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The Predictability of GARCH-Type Models on the Returns Volatility of Primary Indonesian Exported Agricultural Commodities  [cached]
Saarce Elsye Hatane
Jurnal Akuntansi dan Keuangan , 2011,
Abstract: Agricultural sector plays an important role in Indonesia s economy; especially for the plantation sub-sector contributing high revenues to Indonesia s exporting sectors. The primary agricultural commodities in Indonesian export discussed in this study would be Crude Palm Oil (CPO), Natural Rubber TSR20, Arabica Coffee, Robusta Coffee, Cocoa, White Pepper and Black Pepper. Meanwhile, the returns volatility nature of agricultural commodity is famous. The volatility refers to heteroscedasticity nature of the returns which can be modeled by GARCH-type models. The returns volatility can be describe by the residual of the mean equation and volatility of error variances in the previous periods. The aims of this study are to examine the predictability of GARCH-type models on the returns volatility of those seven agricultural commodities and to determine the best GARCH-type models for each commodity based on the traditional symmetric evaluation statistics. The results find that the predictability of ARCH, GARCH, GARCH-M, EGACRH and TGARCH, as type of GARCH models used in this study, are different for each commodity.
Food Commodity Prices Volatility: The Role of Biofuels  [PDF]
Christopher L. Gilbert, Harriet K. Mugera
Natural Resources (NR) , 2014, DOI: 10.4236/nr.2014.55019

Food commodity prices have recently increased sharply and become more volatile, highlighting greater uncertainty in markets and threatening global food security. High fuel prices combined with legislative mandates have increased biofuel production raising the average cost of food on the global market and particularly in developing countries and established a link between crude oil and agricultural prices. We investigate the role of biofuels in explaining increased volatility in food commodities. Multivariate GARCH models and volatility decompositions are estimated on grains and crude oil daily prices over a twelve-year sample from 2000-2011. We find increases in correlations and co-movements between grains and crude oils prices after 2006 and particularly in 2008 when crude oil prices were high. Increased volatility in grains during the 2008-09 spike was largely due to shocks transmitted from crude oil to grains especially corn, wheat and soybean prices.

How does bad and good volatility spill over across petroleum markets?  [PDF]
Jozef Barunik,Evzen Kocenda,Lukas Vacha
Quantitative Finance , 2014,
Abstract: We detect and quantify asymmetries in volatility spillovers using the realized semivariances of petroleum commodities: crude oil, gasoline, and heating oil. During the 1987--2014 period we document increasing spillovers from volatility among petroleum commodities that substantially change after the 2008 financial crisis. The increase in volatility spillovers correlates with the progressive financialization of the commodities. In terms of asymmetries in spillovers we show that periods of increasing crude oil prices strongly correlate with dominating spillovers due to bad volatility. Overall, bad volatility due to negative returns spills over among petroleum commodities to a much larger extent than good volatility due to positive returns. After the 2008 financial crisis the asymmetries in spillovers markedly declined in terms of total as well as directional spillovers. An analysis of directional spillovers further reveals that no commodity dominates other commodities in terms of spillover transmission in general.
Do the Indian Agricultural Commodities’ Prices Exhibit Non-Linear Mean Reversion? An Empirical Evidence  [PDF]
Aviral Kumar Tiwari, Mothkuri Aruna, Aruna Kumar Dash
Theoretical Economics Letters (TEL) , 2015, DOI: 10.4236/tel.2015.52039
Abstract: Indian economy’s inflation index often reflects double digit tendencies due to supply side shortages caused by droughts, rise in the prices of crude oil in the international markets etc. These factors may be responsible for non-linear behaviour of inflation index. Against this backdrop, an attempt is made in this study to capture non-linear mean reversion of prices of 47 agricultural commodities of India. The study employs powerful non-linear unit root test so as to generate robust findings to infer valid policy implications. The results of the study indicate the presence of unit root with drift process for Food Grains, Cereals, Pulses, Fruits, Vegetables, Primary Articles, Ragi and Rice. And for rest of the commodities, it is observed that there is evidence of mean reversion and therefore, the impact would be only temporary in nature. Thus, the empirical inferences enable the policy makers to design appropriate short term and long term polices related to the prices of agricultural commodities.
International Linkages of the Indian Commodity Futures Markets  [PDF]
Brajesh Kumar, Ajay Pandey
Modern Economy (ME) , 2011, DOI: 10.4236/me.2011.23027
Abstract: This paper investigates the cross market linkages of Indian commodity futures for nine commodities with futures markets outside India. These commodities range from highly tradable commodities to less tradable agricultural commodities. We analyze the cross market linkages in terms of return and volatility spillovers. The nine commodities consist of two agricultural commodities: Soybean, and Corn, three metals: Aluminum, Copper and Zinc, two precious metals: Gold and Silver, and two energy commodities: Crude oil and Natural gas. Return spillover is investigated through Johansen’s cointegration test, error correction model, Granger causality test and variance decomposition techniques. We apply Bivariate GARCH model (BEKK) to investtigate volatility spillover between India and other World markets. We find that futures prices of agricultural commodities traded at National Commodity Derivatives Exchange, India (NCDEX) and Chicago Board of Trade (CBOT), prices of precious metals traded at Multi Commodity Exchange, India (MCX) and NYMEX, prices of industrial metals traded at MCX and the London Metal Exchange (LME) and prices of energy commodities traded at MCX and NYMEX are cointegrated. In case of commodities, it is found that world markets have bigger (unidirectional) impact on Indian markets. In bivariate model, we found bi-directional return spillover between MCX and LME markets. However, effect of LME on MCX is stronger than the effect of MCX on LME. Results of return and volatility spillovers indicate that the Indian commodity futures markets function as a satellite market and assimilate information from the world market.
The Cointegration Analysis on the Spot Prices of the Malaysian Crude Palm Oil Futures Market  [cached]
Nik Muhammad Naziman Ab Rahman
International Journal of Economics and Finance , 2012, DOI: 10.5539/ijef.v4n7p95
Abstract: Futures markets play an important role in the price discovery and forward pricing of agricultural commodities. The analysis of this study has mainly focused on the empirical test of the effect of production, stock and export variables on the prices of the Malaysian Crude Palm oil futures market. For the empirical work, correlation analysis, multiple regression and recent econometric analysis were conducted to determine the price relationships of the Malaysian Crude Palm oil futures markets with the production, stock and export variables. Order of integration for all the variables was checked using Augmented Dickey-Fuller and Phillips-Perron tests of unit root. The Johansen approach was used to test cointegration in multivariate system that involved long run and short run estimations. The Vector Error Correction Model was used to test for causal relationships. The empirical evidence obtained from the study shows there exist a significant long run and short run relationships between the cash and future prices of the Malaysian Crude Palm oil futures market with the production, stock and export variables. The results of the causality test also shows that there is a strong relationship between the Malaysian Crude Palm oil futures market with the production, stock and export variables This mean that any information flow regarding the price movement of the Malaysian Crude Palm oil futures market will affect the production, stock and export variables and vice-versa.
Multiscale Stochastic Volatility Model for Derivatives on Futures  [PDF]
Jean-Pierre Fouque,Yuri F. Saporito,Jorge P. Zubelli
Quantitative Finance , 2013,
Abstract: In this paper we present a new method to compute the first-order approximation of the price of derivatives on futures in the context of multiscale stochastic volatility of Fouque \textit{et al.} (2011, CUP). It provides an alternative method to the singular perturbation technique presented in Hikspoors and Jaimungal (2008). The main features of our method are twofold: firstly, it does not rely on any additional hypothesis on the regularity of the payoff function, and secondly, it allows an effective and straightforward calibration procedure of the model to implied volatilities. These features were not achieved in previous works. Moreover, the central argument of our method could be applied to interest rate derivatives and compound derivatives. The only pre-requisite of our approach is the first-order approximation of the underlying derivative. Furthermore, the model proposed here is well-suited for commodities since it incorporates mean reversion of the spot price and multiscale stochastic volatility. Indeed, the model was validated by calibrating it to options on crude-oil futures, and it displays a very good fit of the implied volatility.
The Determinants of Demand for Nigeria`s Agricultural Export Commodities
B.T. Omonona,O.A. Oni,E. Akpan
Pakistan Journal of Social Sciences , 2012,
Abstract: This study examined those factors that influence the demand for Nigeria`s agricultural export commodities. It relied on secondary data collected from the publications of the Federal Office of Statistics, Central Bank of Nigeria, World Bank and International Monetary Fund. The data were analyzed using descriptive statistics and the Auto-regressive Distributed Lag (ADL) model. The paper found out that the proportion of agricultural export commodities to total export has continued to decline. The current and expected per capita income of the importing countries, and the expected quantity of cocoa imported are positively associated with the demand for these agricultural while the current and expected relative prices of these commodities are negatively associated with the demand of agricultural export commodities. In addition, the traditional agricultural export commodities are inelastic in the short run while those of the non-traditional agricultural commodities are elastic in the long run. It is recommended that Nigeria should make these export commodities` prices to be cheap in order to increase the level of demand in the importing countries.
Price dynamics and volatility of crude oil futures market: Inventory information shocks and trading activities of non-commercial traders

BU Hui,HE Ya-nan,

系统工程理论与实践 , 2011,
Abstract: This paper examines the behavior of crude oil futures price volatility and investigates whether information shocks to market expectations about inventory and non-commercial traders' positions change have a significant effect on crude oil price and its volatility.It also studies how these factors,as well as other determinants,influence crude oil returns and volatility,whether returns are related to risks,and whether financial crises increase volatility in crude oil futures markets.This paper constructs a new...
Volatility Spillover from Oil to Food and Agricultural Raw Material Markets  [PDF]
Muge Kaltalioglu, Ugur Soytas
Modern Economy (ME) , 2011, DOI: 10.4236/me.2011.22011
Abstract: The upward movement in oil and food prices in the 2000s has attracted interest in the information transmission mechanism between the two markets. This paper investigates the volatility spillover between oil, food consumption item, and agricultural raw material price indexes for the period January 1980 to April 2008. The results of the Cheung-Ng procedure show that variation in oil prices does not Granger cause the variance in food and agricultural raw material prices. Since there is no volatility spillover from oil markets to food and agricultural raw material markets, investors can benefit from risk diversification. However, there is bi-directional spillover between agricultural raw material and food markets.
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