Acharya, V. V., Almeida, H., & Campello, M. (2007). Is cash negative debt? A hedging perspective on corporate financial policies. Journal of financial intermediation, 16(4), 515-554.
Aflatooni, Abbas, Kazemi, Periyosh, Khatiri, Mohammad. (2022). Comparing the Cash Holdings Speed of Adjustment During Economic Prosperities and Recessions. Financial Management Strategy, 10(3), 141-160. (In Persian).
Anand, V., Brunner, R., Ikegwu, K., & Sougiannis, T. (2019). Predicting profitability using machine learning. Available at SSRN 3466478.
Angelovska M, Valentinčič A (2019) Determinants of cash holdings in private firms: the case of the Slovenian SMEs. Econ Bus Rev 22(1):5–36.
Asgharpour,Hossein,Rezaei, Sadegh, Hamidi Rozi, Daud, Heydari, Mansour. (2022). Investigating the Interaction Effects of Exchange Rate Regimes and Inflation on Iran's Economic Growth. Business Journal, 26(104), 47-74. (In Persian).
Attewell, P., & Monaghan, D. (2015). Data mining for the social sciences: An introduction. Univ of California Press.
Ball, R., & Shivakumar, L. (2005). Earnings quality in UK private firms: comparative loss recognition timeliness. Journal of accounting and economics, 39(1), 83-128.
Barboza, F., Kimura, H. and Altman, E. (2017). Machine learning models and bankruptcy prediction, Expert Systems with Applications 83: 405–417.
Bates TW, Kahle KM, Stulz RM (2009) Why do U.S. firms hold so much more cash than they used to? J Finance 64(5):1985–2021.
Bhuiyan MBU, Hooks J (2019) Cash holding and over-investment behavior in firms with problem directors. Int Rev Econ Financial 61:35–51.
Bigelli, M., & Sánchez-Vidal, J. (2012). Cash holdings in private firms. Journal of Banking & Finance, 36(1), 26-35.
Boubakri N, Ghoul S, Saffar W (2013) Cash holdings of politically connected firms. J Multinatl Finance Manag 23(4):338–355.
Breiman, L. (1996). Heuristics of instability and stabilization in model selection. The Annals of Statistics, 24(6), 2350-2383.
Breiman, L., Friedman, J., Olshen, R., & Stone, C. (1984). Classification and regression trees. Wadsworth Int. Group, 37(15), 237-251.
Campello M, Graham JR, Harvey CR (2010) The real effects of financial constraints: evidence from a financial crisis. J Financial Econ 97(3):470–487.
Chen D, Li S, Xiao JZ, Zou H (2014) The effect of government quality on corporate cash holdings. J Corp Finance 27:384–400.
Chen, Y. J., Lin, J. A., Chen, Y. M., & Wu, J. H. (2019). Financial forecasting with multivariate adaptive regression splines and queen genetic algorithm-support vector regression. IEEE Access, 7, 112931-112938.
Claveria, O., Monte, E., & Torra, S. (2017). Assessment of the effect of the financial crisis on agents’ expectations through symbolic regression. Applied Economics Letters, 24(9), 648-652.
Cortes, C., & Vapnik, V. (1995). Support-vector networks. Machine learning, 20, 273-297.
Dastile, X., Celik, T., & Potsane, M. (2020). Statistical and machine learning models in credit scoring: A systematic literature survey. Applied Soft Computing, 91, 106263.
David, M. (2015). Auto insurance premium calculation using generalized linear models. Procedia Economics and Finance, 20, 147-156.
Diaw A (2021) Corporate cash holdings in emerging markets. Borsa Istanbul Rev 21(2) 139–148.
Ditmar, A.; Mahrt-smith, j. & servaes, H. (2003). International Corporate Governance and Corporate Cash Holdings. Journal of Financial and Quantitative Analysis, 38(1), pp:111-133.
Donepudi PK, Banu MH, Khan W, Neogy TP, Asadullah ABM, Ahmed AAA (2020) Artifical intelligence and machine learning in treasury management: a systematic literature review. Int J Manag 11(11):13–22.
Ellington, M., Stamatogiannis, M. P., & Zheng, Y. (2022). A study of cross-industry return predictability in the Chinese stock market. International Review of Financial Analysis, 83, 102249.
Elyasiani, E., & Movaghari, H. (2022). Determinants of corporate cash holdings: An application of a robust variable selection technique. International Review of Economics & Finance, 80, 967-993.
Elyasiani, E., Jia, J., & Movaghari, H. (2019). Determinants of dividend payout and dividend propensity in an emerging market, Iran: an application of the LASSO. Applied Economics, 51(42), 4576-4596.
Faraji Tabrizi, Arshiya, Hejbar Kiani, Kambyz, Mimar Nejad, Abbas, Ghafari, Farhad (2021). Investigation of the Affecting on the Gross Domestic Product of Selected Countries with Emphasis on the Role of Exchange Rate; ARDL-PMG Approach. Economic growth and development research. (In Persian).
Foley CF, Hartzell JC, Titman S, Twite G (2007) Why do firms hold so much cash? A tax-based explanation. J Financial Econ 86(3):579–607.
García‐Teruel, P. J., Martínez‐Solano, P., & Sánchez‐Ballesta, J. P. (2009). Accrual’s quality and corporate cash holdings. Accounting & Finance, 49(1), 95-115.
Harford, J., Mansi, S. A., & Maxwell, W. F. (2008). Corporate governance and firm cash holdings in the US. Journal of financial economics, 87(3), 535-555.
Hastie, T., Tibshirani, R., Friedman, J. H., & Friedman, J. H. (2009). The elements of statistical learning: data mining, inference, and prediction (Vol. 2, pp. 1-758). New York: springer.
James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An introduction to statistical learning (Vol. 112, p. 18). New York: springer.
Jones, S., Johnstone, D., & Wilson, R. (2017). Predicting corporate bankruptcy: An evaluation of alternative statistical frameworks. Journal of Business Finance & Accounting, 44(1-2), 3-34.
Kim, J. B., Lee, J. J., & Park, J. C. (2015). Audit quality and the market value of cash holdings: The case of office-level auditor industry specialization. Auditing: A Journal of Practice & Theory, 34(2), 27-57.
Lerner, A. P. (1936). Mr. keynes general theory of employment, interest and money. Int'l Lab. Rev., 34, 435.
Li, F. (2010). The information content of forward-looking statements in corporate filingsa na¨ıve bayesian machine learning approach, Journal of Accounting Research 48(5): 1049– 1102.
Liu, H., & Zhang, Z. (2022). Probing the carbon emissions in 30 regions of China based on symbolic regression and Tapio decoupling. Environmental Science and Pollution Research, 29(2), 2650-2663.
Lozano MB, Yaman S (2020) The European financial crisis and firms’ cash holding policy: an analysis of the precautionary motive. Glob Pol 11(S1):84–94.
Maleki, Atefe, Jalalinia, Saeed, Hamzaei, Asghar (2022). The relationship between CEO experience and cash holding levels. Accounting and Management Perspective, 5(67), 10-1. (in persian).
Manoel AAS, Moraes MBC, Santos DFL, Neves MF (2018) Determinants of corporate cash holdings in times of crisis: insights from Brazilian sugarcane industry private firms. Int Food Agribus Manag Rev 21(2):201–217.
Miller MH, Orr D (1966) A model of the demand for money by firms. Q J Econ 80(3):413–435.
Mulai, Rahim (2022). The effect of accounting information quality on cash retention with emphasis on inflation. Accounting and Management Perspective, 5(61), 103-114. (in persian).
Mullainathan, S., & Spiess, J. (2017). Machine learning: an applied econometric approach. Journal of Economic Perspectives, 31(2), 87-106.
Opler, T., Pinkowitz, L., Stulz, R., & Williamson, R. (1999). The determinants and implications of corporate cash holdings. Journal of financial economics, 52(1), 3-46.
Oz, I. O., Yelkenci, T., & Meral, G. (2021). The role of earnings components and machine learning on the revelation of deteriorating firm performance. International Review of Financial Analysis, 77, 101797.
Ozbayoglu, A. M., Gudelek, M. U., & Sezer, O. B. (2020). Deep learning for financial applications: A survey. Applied Soft Computing, 93, 106384.
Ozkan A, Ozkan N (2004) Corporate cash holdings: an empirical investigation of UK companies. J Bank Finance 28(9):2103–2134.
Özlem, Ş., & Tan, O. F. (2022). Predicting cash holdings using supervised machine learning algorithms. Financial Innovation, 8(1), 1-19.
Palazzo, B. (2012). Cash holdings, risk, and expected returns. Journal of Financial Economics, 104(1), 162-185.
Perols, J. (2011). Financial statement fraud detection: An analysis of statistical and machine learning algorithms. Auditing: A Journal of Practice & Theory, 30(2), 19-50.
Pourgadimi, K., Bahri Sales, J., Jabbarzadeh Kangarliue, S., & ZavarRezaee, A. (2022). Presenting the developed model of Benish model with emphasis on audit quality features using neural network, vector machine and random forest. Advances in Finance and Investment, 3(6), 30-1.(in persian).
Rafi, M., Wahab, M. T., Khan, M. B., & Raza, H. (2020, January). ATM cash prediction using time series approach. In 2020 3rd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET) (pp. 1-6). IEEE.
Rajabzadeh, H., Gorganli davaji, J., naderian, A., & ashrafi, M. (2022). Forecast the operating cash flow of accepted companies In Tehran Stock Exchange using machine learning method. Management Accounting. (In Persian).
Ramnath, S., Rock, S., & Shane, P. B. (2008). Financial analysts' forecasts and stock recommendations: A review of the research. Foundations and Trends® in Finance, 2(4), 311-421.
Sarfraz M, Shah SGM, Ivascu M, Quereshi MAA (2020) Explicating the impact of hierarchical CEO sucession on small-medium enterprises’ performance and cash holdings. Int J Financial Econ.
Schapire, R. E., & Freund, Y. (2012). Boosting: Foundations and Algorithms. 1621 Cambridge, MA.
Schauten MB, Dijk D, van der Wall JP (2011) Corporate governance and the value of excess cash holdings of large European firms. Eur Financial Manag 19(5):991–1016.
Sezer, O. B., Gudelek, M. U., & Ozbayoglu, A. M. (2020). Financial time series forecasting with deep learning: A systematic literature review: 2005–2019. Applied soft computing, 90, 106181.
Sezer, O. B., Gudelek, M. U., & Ozbayoglu, A. M. (2020). Financial time series forecasting with deep learning: A systematic literature review: 2005–2019. Applied soft computing, 90, 106181.
Shekarkhah, Javad, Mortezazadeh, Mojtabi (2015). Comparison of cash holding determinants in different industries. Planning and Budget Quarterly, 20(1), 67-86. (in persian).
Shimin, L. E. I., Ke, X. U., Huang, Y., & Xinye, S. H. A. (2020). An Xgboost based system for financial fraud detection. In E3S Web of Conferences (Vol. 214, p. 02042). EDP Sciences.
Song, K. R., & Lee, Y. (2012). Long-term effects of a financial crisis: Evidence from cash holdings of East Asian firms. Journal of Financial and Quantitative analysis, 47(3), 617-641.
Subramaniam, V., Tang, T. T., Yue, H., & Zhou, X. (2011). Firm structure and corporate cash holdings. Journal of Corporate Finance, 17(3), 759-773.
Tian, S., Yu, Y., Guo, H. (2015). Variable selection and corporate bankruptcy forecasts. Journal of Banking & Finance, 52, 89-100.
ULUDAĞ, O., & GÜRSOY, A. (2020). On the financial situation analysis with KNN and naive Bayes classification algorithms. Journal of the Institute of Science and Technology, 10(4), 2881-2888.
Wahlen, J. M. and Wieland, M. M. (2011). Can financial statement analysis beat consensus analysts’ recommendations?, Review of Accounting Studies 16(1): 89–115.
Wu, H. C., Chen, J. H., & Wang, P. W. (2021). Cash Holdings Prediction Using Decision Tree Algorithms and Comparison with Logistic Regression Model. Cybernetics and Systems, 52(8), 689-704.
Wu, X., Wang, Y., & Tong, X. (2021). Cash holdings and oil price uncertainty exposures. Energy Economics, 99, 105303.
Xinyue, C., Zhaoyu, X., & Yue, Z. (2020). Using Machine Learning to Forecast Future Earnings. Atlantic Economic Journal, 48(4), 543-545.
Xinyue, C., Zhaoyu, X., & Yue, Z. (2020). Using Machine Learning to Forecast Future Earnings. Atlantic Economic Journal, 48(4), 543-545.
Zhang, X., & Zhou, H. (2022). The effect of market competition on corporate cash holdings: An analysis of corporate innovation and financial constraint. International Review of Financial Analysis, 82, 102163.
)