Optimal Asset Allocation in the Presence of Macroeconomic Uncertainties and International sanctions against Iran

Document Type : Research Paper


1 Assosiate Professor of Bu-Ali Sina university

2 PhD student of Bu-Ali Sina University


The current study addresses an estimation of investor's optimal portfolio under conditions of uncertainty by using a combination of artificial neural network and Markowitz models. For this purpose, such assets as stock prices, house prices, coin and bonds price are used with monthly data over the period 1378-1392. Three variables including inflation uncertainty, oil uncertainty and free market dollar rate are used as state variables to investigate the impact of macroeconomic shocks on investor's decisions when choosing an optimal portfolio. Autoregressive conditional heteroskedasticity (GARCH) is used to estimate state variables. Following an estimation of the state variables, assets return and uncertainty were measured using Multi Layer Perceptron (MLP) and Radial Basis Function (RBF) neural networks. The results obtained from neural network model are used as input variables in estimation of Markowitz's optimal portfolio. The results of analyzing mean variance show that housing is the dominant asset among uncertain assets over the period of real-estate boom holding the largest share of assets. Over the recent periods, considered to be the period of housing downturn, investors no longer include housing in their portfolio turning instead to stocks and coins as prominent alternatives. Generally, bonds have shown to be an asset with no uncertainty in all the periods making them a reliable alternative in the investor's optimal portfolio.



جعفریه، حمیدرضا، معتمدی، نگار و ملایی، الهه (1385). شبکه‌های عصبی و الگوریتم ژنتیک در تجارت، ماهنامة تدبیر، 17(177)، 62 ـ 67.
حیدرپور، افشین و پورشهابی، فرشید (1391). تبیین آثار نااطمینانی اقتصادی بر متغیرهای کلان اقتصاد، فصلنامة مجلس و راهبرد، 19(71)، 125 ـ 148.
حیدری، حسن و بشیری، سحر (1391). ﺑﺮرﺳﻲ راﺑﻄﻪ ﺑﻴﻦ ﻧﺎاﻃﻤﻴﻨﺎﻧﻲ ﻧﺮخ واﻗﻌﻲ ارز و ﺷﺎﺧﺺﻗﻴﻤﺖ ﺳﻬﺎم در ﺑﻮرس اوراق ﺑﻬﺎدار ﺗﻬﺮان: ﻣﺸﺎﻫﺪاﺗﻲ ﺑﺮ ﭘﺎﻳة ﻣﺪل VAR-GARCH، ﻓﺼﻠﻨﺎمة ﺗﺤﻘﻴﻘﺎت ﻣﺪلﺳﺎزی اﻗﺘﺼﺎدی، 9، 71 ـ 92.
دهمرده، نظر، صفدری، مهدی و پورشهابی، فرشید (1388). مدل‌سازی نااطمینانی تورم در اقتصاد ایران، فصلنامة پژوهش‌ها و سیاست‌های اقتصادی، 17(50)، 77 ـ 92.
قلی‌زاده، علی‌اکبر و طهوری متین، مسعود (1390). انتخاب سبد دارایی‌ها در دورة رکود و رونق بازار مسکن، فصلنامة پژوهش‌های اقتصادی، 11 (3)، 71 ـ 90.
منجمی، سیدامیر حسین، ابزری، مهدی و رعیتی شوازی، علیرضا (1388). پیش‌بینی قیمت سهام در بازار بورس اوراق بهادار با استفاده از شبکة عصبی فازی و الگوریتم‌های ژنتیک و مقایسة آن با شبکة عصبی مصنوعی، فصلنامة اقتصاد مقداری، 6(3)، 1 ـ 26.
Butt, N. (2012). Approximate Methods for Dynamic Portfolio Allocation Under Transaction Costs, Western Ontario University Press.
Campbell, John Y. & Chacko, George, Rodriguez, Jorge & Viciera, Luis (2004). Strategic Asset Allocation in a Continous-Time VAR Model, Working Paper, 9547.
Chinzara, Z. (2012). Macroeconomic Uncertainty and Conditional Stock Market Volatility in South Africa, South African Journal of Economics,1(79), 27-49.
Collins, P. & Stampfli, J. (2009). Static vs. Dynamic Investment Policy: Matching Asset Management to Investor Risk Preferences, Retrieved from http://www.ideas.repec.org.
Collomb, A. (2004). Dynamic Asset Allocation by Stochastic Programming Methods, Retrieved from Canadian Institute for Health Information website: http:// web.stanford.edu/group/SOL/dissertations/collombthesis.pdf.
Constantinides, G. (2002). Rational Asset Prices, Journal of Finance, 4(57), 1567-1591.
Dahle, E. & Drachmann, J. (2011). Dynamic Asset Allocation Modeling and its Applicability for Institutional Investors, Copenhagen University Press.
Dimson, E. & Marsh, P. & Staunton, M. (2002). Triumph of the Optimists: 101 Years of Global Investment Returns, Princeton University Press.
Elton, E.J. & Gruber, M.T. (1997). Modern Portfolio Theory, 1950 to date, Journal of Banking & Finance, 21, 1743-1759.
Farzanegan, M.R. & Markwardt, G. (2009). The Effects of Oil Price Shocks on the IranianEconomy, Energy Economics, 31(1), 134-151.
Fernandez, A. & Gomez, S. (2007). Portfolio Selection Using Neural Networks, Computers & Operations Research, 34, 1177-1191.
Friedman, M. (1977). Nobel Lecture: Inflation and Unemployment, Journal of Political Economy, 85, 451-72.
Hartman, R. (1972). The Effects of Price and Cost Uncertainly on Investment, Journal of Economic Theory, 5, 258-266.
Hubbard, D. (2007). How to Measure Anything: Finding The Value of Intangible in Business, New York: John Wiley & Sons.
Hufbauer, G. (1997). US Economic Sanctions: Their Impact on Trade Jobs, and Wages, Working Paper 97-01, Institute for International Economics Washington D.C.
Haidar, J.I. (2013). Sanctions and trade diversion: Exporter-level Evidence from Iran, VoxEU.org, 9 April, Retrieved from http://www.voxeu.org/article/iran-sanctions-and-diverted-trade-exporter-level-evidence.
Kierkegaard, K. (2006). Practical application of the Modern Portfolio Theory, Retrieved from Canadian Institute for Health Information website: http:// http://www.diva-portal.org/smash/get/diva2:4384/fulltext01.pdf
Kumar M., S., Ganapati, P., Babita, M. & Ritanjali, M. (2012). Improved Portfolio Optimization Combining Multi-objective Evolutionary Computing Algorithm and Prediction Strategy, IAENG Conferences-World Congress on Engineering (WCE-2012), 4-6 July, London, U.K.
Lisbao, P. (2000). Business Applications Of Neural Networks: The State of the Art of Real World Application,Singapore, World Scientific, 64-66.
Levisauskaite, K. (2010). Investment Analysis and Portfolio Management, Retrieved from Canadian Institute for Health Information website:http://www.bcci.bg/ projects/latvia/pdf/8_IAPM_final.pdf.
Markowitz, H.M. (1952). Portfolio Selection, The Journal of Finance, 7(1), 77-91.
Markowitz, H. (1987a). Mean-Variance Analysis in Portfolio Choice and Capital Markets, Basil Blackwell, New York.
Markowitz, H. (1987b). Portfolio Selection, Wiley, New York.
Pluciennik, P. (2010). Forecasting Financial Processes by Using Diffusion Models, Journal of Dynamic Economics Models, 51-60.
Steiner, M. & Wittkemper, H. (1997). Portfolio Optimization with a Neural Network Implementation of the Coherent Market Hypothesis, European Journal of Operational Research, 1(100), 27-40.
Siegel, J. (2002). Stocks for the Long Run: The Definitive Guide to Financial Market Returns and Long-Term Investment Strategies, New York: McGraw-Hill.

Zimmermann, H.G. & Grothmann, R. (2005). Active Portfolio-Management based on Error Correction Neural Networks, Intelligent Systems in Accounting, Finance and Management, 1(13), 33-40.

Volume 50, Issue 4 - Serial Number 4
January 2016
Pages 959-988
  • Receive Date: 12 October 2014
  • Revise Date: 06 July 2015
  • Accept Date: 06 October 2015
  • First Publish Date: 22 December 2015