Document Type : other
Author
Shiraz University
10.22099/ijes.2021.6846
Abstract
سرمایه‌گذاری مستقیم خارجی (FDI) به عنوان بخش جدایی‌ناپذیر از یک نظام اقتصادی باز و موثر بین المللی و عاملی کلیدی برای رشد و توسعه بین کشورها محسوب می‌شود. ایران به دلیل برخورداری از منابع عظیم نفت و گاز و همچنین بازارهای نسبتاً بزرگ، پتانسیل بالایی برای جذب سرمایه گذاری مستقیم خارجی به مراتب بیشتر از عملکرد خود دارد. این در حالی است که اعمال تحریم‌های مختلف بر کشور در سال‌های اخیر با ایجاد فضای روانی خصمانه و ریسک بالای فعالیتهای اقتصادی منجر به کاهش سرمایه گذاری مستقیم خارجی شده است.
در این مقاله قصد داریم با استفاده از روش کنترل ترکیبی (SCM) به بررسی تاثیرات گسترده تحریم‌های اقتصادی اعمال شده توسط ایالات متحده بر FDI ایران بین سال‌های 1980 تا 2020 بپردازیم. ما از طریق SCM تفاوت FDI را بین کشور تحت درمان (ایران) و ترکیبی (ایران ترکیبی) تخمین می‌زنیم.
نتایج نشان می‌دهد که تحریم‌ها منجر به کاهش تقریبا 12 میلیارد دلاری سرمایه گذاری مستقیم خارجی در مقایسه با وضعیت بدون تحریم شده است. به دنبال تشدید تحریم‌ها در دولت ترامپ و خروج ایالات متحده از برجام، اثرات منفی کاهشFDI به اوج خود یعنی 20 میلیارد دلار در سال 2020 رسیده است. علاوه بر این، آزمونهای دارونما نشان می‌دهند که نتایج از نظر آماری در سطح 10٪ معنادار هستند.
Keywords
Article Title [Persian]
چکیده های فارسی
Keywords [Persian]
- چکیده
- فارسی
- مقالات
- نشریه
Abensur, E. O., Moreira, D. F., & De Faria, A. C. R. (2020). Geometric brownian motion: An alternative to high-frequency trading for small investors. Independent Journal of Management & Production, 11(3), 1434-1453.
Bachelor, L. (1900). Theory of speculation. In Scientific Annals of the École normale supérieure, 17, 21-86.
Back, K. (2010). Asset pricing and portfolio choice theory. Oxford University Press, 80-81.
Beasley, J. E., Meade, N., & Chang, T. J. (2003). An evolutionary heuristic for the index tracking problem. Eur J Oper Res, 148, 621-643.
Biagini, S., & Pınar, M. Ç. (2017). The robust Merton problem of an ambiguity averse investor. Mathematics and Financial Economics, 11(1), 1-24.
Black, F., & Scholes, M. (1973). The pricing of options and corporate liabilities. Journal of political economy, 81(3), 637-654.
Browne, S. (1997). Survival and growth with a liability: Optimal portfolio strategies in continuous time. Mathematics of Operations Research, 22(2), 468-493.
Buckley, W. S., Brown, G. O., & Marshall, M. (2012). A mispricing model of stocks under asymmetric information. European Journal of Operational Research, 221(3), 584-592.
Canakgoz, N. A., & Beasley, J. E. (2008). Mixed-integer programming approaches for index tracking and enhanced indexation. Eur J Oper Res, 196, 384-399.
Castellano, R., & Cerqueti, R. (2012). Optimal consumption/investment problem with light stocks: A mixed continuous-discrete time approach. Applied Mathematics and Computation, 218(12), 6887-6898.
Chellathurai, T., & Draviam, T. (2007). Dynamic portfolio selection with fixed and/or proportional transaction costs using non-singular stochastic optimal control theory. Journal of Economic Dynamics and Control, 31(7), 2168-2195.
Chen, W., Zhang, H., Mehlawat, M. K., & Jia, L. (2021). Mean–variance portfolio optimization using machine learning-based stock price prediction. Applied Soft Computing, 100, 106943.
Chen, Z., Zhuang, X., & Liu, J. (2019). A sustainability-oriented enhanced indexation model with regime switching and cardinality constraint. Sustainability, 11(15), 4055.
Cornuejols, G., & Tütüncü, R. (2006). Optimization methods in finance (1th ed.). Cambridge University Press (Chapters 7-8).
de Oliveira, A. D., Filomena, T. P., Perlin, M. S., Lejeune, M., & de Macedo, G. R. (2017). A multistage stochastic programming asset-liability management model: An application to the Brazilian pension fund industry. Optimization and Engineering, 18(2), 349-368.
Dmitrašinović-Vidović, G., & Ware, A. (2006). Asymptotic behaviour of mean-quantile efficient portfolios. Finance and Stochastics, 10(4), 529-551.
Duffie, D. (2001). Dynamic Asset Pricing Theory (3th ed.). Princeton University Press. Princeton, NJ, 87-100.
Gambrah, P. S. N., & Pirvu, T. A. (2014). Risk measures and portfolio optimization. Journal of Risk and Financial Management, 7(3), 113-129.
Glasserman, P. (2003). Monte Carlo methods in financial engineering: Stochastic modelling and applied probability (3th ed.). Springer Science & Business Media (Chapter 3), 53.
Gulisashvili, A., & Stein, E. M. (2010). Asymptotic behavior of distribution densities in models with stochastic volatility. I. An International Journal of Mathematics, Statistics and Financial Economics, 20(3), 447-477.
Hörfelt, P. (2003). Geometric bounds on certain sublinear functionals of geometric Brownian motion. Journal of Applied Probability, 40(4), 893-905.
Kim, W. C., Kim, J. H., & Fabozzi, F. J. (2015). Robust Equity Portfolio Management, + Website: Formulations, Implementations, and Properties using MATLAB. John Wiley & Sons (Chapter 3).
Kourtis, A. (2016). The sharpe ratio of estimated efficient portfolios. Finance Research Letters, 17, 72-78.
Ladde, G. S., & Wu, L. (2009). Development of modified geometric Brownian motion models by using stock price data and basic statistics. Nonlinear Analysis: Theory, Methods & Applications, 71(12), e1203-e1208.
Lakner, P., & Ma Nygren, L. (2006). Portfolio optimization with downside constraints. Mathematical Finance: An International Journal of Mathematics, Statistics and Financial Economics, 16(2), 283-299.
Li, H., Huang, Q., & Wu, B. (2021). Improving the naive diversification: An enhanced indexation approach. Finance Research Letters, 39, 101661.
Lu, X., Yin, G., Zhang, Q., Zhang, C., & Guo, X. (2017). Building up an illiquid stock position subject to expected fund availability: Optimal controls and numerical methods. Applied Mathematics & Optimization, 76(3), 501-533.
Mariani, F., Recchioni, M. C., & Ciommi, M. (2019). Merton’s portfolio problem including market frictions: A closed-form formula supporting the shadow price approach. European Journal of Operational Research, 275(3), 1178-1189.
Markowitz, H. M. (1952). Portfolio selection. The Journal of Finance, 7(1), 77-91.
Markowitz, H. M. (1959). Portfolio Selection: Efficient Diversification of Investments. John Wiley Sons Ltd.
McFadden, D. (1989). Testing for stochastic dominance, in studies in the economics of uncertainty. Edited by T. B. Fomby and T. K. Seo, Springer, ch 7, 113-134.
Merton, R. C. (1971). Optimum consumption and portfolio rules in a continuous time model. Journal of Economic Theory, 3, 373-413.
Mota, P. P., & Esquível, M. L. (2016). Model selection for stock prices data. Journal of Applied Statistics, 43(16), 2977-2987.
Muteba Mwamba, J., & Suteni, M. (2010). An alternative to portfolio selection problem beyond Markowitz’s: Log optimal growth portfolio. Munich Personal RePEc Archive.
Pedersen, J. L., & Peskir, G. (2017). Optimal mean-variance portfolio selection. Mathematics and Financial Economics, 11(2), 137-160.
Pemy, M., Zhang, Q., & Yin, G. G. (2008). Liquidation of a large block of stock with regime switching. Mathematical Finance: An international Journal of Mathematics, Statistics and Financial Economics, 18(4), 629-648.
Pun, C. S., & Wong, H. Y. (2016). Resolution of degeneracy in Merton's portfolio problem. SIAM Journal on Financial Mathematics, 7(1), 786-811.
Reddy, K., & Clinton, V. (2016). Simulating stock prices using geometric Brownian motion: Evidence from Australian companies. Australasian Accounting, Business and Finance Journal, 10(3), 23-47.
Roman, D., Mitra, G., & Zverovich, V. (2013). Enhanced indexation based on second-order stochastic dominance. European Journal of Operational Research, 228(1), 273-281.
Sharpe, W. (1966). Mutual fund performance. The Journal of Business, 39(1), 119-138. Retrieved August 2, 2021, from http://www.jstor.org/stable/2351741.
Sharpe, W. F. (1994). The sharpe ratio. Journal of Portfolio Management, 21(1), 49-58.
Spinu, F. (2015). Buy-and-hold versus constantly rebalanced portfolios: A theoretical comparison. Journal of Asset Management, 16(2), 79-84.
Tie, J., Zhang, H., & Zhang, Q. (2018). An optimal strategy for pairs trading under geometric Brownian motions. Journal of Optimization Theory and Applications, 179(2), 654-675.
Tourin, A., & Yan, R. (2013). Dynamic pairs trading using the stochastic control approach. Journal of Economic Dynamics and Control, 37(10), 1972-1981.
Wei, J., & Wang, T. (2017). Time-consistent mean–variance asset–liability management with random coefficients. Insurance: Mathematics and Economics, 77, 84-96.
Weiner, S. M. (2004). Should stochastic volatility matter to the cost‐constrained investor? Mathematical Finance: An International Journal of Mathematics, Statistics and Financial Economics, 14(1), 131-139.
Xie, S. (2009). Continuous-time mean–variance portfolio selection with liability and regime switching. Insurance: Mathematics and Economics, 45(1), 148-155.
Xie, S., Li, Z., & Wang, S. (2008). Continuous-time portfolio selection with liability: Mean–variance model and stochastic LQ approach. Insurance: Mathematics and Economics, 42(3), 943-953.
Xu, F., Wang, M., Dai, Y. H., & Xu, D. (2018). A sparse enhanced indexation model with chance and cardinality constraints. Journal of Global Optimization, 70(1), 5-25.
Yam, S. C. P., Yung, S. P., & Zhou, W. (2012). Optimal selling time in stock market over a finite time horizon. Acta Mathematicae Applicatae Sinica, English Series, 28(3), 557-570.
Yunita, R., Dharmawan, K., & Harini, L. P. I. (2015). Menentukan portofolio optimal pada pasar saham yang bergerak dengan model gerak brown geometri multidimensi. E-Jurnal Matematika, 4(3), 127-134.
Zeng, Y., & Li, Z. (2011). Optimal time-consistent investment and reinsurance policies for mean-variance insurers. Insurance: Mathematics and Economics, 49(1), 145-154.
Zhu, J. (2009). Testing for expected return and market price of risk in Chinese A and B share markets: A geometric Brownian motion and multivariate GARCH model approach. Mathematics and Computers in Simulation, 79(8), 2633-2653.
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