No abstract

Using extensive and comprehensive databases to select a subset of research papers, we aim to critically analyze previous empirical studies to identify certain patterns in determining the optimal number of stocks in well-diversified portfolios in different markets, and to compare how the optimal number of stocks has changed over different periods and how it has been affected by market turmoil such as the Global Financial Crisis (GFC) and the current COVID-19 pandemic. The main methods used are bibliometric analysis and systematic literature review. Evaluating the number of assets which lead to optimal diversification is not an easy task as it is impacted by a huge number of different factors: the way systematic risk is measured, the investment universe (size, asset classes and features of the asset classes), the investor’s characteristics, the change over time of the asset features, the model adopted to measure diversification (i.e., equally weighted versus optimal allocation), the frequency of the data that is being used, together with the time horizon, conditions in the market that the study refers to, etc. Our paper provides additional support for the fact that (1) a generalized optimal number of stocks that constitute a well-diversified portfolio does not exist for whichever market, period or investor. Recent studies further suggest that (2) the size of a well-diversified portfolio is larger today than in the past, (3) this number is lower in emerging markets compared to developed financial markets, (4) the higher the stock correlations with the market, the lower the number of stocks required for a well-diversified portfolio for individual investors, and (5) machine learning methods could potentially improve the investment decision process. Our results could be helpful to private and institutional investors in constructing and managing their portfolios and provide a framework for future research.

The integration of global equity markets has been a well-studied topic in the last few decades, particularly after stock market crashes. Most studies have focused on developed markets such as the US, Western Europe and Japan. The findings were that the degree of international co-movements among stock prices has substantially increased in the post-crash regime. In this paper we research the co-movements of German and Bosnian stock markets during and after the recent economic and financial crisis. International market integration means that assets of equal risk provide the same expected returns across integrated markets. This means fewer opportunities for risk diversification if the markets are integrated. It is also believed that stock market indices of integrated markets move together over the long run with the possibility of short-run divergence. There is considerable academic research on the benefits of international diversification. Investors who buy stocks in domestic as well in foreign markets seek to reduce risk through international diversification. The risk reduction takes place if the various markets are not perfectly correlated. The increasing correlation among markets during and after the crises has restricted the scope for international diversification. International stock market linkages are the subject of extensive research due to rapid capital flows between countries because of financial deregulation, lower transaction and information costs, and the potential benefits from international diversification. Most stock markets in the world tend to move together, in the same direction, implying positive correlation. In and after crises they tend to move together even more strongly. Thus, this paper aims to research if there are any diversification opportunities by spreading out investments across developed and underdeveloped capital markets. This research attempts to examine the scope of international diversification between German and Bosnian equity markets during the 6-year period from 2006 to 2011. We test the hypothesis of whether there are any risk diversification possibilities by spreading out the investments between German and Bosnian equity markets. In order to determine the mean-variance efficiency of portfolios we use the method of convex (quadratic and linear) programming. The hypothesis is tested with the Markowitz portfolio optimization method using our own software. The results of this research might enhance the efficiency of portfolio management for both types of capital market under analysis, and prove especially useful for institutional investors such as investment funds.

Background: Due to strong empirical evidence from different markets, existence of value premium became a financial theory standpoint. Although previous studies found that value stocks beat growth stocks in bearish and bullish markets, during the GFC, value stocks underperformed growth stocks. Objectives: This paper aims to examine the performance of value and growth stock portfolios after the GFC. Subjects of our analysis are constituent companies of the DJIA index, out of which portfolios of large-cap value and growth stocks have been constructed and evaluated. Methods/Approach: We measure the performance of stock portfolios, which are created based on the naïve diversification rule and random weighting approach. Statistical testing includes Levene’s homogeneity test, the Mann-Whitney U test, T-test, and the One-Sample T-test. Results: Growth stock portfolios outperform value stock portfolios after the GFC. The dominance of growth stock portfolios compared to value stock portfolios is significant, and the value premium disappears. Conclusions: Financial theory and investment management implications show that growth stocks have overtaken the dominance over value stocks since 2009. Causes might be in (1) expansionary monetary policy characterized by very low long-term interest rates and (2) high performance of the tech industry to which most growth stocks belong.

Diversification potential enables investors to manage their risk and decrease risk exposure. Good diversification policy is a safety net that prevents a portfolio from losing its value. A well-diversified portfolio consists of different categories of property with low correlations, while highly correlated markets have the feature of low possibilities for diversification. The biggest riddle in the world of investments is to find the optimal portfolio within a set of available assets with limited capital. There are numerous studies and mathematical models that deal with portfolio investment strategies. These strategies take advantage of diversification by spreading risk over several financial assets. Modern portfolio theory seeks to find the optimal model with the best results. This paper tries to identify relationships between returns of companies traded in South-East European equity markets. A Markowitz mean-variance (MV) portfolio optimization method is used to identify possibilities for diversification among these markets and world leading capital markets. This research also offers insight into to the level of integration of South-East European equity markets. Principal component analysis (PCA) is