The recent literature shows a growing interest in modeling and forecasting oil price volatility due to its impact on the global and regional economies (cf.Wang et al.,2012; Rahman and Serletis,2012). How oil price shocks may a ect economic growth is well-documented in a large body of research. Di erent transmission mechanisms were de-
In contrast, there has been relatively little work done on modeling and forecasting petroleum futures price volatility. This is unfortunate given the importance of oil to our economies. Moreover, one cannot conclude that the success or failure of a particular type of forecasting model applied to one market carries over to a different market.
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Forecasting volatility of crude oil markets Modeling and forecasting oil price volatility are important inputs into macroeconometric models, option pricing formulas, and portfolio selection models. For example, current crude oil prices make use of modern financial instruments,
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Forecasting price volatility range of crude palm oil by mining the historical data using hybrid range model January 2015 Frontiers in Artificial Intelligence and Applications 274:531-540
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This study provides a new perspective of modelling and forecasting realized range-based volatility (RRV) for crude oil futures. We are the first to improve the Heterogeneous Autoregressive model of Realized Range-based Volatility (HAR-RRV) model by considering the significant jump components, signed returns and volatility of realized range-based volatility.
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Volatile price fluctuation of crude palm oil has been a major challenge faced by planters, plantation companies, investors, and even downstream industry. Severe price volatility over the past few years has negatively been impacting the decision making process of risk hedging and mitigation.
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products. The oil palm industry is a contributor to Malaysia export revenue. Thus, modelling and forecasting of CPO prices are important so as to obtain valuable information pertaining to the future of CPO prices. Box-Jenkins approach was used to forecast monthly crude palm oil price [1].
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Neural Network (ANN). Md Nor et al, (2014) studied on forecasting of palm oil price in Malaysia used ARIMA models, neural networks and fuzzy logic systems. Ahmad et al, (2014), studied on volatility modeling and forecasting of CPO prices. Philbertha & Achmad (2014), studied on volatility analysis international CPO used Arch, Arch-M and GARCH
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volatility of crude oil prices. Several properties of crude oil price dynamics are established, including meanreversion, an asymmetry between returns a- nd volatility, volatility clustering, and infrequent compound jumps. They found the evidence of volatility spillover among crude oil, corn germ, and wheat markets after the fall of 2006.
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An accurate prediction of crude palm oil (CPO) prices is important especially when investors deal with ever-increasing risks and uncertainties in the future. Therefore, the applicability of the forecasting approaches in predicting the CPO prices is becoming the matter into concerns. In this study, two artificial intelligence approaches, has been used namely artificial neural network (ANN) and
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The food-energy nexus has attracted great attention from policymakers, practitioners, and academia since the food price crisis during the 2007008 Global Financial Crisis (GFC), and new policies that aim to increase ethanol production. This paper incorporates aggregate demand and alternative oil shocks to investigate the causal relationship between agricultural products and oil markets.
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Forecasting Crude Oil (Spot Price) Volatility Institution Date Table of Contents METHODOLOGY AND DATA 2 Introduction 2 Volatility clustering 4 Data for GARCH Models 6 Estimation 10 Models Used in the Study 11 GARCH (1,1) Model 12 EWMA is considered to be a special type of GARCH(1,1) 15 EGARCH (1,1) Model 15 Data and Sample Size Selection 17 There are four main benchmarks within the global
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Palm oil also serves as a feedstock for biodiesel production, thus establishing a new link between agricultural commodities and crude oil. Price and volatility transmission effects between EU and World butter prices, as well as between butter, palm oil and crude oil prices, before and after the Luxembourg agreement, are analysed.
Get PriceDownloadable (with restrictions)! This paper analyzes volatility models and their forecasting abilities in the presence of jumps in two crude-oil markets - Brent and West Texas Intermediate (WTI) - between January 6th 1992 and December 31st 2014. We compare a number of GARCH-type models that capture short memory as well as asymmetry (GARCH, GJR-GARCH and EGARCH), estimated on raw returns, to
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The Forecasting of agriculture commodity price plays an important role in the developing country like India, whose major population directly or indirectly depends upon farming. Mohamad, A.M.B.: Modeling and forecasting price volatility of crude palm oil and sarawak black pepper using ARMA and GARCH model. Adv. Sci. Lett. 24 McLeod, A.I
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Modeling and Forecasting Price Volatility of Crude Palm Oil and Sarawak Black Pepper Using ARMA and GARCH Model Jelani Bin Razali and Afiqah Munira Bt Mohamad Adv. Sci. Lett. 24, 9327330 (2025) [Full Text - PDF] [Purchase Article]
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An accurate prediction of crude palm oil (CPO) prices is important especially when investors deal with ever-increasing risks and uncertainties in the future. Therefore, the applicability of the forecasting approaches in predicting the CPO prices is becoming the matter into concerns. In this study, two artificial intelligence approaches, has been used namely artificial neural network (ANN) and
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The food-energy nexus has attracted great attention from policymakers, practitioners, and academia since the food price crisis during the 2007008 Global Financial Crisis (GFC), and new policies that aim to increase ethanol production. This paper incorporates aggregate demand and alternative oil shocks to investigate the causal relationship between agricultural products and oil markets.
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Mehmet Balcilar and Zeynel Abidin Ozdemir, The nexus between the oil price and its volatility risk in a stochastic volatility in the mean model with time-varying parameters, Resources Policy, 10.1016/j.resourpol.2025.07.001, (2025).
Get PricePalm oil also serves as a feedstock for biodiesel production, thus establishing a new link between agricultural commodities and crude oil. Price and volatility transmission effects between EU and World butter prices, as well as between butter, palm oil and crude oil prices, before and after the Luxembourg agreement, are analysed.
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The Forecasting of agriculture commodity price plays an important role in the developing country like India, whose major population directly or indirectly depends upon farming. Mohamad, A.M.B.: Modeling and forecasting price volatility of crude palm oil and sarawak black pepper using ARMA and GARCH model. Adv. Sci. Lett. 24 McLeod, A.I
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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.
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Brent crude futures, the international benchmark, have risen by around a half in the past year. Photograph: Henry Romero/Reuters. The price of oil has hit its highest level since November 2014
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Modeling and Forecasting Price Volatility of Crude Palm Oil and Sarawak Black Pepper Using ARMA and GARCH Model Jelani Bin Razali and Afiqah Munira Bt Mohamad Adv. Sci. Lett. 24, 9327330 (2025) [Full Text - PDF] [Purchase Article]
Get PriceMehmet Balcilar and Zeynel Abidin Ozdemir, The nexus between the oil price and its volatility risk in a stochastic volatility in the mean model with time-varying parameters, Resources Policy, 10.1016/j.resourpol.2025.07.001, (2025).
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An accurate prediction of crude palm oil (CPO) prices is important especially when investors deal with ever-increasing risks and uncertainties in the future. Therefore, the applicability of the forecasting approaches in predicting the CPO prices is becom...
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Crude oil is expected to trade at 52.82 USD/BBL by the end of this quarter, according to Trading Economics global macro models and analysts expectations. Looking forward, we estimate it to trade at 56.81 in 12 months time. Trading Economics members can view, download and compare data from nearly 200 countries, including more than 20 million
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Executive SummaryIndia 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
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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.
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Brent crude futures, the international benchmark, have risen by around a half in the past year. Photograph: Henry Romero/Reuters. The price of oil has hit its highest level since November 2014
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Spot Price Volatility (Wheat) Spot Price Volatility (RM Seed Oil) Spot Price Volatility (Refined Soy Oil) Objectives This paper proposes a multivariate vector error-correction generalized autoregressive conditional heteroscedasticity model to investigate the effect of oilseeds and wheat grain prices in neighbouring countries of Asia on its
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Modeling and Forecasting Price Volatility of Crude Palm Oil and Sarawak Black Pepper Using ARMA and GARCH Model Jelani Bin Razali and Afiqah Munira Bt Mohamad Adv. Sci. Lett. 24, 9327330 (2025) [Full Text - PDF] [Purchase Article]
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An accurate prediction of crude palm oil (CPO) prices is important especially when investors deal with ever-increasing risks and uncertainties in the future. Therefore, the applicability of the forecasting approaches in predicting the CPO prices is becom...
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However, the correlation between crude oil price and agricultural commodity prices does not always mean causation from the former to the latter. Previous studies often focused on the causality from crude oil price to agricultural commodity prices, so the possibility of reverse causality is often ignored in the literature.
Get PriceCrude 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.
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In the case of mustard seed, the model reports bi-directional volatility spillover with equal strength. The magnitude of spillover coefficient from spot to futures is greater in the case of soya oil, Mentha oil, and crude palm oil (CPO). Therefore, spillover effect from spot to futures is more than the spillover from futures to spot.
Get PriceBrent crude futures, the international benchmark, have risen by around a half in the past year. Photograph: Henry Romero/Reuters. The price of oil has hit its highest level since November 2014
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Crude oil is expected to trade at 52.82 USD/BBL by the end of this quarter, according to Trading Economics global macro models and analysts expectations. Looking forward, we estimate it to trade at 56.81 in 12 months time. Trading Economics members can view, download and compare data from nearly 200 countries, including more than 20 million
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Spot Price Volatility (Wheat) Spot Price Volatility (RM Seed Oil) Spot Price Volatility (Refined Soy Oil) Objectives This paper proposes a multivariate vector error-correction generalized autoregressive conditional heteroscedasticity model to investigate the effect of oilseeds and wheat grain prices in neighbouring countries of Asia on its
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