• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.13-22
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• 2020

This research explores the appropriate rubber pricing model and the consistent empirical evidence. This model has been derived from the utility function and firm profit-maximization model of commodity goods. The finding shows that the period t - 1 affects expected commodity price and expected profit of commodity production. In fact, a change in the world price of rubber in the past period led to a change in the expected price of rubber in the short run which influenced the expected rubber profit. As a result, the past-period free on board price has an entirety effect on expected farm price of rubber given an exchange rate. In addition, the rubber pricing model indicates that the profit of local farmer on rubber plant depends solely on the world price of rubber in the short run in case of Thailand. In an empirical study, it was found that a change in the price of ribbed smoke sheet 3 in Singapore Commodity Exchange significantly and positively determined the fluctuation of rubber price at the farm gate in Thailand which was consistent with the behavior of the Thai farmers. Both prices are also cointegrated in the long run. That is, the result states that the VECM is an appropriated pricing model for forecasting the farm price in Thailand.

• Journal of Navigation and Port Research
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• v.45 no.2
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• pp.69-74
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• 2021

This study aims to investigate the lead-lag relationship between the agricultural produce import price in Korea and the corresponding shipping freight rate. Since the Korean economy has pursued an export-driven growth strategy, mainly based on the manufacturing sector, the country has to depend on the vast majority of its agricultural produce consumption after import from foreign countries. Moreover, compared with other high-value products, transportation cost occupies a substantial share of the agricultural commodity price, resulting in changes in the shipping freight rate being a pivotal determinant of agricultural produce import. In this respect, this study explores the possible association between agricultural produce import in Korea and shipping freight rate and the lead-lag relationship. Using a monthly dataset of agricultural produce import prices and freight rates for Handysize and Panamax dry-bulkers for the period between January 2010 and November 2020, this study determines that the shipping freight rate, in general, leads the agricultural commodity price.

• 사회경제평론
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• no.38
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• pp.129-161
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• 2012

This paper suggests that, in contrast to main argument of Efficient Market Hypothesis, hedge funds's financial speculation activity in the commodity markets are tending to generate a malfunction of making future price diverge from fundamental price. For this reason, we insist that stricter regulation on commodity derivative markets, including position limitation, is needed. Using some statistic analysis tools, we show that derivative transaction volume is getting so larger that financial speculation by hedge funds dominates price movement in commodity market and eventually slackens the speed of price's return to the fundamental price.

• Economic Analysis
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• v.17 no.1
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• pp.131-168
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• 2011

We estimate consumer price indexes of eight major cities from 1907 to 1939, and then integrate them into a national level one. The data mainly came from the Statistical Yearbooks of the Government-General of Colonial Korea, and if necessary, we supplement them using wages and unit prices of public utility charges which are used as the price of housing and various services. We apply Laspeyres index method, and the composition ratios of consumption expenditure estimated by the commodity flow method are used as weights. The price indexes of 12 item groups as well as aggregate one are also calculated. In case of Seoul, it is possible to calculate the consumer price index from 1907 to 2009, showing a century-long pattern. This consumer price index is critical for measuring the real income and expenditure before the liberation.

• The Journal of Asian Finance, Economics and Business
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• v.4 no.4
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• pp.27-37
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• 2017

This study examines the behaviour of staple food price using Multivariate BEKK-GARCH Model. Understanding of staple food price behaviour is important for determining the unpredictability of staple food market and also for policy making. In this paper, we focus on the commodity prices of sugar, rice, soybean and wheat to examine the volatility behaviour of those commodities. The empirical results show that the own-volatility spillover are relatively significant for all food prices. The own-volatility spillover effect for sugar price is relatively large compared with the volatility spillover of other staple food commodities. The findings also highlight that the price volatility of wheat increases during food crisis more than it does when the condition is stable. Also, the own-volatility of rice and wheat in the period of the food crisis is significant and higher compared to the period before food crisis indicates that the past own-volatility effects during food crisis are relatively more difficult to predict because of the uncertainty and high price volatility. Policy recommendations that can be proposed based on the findings are: (1) a better trade agreement in food commodity trade, (2) lower the dependence on wheat importation in Indonesia, and (3) reliable system to minimize food price volatility risks.

• 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.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.451-459
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• 2020

This study aims to examine the causality between production input and the price of rice in East Java, Indonesia. This study applied a quantitative method to understand in a comprehensive way the correlation between variables. The data used for this study were collected from several sources, including East Java Agriculture Office, Siskaperbapo.com, and Statistics Indonesia (BPS) of East Java. This research was carried out over five years, starting from 2014 to 2018. Furthermore, the data were analyzed using the Vector Error Correction Model (VECM) by employing E-Views (version 7). The findings of this study indicated that, in the long run, the population, rice production, and changes in people's income have a positive effect on price stability, but are inversely proportional if seen in the short term. In comparison, in the long run, farmer exchange rates variable has a negative impact on price stability, and inversely proportional in the short term, which has a positive effect. There are different implications when the people's income increases and the rice price declines; these have great potential to alleviate poverty in East Java, Indonesia. This is due to the fact that the price stability also concerns the welfare of the community.

• Journal of Korea Trade
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• v.23 no.2
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• pp.34-45
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• 2019

Purpose - This study investigates the lead-lag relations between the prices of major commodities imported into Korea and corresponding shipping freight rates. This paper aims to provide implications for cross-market causal relations between related economic segments. Design/Methodology - For economic long-run equilibrium between commodity prices and freights, a Johansen (1988) cointegration test is employed first. Then, Granger (1987) causality tests are performed under the vector error correction model (VECM) framework. Findings - The results indicate that the direction of causality varies by raw materials, which is attributable to different economic mechanisms in the corresponding shipping transportation sectors. In addition, the significance of causality becomes blurred during the post-2008 period. Practical Implication - Corporate managers in commodity trading, steelmaking, power generation, and oil refinery sectors can take advantage of the findings in this study as identifying leading economic indicators can be helpful for decision making in both short- and long-term strategies. Originality/value - This study is the first attempt to analyze the inter-relations between commodity prices and corresponding freight rates focusing on raw material imports of Korea.

• Korean Journal of Poultry Science
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• v.7 no.1
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• pp.13-22
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• 1980

On the Chicago Meracntile Exchange, individuals and firms buy and sell contracts for specified amounts of products that are to be delivered at a time period in the future at a price arrived at through openly competitive bidding. The transfer of ownership of these delivery promises takes place in a particular trading pit, for each commodity, on the floor of the Exchange. Trades are officially made by qualified members of the Exchange who act as brokers for their customers. For his services, the broker is paid a nominal round- turn commission fee by the customer. Although each commodity contract carefully describes the particular standards that product must meet in order to be a acceptable for delivery, actually fewer than three percent of the contracts traded are consummated by delivery. For the most part, contract obligations ions art offset, and thereby liquids. before the termination of the delivery month. The trader liquidates his position in the market after analyzing price trends, his timing, and his calculated price objectives. (omitted)

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.10a
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• pp.253-255
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• 2015

Crude oil is the world's most actively traded commodity and also one of the most significant resources in the world. The impact of oil price volatility has great influences on macroeconomic activities. This presentation is to review and analyze the oil price fluctuation and to examine the effects especially on the offshore oil production and thereafter to look over the challenges and opportunities in this sector focusing on the petroleum logistics.