Volatility modelling and forecasting of Malaysian crude palm oil prices

Ahmad, Mohd Hamdan; Ping, Pung Yean; Mahamed, Norizan

doi:10.12988/ams.2014.48650

Cited by 14 publications

(10 citation statements)

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“…In Exponential smoothing [9] technique, the exponentially weighted average of past observations is used as a basis to make forecasting. The size of the weight assigned to each observation depends on the arrangement of data with regards to time.…”

Section: Double Exponential Smoothingmentioning

confidence: 99%

“…The results showed that the MARMA model is more efficient and palm oil price was predicted to decrease. There are also studies focusing on the price of crude palm oil (CPO) using ARIMA-GARCH ( [9]. Gan and Li [4] studied on Malaysia's palm oil position in the world market in 2035, with results showing domestic palm oil production is projected to rise by about 50%, about 26.6 million tons in 2035 while domestic demand of palm oil is expected to increase by more than 200% to 1.4 million tons in 2035.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Determining the Best-Fit Model for Oil Palm Yield and Planted Area in Malaysia

Norzaida¹,

Kamariah²,

Shafrina³

2017

IJHIT

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Section: Double Exponential Smoothingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Determining the Best-Fit Model for Oil Palm Yield and Planted Area in Malaysia

Norzaida¹,

Kamariah²,

Shafrina³

2017

IJHIT

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“…Hasil-hasil penelitian terkait peramalan harga minyak kelapa sawit berbasis analisis univariate maupun multivariate time series hingga model ekonometrika relatif telah banyak dilakukan. Beberapa penelitian terkait, antara lain penelitian Kanchymalay et al (2017), Ariff et al (2015), Ahmad et al (2014), Ahmed dan Shabri (2014), Kantaporn et al (2013), Khin et al (2013), Karia (2013), Karia dan Bujang (2011), dan Kurniawan (2011). Data basis yang menjadi unit ramalan pada analisis univariate maupun multivariate time series pada umumnya adalah harga bulanan dan sedikit yang berbasis data harian serta berupa peramalan post-ante untuk sebuah periode tertentu.…”

Section: Pendahuluanunclassified

Optimization of Technical Analysis in the Palm Oil Marketing Strategy: Daily Pricing Model for 30 Days Transactions

Kurniawan

Saragih²

2017

J. Penelitian Kelapa Sawit

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Information on future trends in price movement has a strategic role in the palm oil business. Through this information then embodied in the form of product marketing strategy. This study aims to build a daily price forecasting model for 30 days of forward transactions (Model 30 DTH) and based on the technical analysis. Goodness of fit is based on the suitability of the trend of price movement and the daily margin error between the forecast and the actual price in the future (ex-ante). Referring to both indicators from the Formulation stage to the 9th Validation, it shows that the model is relatively good in predicting daily price movement trends as well as daily error margins.

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“…There are a number of ways to obtain forecast value in the analysis of time series [1] such as artificial intelligence approaches [2], artificial neural network (ANN) [3,4] and autoregressive integrated moving average (ARIMA) models [1,5]. According to [6], the selection of the methods must reflect several features such as data and degree of significance.…”

Section: Introductionmentioning

confidence: 99%

Type 2 Fuzzy Inference-Based Time Series Model

et al. 2019

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Fuzzy techniques have been suggested as useful method for forecasting performance. However, its dependency on experts’ knowledge causes difficulties in information extraction and data collection. Therefore, to overcome the difficulties, this research proposed a new type 2 fuzzy time series (T2FTS) forecasting model. The T2FTS model was used to exploit more information in time series forecasting. The concepts of sliding window method (SWM) and fuzzy rule-based systems (FRBS) were incorporated in the utilization of T2FTS to obtain forecasting values. A sliding window method was proposed to find a proper and systematic measurement for predicting the number of class intervals. Furthermore, the weighted subsethood-based algorithm was applied in developing fuzzy IF–THEN rules, where it was later used to perform forecasting. This approach provides inferences based on how people think and make judgments. In this research, the data sets from previous studies of crude palm oil prices were used to further analyze and validate the proposed model. With suitable class intervals and fuzzy rules generated, the forecasting values obtained were more precise and closer to the actual values. The findings of this paper proved that the proposed forecasting method could be used as an alternative for improved forecasting of sustainable crude palm oil prices.

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Volatility modelling and forecasting of Malaysian crude palm oil prices

Cited by 14 publications

References 0 publications

Determining the Best-Fit Model for Oil Palm Yield and Planted Area in Malaysia

Determining the Best-Fit Model for Oil Palm Yield and Planted Area in Malaysia

Optimization of Technical Analysis in the Palm Oil Marketing Strategy: Daily Pricing Model for 30 Days Transactions

Type 2 Fuzzy Inference-Based Time Series Model

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