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Academic literature on the topic 'Commodity futures Indonesia Econometric models'

Author: Grafiati
Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "Commodity futures Indonesia Econometric models"

1

Maitra, Debashish. "Do seasonality, break and spillover effects explain commodity price volatility." Journal of Agribusiness in Developing and Emerging Economies 8, no. 1 (March 12, 2018): 144–70. http://dx.doi.org/10.1108/jadee-04-2015-0019.

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Purpose The purpose of this paper is to understand the volatility in commodity futures and spot markets. The study starts with a few questions: first, the effect of seasonality on the volatility is studied. Thereafter, the presence of structural breaks in the variance is identified. At last the seasonality, structural shifts and spillover effects are examined together to find out their effects on volatility. Design/methodology/approach The methodology heavily employs econometric tools and techniques. The monthly seasonal dummies are incorporated to identify the effects of seasonality on volatility. Then, the presence of break in volatility is tested by cumulative sum of squares (CUSUM test), followed by generalized autoregressive conditional heteroscedastictity and EGARCH models are measured by including seasonal dummies, break dummies and the residuals of other market in the variance equation to determine spillover effects. Findings It is found that the effects of seasonality on volatility cannot be ignored as the effects are significant. The presence of asymmetry is detected in all the commodities. The presence of seasonality and structural breaks in the variance equation are statistically able to reduce the volatility but the magnitude is very negligible with an exception in cumin futures markets. Bi-directional volatility spillover between futures and spot markets is observed in all the commodities and the effect of spillover is more from spot markets to the futures markets. Research limitations/implications This study is limited to a few agro commodities which are well traded. This study could have been extended to the other thinly traded commodities. This study has also taken only near month futures contracts as it contains more information but the same could have been studied by taking far month contracts also. Originality/value The present study attempted to understand the conjugated effects of seasonality, structural breaks and spillover on volatility of commodity markets which is not apparent in the previous studies. This study has also employed methodological rigor to identify the breaks in the variance equation. In addition to this it has also investigated whether Indian commodity futures markets are informationally more efficient than the spot markets.
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2

Malhotra, Meenakshi, and Dinesh Kumar Sharma. "Volatility Dynamics in Oil and Oilseeds Spot and Futures Market in India." Vikalpa: The Journal for Decision Makers 41, no. 2 (May 31, 2016): 132–48. http://dx.doi.org/10.1177/0256090916642686.

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Executive Summary India occupies the fifth position in the vegetable oil economy of the world. The demand for oilseeds and vegetable oil has far exceeded the domestic output necessitating huge imports. Futures market helps to bring price stability for the development of the underlying physical market. The present study investigates the volatility dynamics in spot and futures markets of select oil and oilseeds commodities. The objectives of this article are to study (a) the information transmission process between spot and futures markets, also called volatility spillover and (b) the impact of futures trading activity on the volatility of physical market prices. The commodities selected from oil and oilseeds segment are refined soya oil, mustard seed, crude palm oil, and mentha oil. The study uses basic Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model to capture volatility in prices of the selected commodities. Bivariate GARCH model makes use of information in the history of two different markets for testing volatility spillover between two markets of the same underlying commodity. The relationship between futures trading activity and spot price volatility is investigated for examining the impact of futures trading activity on the volatility of underlying spot market. Two variables, viz., futures trading volume and open interest are decomposed into expected and unexpected components and are taken as a proxy for the level of trading activity. The contemporaneous and dynamic relationships are studied with the help of augmented GARCH model and Granger causality, respectively. It is observed that there is an efficient transmission of information between spot and futures markets but it is the spot market which leads to the flow of information to futures and hence causes greater spillover of volatility. The spot market has a greater impact on the volatility of futures market, indicating that informational efficiency of oilseeds spot market is stronger than that of the futures market. The contemporaneous and dynamic relationship between spot price volatility and futures trading activity tested with econometric models provide evidence of the destabilizing impact of an unexpected increase in futures trading activity (volume or open interest) on the spot price volatility in three out of four commodities studied. This indicates that badly informed traders present in futures market are destabilizing the underlying spot market by inducing noise and lowering the information content of prices.
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3

Erlita, Devi Indah, Asyifa Nur Azizah, and Yuhka Sundaya. "Analisis Ekonomi Kesehatan Rumah Tangga Indonesia Pada Masa Pandemi Covid-19." Jurnal Ekonomi Pembangunan 11, no. 2 (July 3, 2022): 95–106. http://dx.doi.org/10.23960/jep.v11i2.486.

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The decreasing household access to health services occurred during the Covid-19 pandemic. Observing the health profile of BPS Indonesia (2021), it can be seen that there is a percentage change in the decrease in road treatment and an increase in health complaints. This study aims to present the results of estimating econometric models that explain economic and non-economic variables that can potentially change the opportunities for health demand in Indonesia. The morbidity data for each district and city on the selected island was converted into four categories of health status, namely [1] very healthy, [2] healthy, [3] moderately healthy, and [4] unhealthy. This research is deductive. We use the demand for health theory to identify variables that need to be researched and employ QLDV (qualitative limited dependent variable) to estimate them. The estimation results are conducting to the issue of efforts to increase the chances of household health levels and serial studies starting in 1972. The simulation results with marginal effect predict that the probability of demand for health will increase by 2.71 percent in conditions of inflation of food and health commodities at the level of 6 and 7 percent, children under-five immunization coverage is close to 90 percent, education average is junior high school, income allocation of less than 50 percent, and real income per capita is close to 10 million per year. Regarding the literature series, this study succeeded in showing the significance of health commodity prices which was difficult to display by previous researchers.
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4

Zeng, Tian, and Norman R. Swanson. "Predictive Evaluation of Econometric Forecasting Models in Commodity Futures Markets." Studies in Nonlinear Dynamics & Econometrics 2, no. 4 (January 1, 1998). http://dx.doi.org/10.2202/1558-3708.1037.

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5

Rifa’i, Muhammad. "ANALISIS DINAMIS PERMINTAAN DAN PENAWARAN KOMODITAS KEDELAI DI JAWA TIMUR." IQTISHODUNA, June 15, 2011. http://dx.doi.org/10.18860/iq.v0i0.310.

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The aims of this research are: (a) analyze factors influenceing supllay, import and demand of soybean in east java region; (b) analyze factors influencing price of soybean; (c) analyze linkage among suplay, import, demand and domistic price of soyben simultaneously. This research conducted in east java as main producer of soyben in Indonesia. We use secondary data for 1980-2004 periods wits simutaneus models, especially two stage least square method. The result of research shows that the model of demand and supply used had fulfilling economic, statistic and econometric criteria so can be used to explain economic behavior of soyben in east java correctly. Suplay of soybean influenced positively by corn price, productivity and harvesting are of soybean commodity, while domistic price of soybean, price of rice, price of fertilizer, world price and so lags of supplay does not significant. Import positively influenced by income and current demand, and negatively import does not significant. Domistic demand of soybean positively influenced by population size and negatively influenced influenced by per capita income, while other variables such as domistic price, corn price and previous demand does not significant. Domistic price positively influenced by suplay and exchange rate, and so previosly domistic price, while demand and world price does not signficant.
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Dissertations / Theses on the topic "Commodity futures Indonesia Econometric models"

1

Ji, Wen. "Essays on econometric evaluation of models of commodity futures prices." 2003. http://www.lib.ncsu.edu/theses/available/etd-07312003-224352/unrestricted/etd.pdf.

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Books on the topic "Commodity futures Indonesia Econometric models"

1

Casassus, Jaime. Equilibrium commodity prices with irreversible investment and non-linear technology. Cambridge, Mass: National Bureau of Economic Research, 2005.

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2

Schaeffer, Peter V. Commodity Modeling and Pricing. New York: John Wiley & Sons, Ltd., 2008.

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Commodity modeling and pricing: Methods for analyzing resource market behavior. Hoboken, N.J: Wiley, 2008.

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Tchernykh, Elena. Regime-switching behavior of the term structure of forward markets. Cambridge, Mass: National Bureau of Economic Research, 2005.

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Tchernykh, Elena. Regime-switching behavior of the term structure of forward markets. Cambridge, MA: National Bureau of Economic Research, 2005.

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Priyanka, Singh, and Indian Institute of Management, Ahmedabad., eds. Volatility modeling, seasonality, and risk-return relationship in GARCH-in-mean framework: The case of Indian stock and commodity markets. Ahmedabad: Indian Institute of Management, Ahmedabad, 2008.

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7

1939-, Güvenen Orhan, Labys Walter C. 1937-, and Lesourd Jean-Baptiste, eds. International commodity market models: Advances in methodology and applications. London: Chapman and Hall, 1991.

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8

Chow, Ying-Foon. The efficiency of the precious metals futures market. 1995.

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9

1939-, Güvenen Orhan, Labys Walter C. 1937-, Lesourd Jean-Baptiste, and Applied Econometric Association, eds. Politiques économiques et marchés internationaux de matières premières: Analyses économétriques. Paris: Economica, 1991.

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10

Kumar, Brajesh, and Indian Institute of Management, Ahmedabad., eds. Price and volatility spillovers across North American, European, and Asian stock markets: With special focus on Indian stock market. Ahmedabad: Indian Institute of Management, Ahmedabad, 2008.

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