Markowitz theorem is one of the most popular techniques for asset management. The method has been widely used to solve many applications, successfully. In this paper, we present a multi objective Markowitz model to determine asset allocation by considering cardinality constraints. The resulted model is an NP-Hard problem and the proposed study uses two metaheuristics, namely genetic algorithm (GA) and particle swarm optimization (PSO) to find efficient solutions. The proposed study has been applied on some data collected from Tehran Stock Exchange over the period 2009-2011. The study considers four objectives including cash return, 12-month return, 36-month return and Lower Partial Moment (LPM). The results indicate that there was no statistical difference between the implementation of PSO and GA methods.
This paper studies the effects of cash conversion cycle (CCC) and size of selected firms listed on Tehran Stock Exchange (TSE) on four variables including return of assets, return of equities, tangible assets and equity multiplier. The study selects a sample of 105 firms listed on TSE and divides them into two groups of big and small sized companies over the period 2008-2012. Using a regression analysis, the study confirmed a meaningful relationship between different variables. In other words, in our survey, CCC and size negatively influence on tangible assets, they positively influence on equity multiplier as well as ROA but the effects of CCC and size on ROE for small and big firms are mixed.
During the past 65 years, there have been tremendous efforts on portfolio selection problem. The standard Markowitz mean–variance model to portfolio selection includes tracing out an efficient frontier, a continuous curve demonstrating the tradeoff between return and risk. This frontier can be often detected via standard quadratic programming, categorized in convex optimization. Traditional Markowitz problem has been recently extended into a new form of mixed integer nonlinear problems by considering various constraints such as cardinality constraints, industry limitation, etc. This paper proposes a mixed integer nonlinear programming to determine optimal asset allocation on Tehran Stock Exchange. The results have indicated that a petrochemical firm named Farabi has gained 44% of the portfolio followed by a drug firm named Kosar Pharmacy gaining 28%. In addition, banking sector was the third winning firm where Eghtesad Novin bank gained nearly 10% of the portfolio. Minerals and mining firms were the next sector in our portfolio where Gol Gohar Iron Ore and Tehran Cement collected 0.73% and 0.57% of the portfolio, respectively. In our survey, auto industry gained only 0.26% of the portfolio, which belonged to Saipa group.
During the past few years, Tehran Stock Exchange (TSE) has been changed into one of the most popular places to invest and index has been quadrupled in fewer than three years. As a result, many people have been attracted to invest on TSE market. This paper presents an empirical investigation to study the effects of investors’ personal characteristics including financial management skills, wealth and financial intelligence on investors’ risk tolerance among 384 randomly chosen investors who were active on TSE market in city of Esfahan, Iran. Using structural equation modeling, the study has determined that financial management skills, wealth and financial intelligence influence positively on investors’ risk tolerance.
This paper presents an empirical investigation to study the effects of macro-economic factors on the performance of stocks listed on Tehran Stock Exchange (TSE). The proposed study considers the effects of money supply, inflation rate, oil price, unforeseen changes in the course structure of interest rates as well as unanticipated changes in industrial production on stock price. Using seasonal information of stock price over the period 1997-2007 as well as regression analysis, the study has determined that risk premium of unforeseen changes in the course structure of interest rates, money supply, inflation rate and unanticipated changes in industrial production are meaningful when the level of significance is five percent. In other words, Arbitrage pricing theory model describing the expected return per share is reasonable and macro-level variables explain systematic risk on TSE.
One of the primary concerns on most business activities is to determine an efficient method for ranking mutual funds. This paper performs an empirical investigation to rank 42 mutual funds listed on Tehran Stock Exchange using Sortino method over the period 2011-2012. The results of survey have been compared with market return and the results have confirmed that there were some positive and meaningful relationships between Sortino return and market return. In addition, there were some positive and meaningful relationship between two Sortino methods.
Human resources play essential role on the success of many organizations and it is essential to learn more about the effects of human capital on the success of business units. This paper presents an empirical investigation to study the relationship between equity and intellectual capital among stocks listed on Tehran Stock Exchange over the period 2001-2007. Using Pearson correlation test, the study selects a sample of 77 firms and investigates the relationship between equity and three components of intellectual capital, namely; human capital, structural capital and customer capital. The study has detected a positive and meaningful relationship between equity and all components of the survey (? = 5%).
This paper presents an empirical investigation to predict future cash flows using present cash flow and accruals using the information of 96 selected firms listed on Tehran Stock Exchange over the period 2007-2011. The proposed study uses linear regression techniques to forecast future cash flow and the results indicate that cash flow and accruals together could provide more power to forecast cash flow. In addition, accrual provides future cash flow better than cash flow. The survey also performs an investigation on discretionary accrual and finds that the firms with higher accruals maintain lower return compared with firms with lower return. This means there is a clear evidence of discretionary accruals on Tehran Stock Exchange.
This paper presents an empirical investigation to study the effect of market management using Markowitz theorem. The study uses the information of 50 best performers on Tehran Stock Exchange over the period 2006-2009 and, using Markowitz theorem, the efficient asset allocation are determined and the result are analyzed. The proposed model of this paper has been solved using genetic algorithm. The results indicate that Tehran Stock Exchange has managed to perform much better than average world market in most years of studies especially on year 2009. The results of our investigation have also indicated that one could reach outstanding results using GA and forming efficient portfolio.