Integrating Fibonacci Retracement To Improve Accuracy of Time Series Prediction of Gold Prices
The prediction of gold prices is crucial for investors and policymakers due to its significant impact on global financial markets. Machine learning and deep learning have been used for predicting gold prices on time series data. This study employs MLR, SVM and CNN LSTM with Fibonacci retracement le...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Yayasan Pendidikan Riset dan Pengembangan Intelektual (YRPI)
2025-06-01
|
| Series: | Journal of Applied Engineering and Technological Science |
| Subjects: | |
| Online Access: | http://journal.yrpipku.com/index.php/jaets/article/view/6073 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850136860634906624 |
|---|---|
| author | Bagus Priambodo Ruci Meiyanti Samidi Samidi Gushelmi Gushelmi Rabiah Abdul Kadir Azlina Ahmad |
| author_facet | Bagus Priambodo Ruci Meiyanti Samidi Samidi Gushelmi Gushelmi Rabiah Abdul Kadir Azlina Ahmad |
| author_sort | Bagus Priambodo |
| collection | DOAJ |
| description |
The prediction of gold prices is crucial for investors and policymakers due to its significant impact on global financial markets. Machine learning and deep learning have been used for predicting gold prices on time series data. This study employs MLR, SVM and CNN LSTM with Fibonacci retracement levels to forecast gold prices based on time series data. The experiment results demonstrate that combining Fibonacci retracement with model prediction significantly enhances predictive performance compared to prediction without Fibonacci. The use of Fibonacci levels has resulted in a higher R² score and lower RMSE score showing that Fibonacci levels influence the accuracy of gold price predictions and strengthen the overall reliability of gold price forecasts. The findings underscore the potential of combining machine learning models with technical analysis tools in financial forecasting. Integrating the Fibonacci retracement level offers valuable insights for market participants, enabling more informed investment decisions and effective risk management strategies.
|
| format | Article |
| id | doaj-art-fe3ee384c6194611848bf8bc46da92da |
| institution | OA Journals |
| issn | 2715-6087 2715-6079 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Yayasan Pendidikan Riset dan Pengembangan Intelektual (YRPI) |
| record_format | Article |
| series | Journal of Applied Engineering and Technological Science |
| spelling | doaj-art-fe3ee384c6194611848bf8bc46da92da2025-08-20T02:31:00ZengYayasan Pendidikan Riset dan Pengembangan Intelektual (YRPI)Journal of Applied Engineering and Technological Science2715-60872715-60792025-06-016210.37385/jaets.v6i2.6073Integrating Fibonacci Retracement To Improve Accuracy of Time Series Prediction of Gold Prices Bagus Priambodo0Ruci Meiyanti1Samidi Samidi2Gushelmi Gushelmi3Rabiah Abdul Kadir4Azlina Ahmad5Universitas Mercu BuanaUniversitas Mercu BuanaUniversitas Budi LuhurUniversitas Putra Indonesia YPTKUniversiti Kebangsaan MalaysiaUniversiti Kebangsaan Malaysia The prediction of gold prices is crucial for investors and policymakers due to its significant impact on global financial markets. Machine learning and deep learning have been used for predicting gold prices on time series data. This study employs MLR, SVM and CNN LSTM with Fibonacci retracement levels to forecast gold prices based on time series data. The experiment results demonstrate that combining Fibonacci retracement with model prediction significantly enhances predictive performance compared to prediction without Fibonacci. The use of Fibonacci levels has resulted in a higher R² score and lower RMSE score showing that Fibonacci levels influence the accuracy of gold price predictions and strengthen the overall reliability of gold price forecasts. The findings underscore the potential of combining machine learning models with technical analysis tools in financial forecasting. Integrating the Fibonacci retracement level offers valuable insights for market participants, enabling more informed investment decisions and effective risk management strategies. http://journal.yrpipku.com/index.php/jaets/article/view/6073Predict Gold PriceMultiple Linear RegressionFibonacciSVMCNN-LSTM |
| spellingShingle | Bagus Priambodo Ruci Meiyanti Samidi Samidi Gushelmi Gushelmi Rabiah Abdul Kadir Azlina Ahmad Integrating Fibonacci Retracement To Improve Accuracy of Time Series Prediction of Gold Prices Journal of Applied Engineering and Technological Science Predict Gold Price Multiple Linear Regression Fibonacci SVM CNN-LSTM |
| title | Integrating Fibonacci Retracement To Improve Accuracy of Time Series Prediction of Gold Prices |
| title_full | Integrating Fibonacci Retracement To Improve Accuracy of Time Series Prediction of Gold Prices |
| title_fullStr | Integrating Fibonacci Retracement To Improve Accuracy of Time Series Prediction of Gold Prices |
| title_full_unstemmed | Integrating Fibonacci Retracement To Improve Accuracy of Time Series Prediction of Gold Prices |
| title_short | Integrating Fibonacci Retracement To Improve Accuracy of Time Series Prediction of Gold Prices |
| title_sort | integrating fibonacci retracement to improve accuracy of time series prediction of gold prices |
| topic | Predict Gold Price Multiple Linear Regression Fibonacci SVM CNN-LSTM |
| url | http://journal.yrpipku.com/index.php/jaets/article/view/6073 |
| work_keys_str_mv | AT baguspriambodo integratingfibonacciretracementtoimproveaccuracyoftimeseriespredictionofgoldprices AT rucimeiyanti integratingfibonacciretracementtoimproveaccuracyoftimeseriespredictionofgoldprices AT samidisamidi integratingfibonacciretracementtoimproveaccuracyoftimeseriespredictionofgoldprices AT gushelmigushelmi integratingfibonacciretracementtoimproveaccuracyoftimeseriespredictionofgoldprices AT rabiahabdulkadir integratingfibonacciretracementtoimproveaccuracyoftimeseriespredictionofgoldprices AT azlinaahmad integratingfibonacciretracementtoimproveaccuracyoftimeseriespredictionofgoldprices |