We invest in order to obtain excess returns on the investment. The excess return is calculated with respect to the risk free rate and implies taking on risk. It is necessary to quantify both return and risk on the portfolio level. Asset returns are correlated, and for this reason the correlation matrix is estimated to quantify precisely the correlation among the returns on portfolio assets. These coefficients will then enable us to describe the combined returns on the portfolio’s assets, and the risk of the portfolio. The basis of all quantitative portfolio management and theory today are given by the well-known Modern Portfolio Theory. We analyze in this paper ten American stocks from completely different industry sectors, part of the Standard & Poor’s 500 index. The period is from December 2010 to December 2015, monthly observations. Since the end of 1999, the S&P’s 500 stock index has lost an average of 3.3% a year on an inflation adjusted basis, compared with a 1.8% average annual gain during the 1930s when deflation afflicted the economy. In nearly 200 years of recorded stock-market history, no calendar decade has seen such a bad performance as the 2000s. The computer programs used in this work are MATLAB and Microsoft Excel. For optimization problems we mainly use the Excel Solver.
Published in | International Journal of Accounting, Finance and Risk Management (Volume 1, Issue 1) |
DOI | 10.11648/j.ijafrm.20160101.12 |
Page(s) | 11-18 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2016. Published by Science Publishing Group |
Portfolio Allocation, Stock Prices, Standard and Poor’s 500
[1] | Billio M., M. Getmansky, A. Lo and L. Pelizzon (2010), Econometric Measures of Systemic Risk in Finance and Insurance sectors, MIT WP 4774-10, NBER WP 16223, Journal of Financial Economics. |
[2] | Bodie, Zvi, Alex Kane, and Alan J. Marcus, 2005, Investments, 6th edition, McGraw-Hill/Irwin. |
[3] | Campbell, John Y., A. W. Lo, and A. C. MacKinlay. The Econometrics of Financial Markets. Princeton University Press, Princeton, NJ, 1997. |
[4] | Chavas, Jean-Paul, and M. T. Holt. ‘‘Economic Behavior under Uncertainty: A Joint Analysis of Risk Preferences and Technology’’ Review of Economics and Statistics. |
[5] | DeGroot, Morris H. Optimal Statistical Decisions. McGraw-Hill, New York, 1970. |
[6] | Dixit, Avinash K., and Robert S. Pindyck. Investment under Uncertainty. Princeton University Press, 1994. |
[7] | Dre`ze, Jacques. Essays on Economic Decisions under Uncertainty. Cambridge University Press, New York, 1987. |
[8] | Epstein, L., and S. Zin. ‘‘Substitution, Risk Aversion, and Temporal Behavior of Consumption and Asset Returns: An Empirical Investigation’’ Journal of Political Economy. 99(1991): 263–286. |
[9] | Elton, E. J., Martin, J. G., Brown, S. J., Goetzmann, W. N. (2014), Modern Portfolio Theory and Investment Analysis. United States: Wiley. |
[10] | Hirshleifer, Jack, and John G. Riley. The Analytics of Uncertainty and Information. Cambridge University Press, Cambridge, 1992. |
[11] | Hull, John. Options, Futures and Other Derivatives. Fifth Edition. Prentice Hall, 2002. |
[12] | J. F. Affleck-Graves and A. H. Money 1976, A comparison of two portfolio selection models, The Investment Analysts Journal,7(4), 1976, 35-40. |
[13] | Kahneman, Daniel, and A. Tversky. ‘‘Prospect Theory: An Analysis of Decision under Risk’’ Econometrica 47(1979): 263–191. |
[14] | Low, R. K. Y.; Faff, R.; Aas, K. (2016). "Enhancing mean–variance portfolio selection by modeling distributional asymmetries". Journal of Economics and Business. |
[15] | Mandelbrot, B. (2004). The (Mis) Behavior of Markets. New York: Basic Books. |
[16] | Markowitz, H. ‘‘Portfolio Selection’’ Journal of Finance. 6(1952): 77–91. |
[17] | Menezes, C., and D. Hanson. ‘‘On the Theory of Risk Aversion’’ International Economic Review. 11(1970): 481–487. |
[18] | Parigi B. and L. Pelizzon (2008), Diversification and Ownership Structure, CESifo Working Paper 1590. Journal of Banking and Finance, 32, 9, 1709-1722. |
[19] | Pelizzon L and G. Weber (2005) Efficient Portfolios Conditional on Housing: Evidence from the UCI survey, Trends in Saving and Wealth n.9/2005, Pioneer Investments. |
[20] | Pelizzon L and G. Weber (2008) Optimal portfolio composition when real assets and liabilities are taken into account, Trends in Saving and Wealth n.1/2008, Pioneer Investments. |
[21] | Pratt, John W. ‘‘Risk Aversion in the Small and in the Large’’ Econometrica 32(1964): 122–136. |
[22] | Savage, Leonard J. The Foundations of Statistics. Wiley, New York, 1954. |
[23] | Sharpe, William F. 1966. “Mutual Fund Performance.” Journal of Business. January, 39, pp. 119–38. |
[24] | Tobin, James. 1958. “Liquidity Preference as Behavior Towards Risk.” Review of Economic Studies, February. |
APA Style
Emi Malaj, Visar Malaj. (2016). Portfolio Allocation: An Empirical Analysis of Ten American Stocks for the Period 2010-2015. International Journal of Accounting, Finance and Risk Management, 1(1), 11-18. https://doi.org/10.11648/j.ijafrm.20160101.12
ACS Style
Emi Malaj; Visar Malaj. Portfolio Allocation: An Empirical Analysis of Ten American Stocks for the Period 2010-2015. Int. J. Account. Finance Risk Manag. 2016, 1(1), 11-18. doi: 10.11648/j.ijafrm.20160101.12
@article{10.11648/j.ijafrm.20160101.12, author = {Emi Malaj and Visar Malaj}, title = {Portfolio Allocation: An Empirical Analysis of Ten American Stocks for the Period 2010-2015}, journal = {International Journal of Accounting, Finance and Risk Management}, volume = {1}, number = {1}, pages = {11-18}, doi = {10.11648/j.ijafrm.20160101.12}, url = {https://doi.org/10.11648/j.ijafrm.20160101.12}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijafrm.20160101.12}, abstract = {We invest in order to obtain excess returns on the investment. The excess return is calculated with respect to the risk free rate and implies taking on risk. It is necessary to quantify both return and risk on the portfolio level. Asset returns are correlated, and for this reason the correlation matrix is estimated to quantify precisely the correlation among the returns on portfolio assets. These coefficients will then enable us to describe the combined returns on the portfolio’s assets, and the risk of the portfolio. The basis of all quantitative portfolio management and theory today are given by the well-known Modern Portfolio Theory. We analyze in this paper ten American stocks from completely different industry sectors, part of the Standard & Poor’s 500 index. The period is from December 2010 to December 2015, monthly observations. Since the end of 1999, the S&P’s 500 stock index has lost an average of 3.3% a year on an inflation adjusted basis, compared with a 1.8% average annual gain during the 1930s when deflation afflicted the economy. In nearly 200 years of recorded stock-market history, no calendar decade has seen such a bad performance as the 2000s. The computer programs used in this work are MATLAB and Microsoft Excel. For optimization problems we mainly use the Excel Solver.}, year = {2016} }
TY - JOUR T1 - Portfolio Allocation: An Empirical Analysis of Ten American Stocks for the Period 2010-2015 AU - Emi Malaj AU - Visar Malaj Y1 - 2016/11/08 PY - 2016 N1 - https://doi.org/10.11648/j.ijafrm.20160101.12 DO - 10.11648/j.ijafrm.20160101.12 T2 - International Journal of Accounting, Finance and Risk Management JF - International Journal of Accounting, Finance and Risk Management JO - International Journal of Accounting, Finance and Risk Management SP - 11 EP - 18 PB - Science Publishing Group SN - 2578-9376 UR - https://doi.org/10.11648/j.ijafrm.20160101.12 AB - We invest in order to obtain excess returns on the investment. The excess return is calculated with respect to the risk free rate and implies taking on risk. It is necessary to quantify both return and risk on the portfolio level. Asset returns are correlated, and for this reason the correlation matrix is estimated to quantify precisely the correlation among the returns on portfolio assets. These coefficients will then enable us to describe the combined returns on the portfolio’s assets, and the risk of the portfolio. The basis of all quantitative portfolio management and theory today are given by the well-known Modern Portfolio Theory. We analyze in this paper ten American stocks from completely different industry sectors, part of the Standard & Poor’s 500 index. The period is from December 2010 to December 2015, monthly observations. Since the end of 1999, the S&P’s 500 stock index has lost an average of 3.3% a year on an inflation adjusted basis, compared with a 1.8% average annual gain during the 1930s when deflation afflicted the economy. In nearly 200 years of recorded stock-market history, no calendar decade has seen such a bad performance as the 2000s. The computer programs used in this work are MATLAB and Microsoft Excel. For optimization problems we mainly use the Excel Solver. VL - 1 IS - 1 ER -