پیش‌بینی نرخ ارز در ایران با استفاده از تلفیق داده‌ها و مدل جامع مبتنی بر یادگیری ماشین

Abounouri, A., Khanalipour, A. & Abbasi, J. (2009). The effect of news on exchange rate volatility in Iran: An application of the ARCH family. Pajouheshnameh Bazargani, 50, 101-120. [In Persian] dor:20.1001.1.17350794.1388.13.50.4.8

Amiri, Farhad, Derakhshani-Daraabi, Kaveh, & Asayesh, Hamid. (2020).

Investigation the Effects of Exchange Rate Fluctuations on the Sub-Sectors Value Added in Iran. Iranian Journal of Applied Economic Studies, 10(39), 247–267. [In Persian]

Bayat, N. (2018). Forecasting exchange rates using recurrent self-organizing maps. Economics and Modern Trade, 13, 55-84. [In Persian]

Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J.D., Dhariwal, P., ... & Amodei, D. (2020). Language models are few-shot learners. Advances in Neural Information Processing Systems, 33, 1877-1901. doi:10.48550/arXiv.2005.14165

Devlin, J., Chang, M.-W., Lee, K. & Toutanova, K. (2018). BERT: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv: 1810.04805. doi:10.48550/arXiv.1810.04805

Dridan, R. & Oepen, S. (2012). Tokenization: Returning to a long solved problem—a survey, contrastive experiment, recommendations, and toolkit. Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers).

Farahani, M., Gharachorloo, M., Farahani, M. & Manthouri, M. (2021). ParsBERT: Transformer-based model for Persian language understanding. Neural Processing Letters, 53, 3831-3847.

doi:10.48550/arXiv.2005.12515

Fatahi, Sh., Ahmadi, A. & Akram-Mirzaei, A. (2013). Comparison of the accuracy of genetic algorithm methods with other exchange rate forecasting methods. Economic Studies and Policies, 96, 113-136. [In Persian]. doi:10.22096/esp.2013.26156

Goudarzi Farahani, G., Adeli, O.A. & Ghorbani, M. (2020). The impact of economic policy uncertainty on exchange rate volatility using the NARDL model approach. Econometric Modeling, 5(4), 147-171. [In Persian]. doi:10.22075/jem.2021.22243.1547

Hashemi-Dizaj, A., Hazari-Neiri, H. & Pourvohedani, R. (2020). Comparing the performance of artificial neural network models for forecasting exchange rates in Iran. Scientific Biannual Journal of Economic Studies and Policies, 7(2), 53-80. [In Persian]. doi:10.22096/esp.2020.43397

Khashaei, Mehdi, Bijari, Mehdi, & Mokhatab-Rafi‘i, Farimah. (2013).

Forecasting the Exchange Rate Using Hybrid Models of Multilayer Perceptrons (MLPs) and Probabilistic Neural Network Classifiers (PNNs). Numerical Methods in Engineering Quarterly, 32(1), 1–14. [In Persian]

Khodaveisi, H. & Molabahrami, A. (2012). Modeling and forecasting exchange rates based on stochastic differential equations. Economic Research, 100(47), 129-144. [In Persian]. doi:10.22059/jte.2012.29257

Heaton, J. (2016). An empirical analysis of feature engineering for predictive modeling. SoutheastCon, 1-6. doi:10.48550/arXiv.1701.07852

Josse, J. & Husson, F. (2012). Handling missing values in exploratory multivariate data analysis methods. Journal de la Société Française de Statistique, 153(2), 79-99.

Khan, W., Daud, A., Khan, K., Muhammad, S. & Haq, R. (2023). Exploring the frontiers of deep learning and natural language processing: A comprehensive overview of key challenges and emerging trends. Natural Language Processing Journal, 100026. doi:10.1016/j.nlp.2023.100026

Li, Y. & Yang, T. (2018). Word embedding for understanding natural language: A survey. Guide to Big Data Applications, 83-104. doi:10.1007/978-3-319-53817-4

Liu, J., Li, T., Xie, P., Du, S., Teng, F. & Yang, X. (2020). Urban big data fusion based on deep learning: An overview. Information Fusion, 53, 123-133. doi:10.1016/j.inffus.2019.06.016

Mansouri-Gorgori, H. & Khodavisi, H. (2019). Exchange rate forecasting: Comparison of logistic growth models with competing models. Economics and Modeling, 10, 141-179. [In Persian]. doi:10.48308/ecoj.10.3.157

Marzban, D.H., Javaheri, B.B. & Akbarian, A. (2005). A comparison between structural econometric models, time series, and neural networks for exchange rate forecasting. Economic Research Journal, 40(2). [In Persian]. dor: 20.1001.1.00398969.1384.40.2.8.6

Mikolov, T., Chen, K., Corrado, G. & Dean, J. (2013). Efficient estimation of word representations in vector space. arXiv preprint arXiv: 1301.3781. doi:10.48550/arXiv.1301.3781

Mohamadi, S., Mujtaba, G., Le, N., Doretto, G. & Adjeroh, D.A. (2023). ChatGPT in the Age of Generative AI and Large Language Models: A Concise Survey. arXiv preprint arXiv: 2307.04251.

doi:10.48550/arXiv.2307.04251

Nargesian, F., Samulowitz, H., Khurana, U., Khalil, E.B. & Turaga, D.S. (2017). Learning feature engineering for classification. IJCAI, 2529-2535. doi:10.24963/ijcai.2017/352

Potdar, K., Pardawala, T.S. & Pai, C.D. (2017). A comparative study of categorical variable encoding techniques for neural network classifiers. International Journal of Computer Applications, 175(4), 7-9.

doi:10.5120/IJCA2017915495

Rahimi-Boroujerdi, A. (2000). The optimal exchange system and forecasting exchange rates for Iran's economy. Iranian Economic Research, 5, 40-45. [In Persian].

Seabe, P.L., Moutsinga, C.R.B. & Pindza, E. (2023). Forecasting cryptocurrency prices using LSTM, GRU, and bi-directional LSTM: A deep learning approach. Fractal and Fractional, 7(2), 203.

doi:10.3390/fractalfract7020203

Sharif-Moghaddam, Sh. & Hashemi, S.A. (2018). Forecasting euro to dollar exchange rate using artificial neural networks. Financial Engineering and Securities Management, 9(37), 399-413. [In Persian].

Shirazi, Homayoun, & Nasrollahi, Khadijeh. (2013). Monetary Models and Exchange Rate Forecasting in Iran: From Theory to Empirical Evidence. Financial and Economic Policies Quarterly, 1(4), 5–24. [In Persian]

Singh, D. & Singh, B. (2020). Investigating the impact of data normalization on classification performance. Applied Soft Computing, 97, 105524. doi:10.1016/j.asoc.2019.105524

Sousa, M.G., Sakiyama, K., de Souza Rodrigues, L., Moraes, P.H., Fernandes, E.R. & Matsubara, E.T. (2019). BERT for stock market sentiment analysis. 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI), 1597-1601. doi.org:10.1109/ICTAI.2019.00231

Taghavi, M. & Khodam, M. (2011). Comparative efficiency of exchange rate theories in predicting exchange rate changes in the international foreign exchange market. Financial Knowledge of Securities Analysis (Financial Studies), 9, 147-192. [In Persian].

Tayebi, S., Moheddinia, N. & Kazemini, M. (2008). Utilizing artificial neural networks in forecasting economic variables and comparison with econometric methods: Forecasting exchange rate trends in Iran. Industrial Engineering and Management (Sharif Special Edition for Engineering Sciences), 43, 104-199. [In Persian]

Villamil, L., Bausback, R., Salman, S., Liu, T.L., Horn, C. & Liu, X. (2023). Improved stock price movement classification using news articles based on embeddings and label smoothing. arXiv preprint arXiv:2301.10458. doi:10.48550/arXiv.2301.10458

Yarmohammadi, M. & Mahmoodvand, R. (2015). Forecasting exchange rates using singular value decomposition analysis. Journal of Economics, 18, 137-146. [In Persian].

Zaranejad, M., Fagh-Majidi, A. & Rezaei, R.A. (2008). Exchange rate forecasting using artificial neural networks and ARIMA models. Quantitative Economics (Economic Studies), 19, 107-130. [In Persian]