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"Laporan ini merupakan gabungan dari tiga penelitian yang berkelanjutan mengenai metode peramalan inflasi di Australia, yang dianalisis menggunakan pendekatan ekonometrika runtun waktu. Penelitian pertama menggunakan model ARIMA untuk meramalkan inflasi Indeks Harga Konsumen (CPI) di Australia untuk periode 2023Q1 hingga 2024Q4. Penelitian kedua mengeksplorasi dampak dinamis tingkat pengangguran dan suku bunga terhadap inflasi, menggunakan model ARDL dan fungsi respon impuls (IRF). Penelitian ketiga membandingkan model ARIMA dan V AR untuk peramalan inflasi, menilai keakuratan prediksi melalui data observasi. Hasil dari laporan ini menunjukkan bahwa model ARIMA efektif dalam peramalan jangka pendek, sementara model V AR menunjukkan stabilitas yang lebih baik dalam prediksi jangka panjang. Temuan ini memberikan wawasan penting bagi pembuat kebijakan untuk memahami dinamika variabel-variabel makroekonomi dan dampaknya terhadap tingkat inflasi dan kondisi perekonomian.

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This report is a combination of three consecutive research studies on inflation forecasting methods in Australia, analyzed using a time series econometrics approach. The first study utilizes the ARIMA model to forecast Consumer Price Index (CPI) inflation in Australia for the period 2023Q1 to 2024Q4. The second study explores the dynamic impacts of unemployment rates and cash rates on inflation, employing ARDL models and impulse response functions (IRFs). The third study compares ARIMA and V AR models for inflation forecasting, evaluating predictive accuracy through observed data. The results indicate that ARIMA models are effective for short-term forecasting, while V AR models exhibit greater stability in long-term predictions. These findings provide valuable insights for policymakers to understand the dynamics of macroeconomic variables and their impacts on inflation and the economy condition."

"Penelitian ini bertujuan untuk melihat pengaruh aktivitas perdagangan berjangka terhadap volatilitas pasar spot komoditas kakao yang diukur menggunakan GARCH. Sesuai dengan Kumar (2009), sebelumnya volume dan open interest dibedakan menjadi komponen expected dan unexpected menggunakan ARIMA dan volatilitas spot, yang dimodelkan dengan GARCH (1,1), ditambahkan dengan expected/unexpected volume dan open interest perdagangan berjangka sebagai variabel eksogen. Granger Causality Test digunakan untuk memahami hubungan dinamis setiap variabel.Hasil penelitian menunjukkan bahwa (1) conditional spot volatility dipengaruhi oleh volume/open interest baik komponen expected maupun unexpected; (2) hubungan dinamis yang terjadi adalah hubungan signifikan 1 (satu) arah antara lain : open interest (expected) menyebabkan spot volatility, open interest (unexpected) menyebabkan spot volatility, volume (expected) menyebabkan spot volatility.

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This study aimed to examine the effect of futures trading activity on cocoa spot market volatility measured using GARCH. According to Kumar (2009), first the trading volumes and open interest are divided into expected and unexpected components using ARIMA and then spot volatility equation, which is modeled as GARCH (1,1) process, is augmented with expected and unexpected futures trading volume and open interest as exogenous variabel. Granger Causality Test is used to understand the dynamic relationship between these variables.The results showed that (1) the conditional spot volatility is influenced by the volume / open interest with both expected and unexpected components; (2) the dynamic relationship that occurs is a significant in 1 (one) way include: open interest (expected) causes spot volatility, open interest (unexpected) causes the spot volatility, volume (expected) causes the spot volatility."