A comparative study of moving average and ARIMA model in forecasting gold price / Arif Luqman Khairil Annuar ... [et al.]
Technical analysis is becoming an important reference to the traders in financial markets such as stock markets, foreign exchange market, and gold market. Moving average is one of the most vastly used statistical model in technical analysis to project and forecast the trend of data in financial mark...
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2021.
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LEADER | 00000 am a22000003u 4500 | ||
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001 | repouitm_56207 | ||
042 | |a dc | ||
100 | 1 | 0 | |a Khairil Annuar, Arif Luqman |e author |
700 | 1 | 0 | |a Hang, See Pheng |e author |
700 | 1 | 0 | |a Mohd Nor, Siti Rohani |e author |
700 | 1 | 0 | |a Thoo, Ai Chin |e author |
245 | 0 | 0 | |a A comparative study of moving average and ARIMA model in forecasting gold price / Arif Luqman Khairil Annuar ... [et al.] |
260 | |c 2021. | ||
500 | |a https://ir.uitm.edu.my/id/eprint/56207/1/56207.pdf | ||
520 | |a Technical analysis is becoming an important reference to the traders in financial markets such as stock markets, foreign exchange market, and gold market. Moving average is one of the most vastly used statistical model in technical analysis to project and forecast the trend of data in financial markets. This study aims to compare the performance of the simple moving average (SMA), moving average convergence divergence (MACD), and autoregressive integrated moving average (ARIMA) in forecasting gold price with the effect of COVID-19 pandemic. A dataset is collected from World Gold Council in 2020 and 2021. The comparison is done by different validations: accuracy rate, mean absolute percentage error (MAPE) and root mean square error (RMSE). The results indicating the accuracy rate of MACD is higher than SMA. SMA is found providing smaller forecasting error 1.264% compared to compare to ARIMA with 1.809%. The result favours to SMA as compared to ARIMA due to the dataset obtained during COVID-19 pandemic phase which observes the instability of economy. | ||
546 | |a en | ||
690 | |a HB Economic Theory. Demography | ||
690 | |a Economics | ||
655 | 7 | |a Conference or Workshop Item |2 local | |
655 | 7 | |a NonPeerReviewed |2 local | |
787 | 0 | |n https://ir.uitm.edu.my/id/eprint/56207/ | |
856 | 4 | 1 | |u https://ir.uitm.edu.my/id/eprint/56207/ |z Link Metadata |