• pp.167-198
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• 2023

Purpose - This paper aims to compare and analyze the co-movements and information spillover effects between the international commodity futures markets and the South Korean stock markets during the COVID-19 and the 2008 financial crises. Design/methodology - The DCC-GARCH model is used in the co-movements analysis. In contrast, the BEKK-GARCH model is used to evaluate information spillover effects. The statistical data used is from January 1, 2005, to December 31, 2022. It comprises the Korea Composite Stock Price Index data and daily international commodity futures prices of natural gas, West Texas Intermediate crude oil, gold, silver, copper, nickel, soybean, and wheat. Findings - The results of the co-movement analysis were as follows: First, it was shown that the co-movements between the international commodity futures markets and the South Korean stock markets were temporarily strengthened when the COVID-19 and 2008 financial crises occurred. Second, the South Korean stock markets were shown to have high correlations with the copper, nickel, and crude oil futures markets. The results of the information spillover effects analysis are as follows: First, before the 2008 financial crisis, four commodity futures markets (natural gas, gold, copper, and wheat) were shown to be in two-way leading relationships with the South Korean stock markets. In contrast, seven commodity futures markets, except for the natural gas futures market, were shown to be in two-way leading relationships with the South Korean stock markets after the financial crisis. Second, before the COVID-19 crisis, most international commodity futures markets, excluding natural gas and crude oil future markets, were shown to have led the South Korean stock markets in one direction. Third, it was revealed that after the COVID-19 crisis, the connections between the South Korean stock markets and the international commodity futures markets, except for natural gas, crude oil, and gold, were completely severed. Originality/value - Useful information for portfolio strategy establishment can be provided to investors through the results of this study. In addition, it is judged that financial policy authorities can utilize the results as data for efficient regulation of the financial market and policy establishment.

• Journal of the Chungcheong Mathematical Society
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• v.26 no.4
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• pp.787-791
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• 2013

In this paper we present one factor model of commodity prices with a single jump regime-switching process. And we derive an analytic formula for pricing futures contracts when the parameters of commoditiy process have governed by a Markov regime-switching process.

• Journal of applied mathematics & informatics
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• v.8 no.2
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• pp.519-530
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• 2001

A two commodity continuous review inventory system with independent Poisson processes for the demands is considered in this paper. The maximum inventory level for the i-th commodity fixed as $S_i$(i = 1,2). The net inventory level at time t for the i-th commodity is denoted by $I_i(t),\;i\;=\;1,2$. If the total net inventory level $I(t)\;=\;I_1(t)+I_2(t)$ drops to a prefixed level s $[{\leq}\;\frac{({S_1}-2}{2}\;or\;\frac{({S_2}-2}{2}]$, an order will be placed for $(S_{i}-s)$ units of i-th commodity(i=1,2). The probability distribution for inventory level and mean reorders and shortage rates in the steady state are computed. Numerical illustrations of the results are also provided.